CIRP Annals - Manufacturing Technology 58 (2009) 588–607

Contents lists available at ScienceDirect

CIRP Annals - Manufacturing Technology

journal homepage: http://ees.elsevier.com/cirp/default.asp

Interaction of manufacturing process and machine tool

C. Brecher (2)*, M. Esser, S. Witt

Laboratory for Machine Tools and Production Engineering, RWTH Aachen University, Aachen, Germany

ARTICLE INFO ABSTRACT

Keywords: Analysing the machine tool and the machining process individually is necessary in order to tackle the Machine challenges that both have to offer. Nevertheless, to fully understand the manufacturing system, e.g. Modelling vibrations, deflections or thermal deformations, the interactions between the manufacturing process and Process–machine interaction the machine tool also have to be analysed. In cutting, grinding and forming there are important effects that can only be explained through these interaction phenomena. This paper presents the current state of research in process–machine interactions for a wide variety of manufacturing processes. It is based on the findings of the CIRP research group ‘‘Process Machine Interaction (PMI)’’ and on the international publications in this field. Cutting with defined and undefined cutting edges as well as sheet and bulk metal forming are the key processes. The emphasis is on understanding, modelling and simulating all modes of interaction. Additional needs of research in process–machine interaction are identified for future projects. ß 2009 CIRP.

1. Introduction and historical review first time a series of different projects on process–machine interactions during grinding. In 2004, Altintas and Weck [10] In an industrial context, production costs are often lowered by summarised a large number of the characteristics of the reducing manufacturing times. With this as the objective, machine regenerative effects during grinding, turning and milling. Research tools are continually being improved with respect to their speed, results for the various forming procedures are very sparse. To date, acceleration and process force. Moreover, processes are also there is no comprehensive compilation of the mechanisms of continually undergoing optimisation. Higher cutting and forming interaction for the different processes. For this reason, a vast range speeds, improved machine-tool concepts, wider contact and of different topics in the field of process–machine interaction have greater degrees of forming should enable processes to be carried been gathered together in the CIRP Working Group ‘‘Process– out more economically. The problem is that when optimised Machine Interaction’’. For the purposes of this paper, the topics manufacturing concepts are developed, the machines operate have been complemented, structured, generally summed up and particularly fast, but they either do not meet the requirements in evaluated. terms of part quality or else the machine components and tools Fig. 2 shows the possible interactions between machine and have short service lives. process, using a milling machine as an example. The continuity of interaction, i.e. the continuous and mutual influence exerted by 1.1. Motivation both machine and process, results in the often unpredictable effects of the interaction. In many cases, predictions can only be In many cases, the reason for such problems is not due to the made by means of complex simulations. incorrect planning of machines or processes, but rather due to The challenges arising from this were recognised many years additional effects that can only be explained by the interaction of ago, but were at first investigated only tentatively. machine and process. Fig. 1 shows the results of such effects, using various processes as examples. In research, these production–technical processes and the mechatronic structures involved, i.e. the machine tools have been dealt with separately up to now. However, in recent years it has been considered increasingly necessary to treat processes and structures in an integrated way, thereby overcoming the wide- spread independent treatment of such systems. Observations generally originate in details and certain specific mechanisms of the interaction. Recently, Biermann et al. [28] documented for the

* Corresponding author. E-mail address: [email protected] (C. Brecher). Fig. 1. Motivation for PMI research.

0007-8506/$ – see front matter ß 2009 CIRP. doi:10.1016/j.cirp.2009.09.005 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 589

describing the individual components of the overall system. This section is dedicated to achievements in the research of machine tools and processes as individual elements. Most of these have been summarised in keynote papers over the last few years.

2.1. Structural behaviour of machine tools

The task of machine tools and their components is to generate the movements and forces necessary for executing a process. It is presupposed that the available forces are great enough and the movements fast and precise enough to complete the process successfully. However, disturbances that take effect during the process may negatively influence the behaviour of the machine. In general, such disturbances are forces, moments Fig. 2. Interactions between process and machine tool. or heat input. The relationship between the thermal load of the machine and the thermal drift of the cutting process is very complex. Due to the 1.2. History of international PMI research inaccurate knowledge of heat sources, thermal boundary condi- tions, mechanisms of heat transfer, etc., precise prediction of the The first work on interaction in cutting machines was carried behaviour of a standard machine tool at the design stage is very out as early as the 1950s. Some researchers found that chatter in difficult [202]. The research in this field has been summarised in turning and milling operations does not result from negative keynote papers by Bryan [53] and Weck et al. [202]. Some models damping of the chip formation process. Instead, they outlined self- offer a reliable correlation between thermal load and displace- excited vibrations with a force–displacement interaction between ment, but the metrological effort as well as the model complexity is the machine tool and the cutting process [119,143,181]. Based on high. this work, an effective circle of researchers formed within the CIRP- The correlations between force and displacement are easier to Ma group (today: STC M). From 1969 onwards, this group set itself handle because in general the force acts solely at the tool centre the goal of ascertaining the dynamic cutting force coefficients that point. The measurement of the correlation between force and describe the cutting process within this interaction [189]. displacement in static and dynamic cases has already been state- Ultimately, it was possible to predict the chatter phenomenon of-the-art for a long time. Nowadays it is also possible to simulate within certain limits [47,159]. Since then, modelling the range of the determination of machine behaviour. The relevant advances actions that includes processes and machines in a mutually were noted in 2005 by Altintas et al. [11]. Fig. 4 summarises the interactive system has become established as a possible means of possibilities of the computer-supported analysis, prediction and explaining complex behaviour. design of a machine tool. The broad application of this analysis concept resulted in a large Moreover, in the past few years many new challenges in the number of papers in all areas of cutting with defined and undefined analysis of machine-tool structures have been described. Here, we cutting edges. For some years, forming operations have also been must mention in particular the stringent requirements placed on viewed within the closed loop formed by process and machine. machine tools by high process speeds [190], the emergence of Since 2004, the (sometimes widely varying) research papers have parallel-kinematic structure [203], and the increased use of been summarised as one of the Priority Programs of the German adaptronic devices [151]. The fields of research mentioned and Research Foundation (DFG) (Fig. 3). the respective advances that have been made provide a solid At the international level, within the framework of the CIRP foundation with regards to the modelling of machine structures in General Assemblies and winter meetings, working sessions of the interactive systems. PMI (Process–Machine Interactions) Collaborative Working Group were held between 2003 and 2008. This group created a forum for 2.2. Cutting and grinding processes the presentation of very different papers, with the objective of comprehending and predicting such effects. The purpose of this In cutting and grinding, many parallel developments have been keynote paper is not least to summarise the research results carried out. The move towards faster processes may be one of the presented there. most important fields of research. Schulz et al. and To¨nshoff et al. have summarised these process developments for cutting and 2. Modelling of single phenomena grinding respectively [177,192]. Fig. 5 shows other important fields of research. Overviews of the Long before the interaction between machine tool and process various modelling approaches are given in [46,191] for grinding was treated, great advances were made in understanding and and in [139] for cutting.

Fig. 3. History of PMl research. Fig. 4. Research on machine tool behaviour: virtual prototypes [11]. 590 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

3. Developments describing defined cutting edge phenomena

3.1. Analysis of interaction phenomena

In last two decades the interaction of machine and process in defined cutting edge machining has been studied intensively. Many analyses recognised the need to take into account the relevant interactions in the machine-process system while carrying out a simulation of production processes. Vormann outlined the importance of simulation, including necessary interactions for the planning and adjustment of modern produc- tion systems in [198]. He claimed that no production model, i.e. complete simulation of a process and a machine, is possible without a consideration of mutual influences between them. In the article by Brecher [41], some important uncertainties during the simulation of such machine-process systems were highlighted as Fig. 5. Research on cutting and grinding processes. well as the demands placed on models for acceptable simulation accuracy. Witt [212] carried out comprehensive research relating As a basis for modelling process–machine interactions, forces to the interactions between the components of complex produc- are of high relevance. FEM models are currently used to predict tion machines (Fig. 7). He argued in favour of extending established process forces. Due to unclear effects at the clearance face of simulation tools by incorporating the relevant interaction between cutting tools and due to the unknown grain geometry in grinding, the machine tool, the workpiece and the cutting process, as this is the quality of the results is often inadequate. Empirical models give essential for reliable process planning and optimisation at the more exact but less general results. machine development stage. Thermal effects in grinding influence the quality of the By taking into account the interactions in a machine tool as machined part. Refs. [44,140] contain the state-of-the-art with shown in Fig. 7, the manufacturing process includes, per definition, respect to friction, temperature and cooling in grinding processes. a workpiece, a manufacturing technology and a tool. The machine In cutting, dry machining is an option for a large variety of tool unites a machine structure, controls and clamping fixtures. materials. The current state of research has been summarised in These interactions are common to different production machines [125,204]. and must be regarded as a system when analysing performance In cutting, the material of the workpiece and the tool can and optimising process parameters. In machine tools such as lathes completely change the process behaviour. New workpiece materials and milling machines, the direct interaction of the machine [132,193] and coatings of cutting tools [126] have therefore been structure with the numerical control system greatly influences the researched extensively. Byrne et al. give a broad overview of these dynamic behaviour of the machine and hence the characteristics of and other developments in the cutting process [54]. the process. This behaviour must be represented very accurately for the integrated simulation of industrial machining processes in 2.3. Forming processes order to minimise errors from machine modelling. Another interaction occurs at the interface of the mechatronic system Forming processes usually serve as means of mass production. and a machining process between the cutting edge and the The wide variety of different forming operations can generally be workpiece. This interaction determines the quality of a part, classified as bulk or sheet metal forming operations. possible tolerances and stock removal rate, which might be limited For sheet and tube forming, a wide variety of process by process instabilities. In order to achieve a comprehensive kinematics and their characteristics are summarised in evaluation on the basis of simulation, the influence of machine tool [124,150,176]. Among these are incremental forming processes properties on the process and of the process on the machine tool that allow very flexible manufacturing of parts and forming with must be precisely depicted. Unacceptable simplifications might media (oil, gas) which can provide tubes with complex geometries. lead to significant errors in simulation results and thus to faulty Bulk metal forming is usually carried out at higher tempera- conclusions relating to the process behaviour. Certain criteria are tures and very high process forces. Incremental forming can needed in order to assess and approve cutting processes. On the simplify these difficult conditions. The state-of-the-art in this area one hand, process stability and processing time are important is summarised in [89]. Modern incremental rolling process characteristics, as they indicate productivity and profitability. On kinematics can be seen, for example, in Fig. 6, top right. the other hand, the surface quality and machining tolerances for a The behaviour of the workpiece material during forming is the machined part are also of significance when carrying out an real challenge when describing any forming process. The literature dealing with this problem (see also Fig. 6)is summarised in [8,19].

Fig. 7. Interactions and their analysis in machining with defined cutting edges Fig. 6. Research on forming processes. [212]. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 591 evaluation. To assess a production process using simulation the Modelling of machining processes was expanded for non-trivial latter must represent the properties of a process with sufficient cases like ball-end milling, milling with helical end mills, etc. in accuracy. In order to carry out this task, all the above-mentioned [58,61,64,167,175]. Denkena et al. [61] presented a method for interactions must be considered in an integrated simulation prediction of cutting forces in milling on the basis of empirically system. In the literature, there are sources focusing either on the determined specific cutting forces. The latter were calculated from machining process or the machine tool modelling, as well as the measured milling forces, which were subsequently related to approaches analysing the interaction of the two. the engagement-dependent undeformed chip area. The dynamics as well as damping of the process is not considered in this model. 3.2. Identification of model parameters Schmidt [175] from the same research circle presented a procedure for predicting cutting forces for helical end mills using a 3.2.1. Machine tool geometrical model considering serrated chips and a parametric A study of the interactions between a process and a machine force model. The force model used by Schmidt is described in detail requires appropriate methods to represent all the necessary in [62] by Denkena. Riviere-Lorphevre et al. [167] addressed the properties of the objects modelled. On the machine tool side, the issue of modelling a helical end mill and concentrated on integrated models providing data on static and dynamic behaviour implementing a general algorithm for evaluating cutting force of the structure must be appropriately parameterised. According to parameters. He proposed an algorithm for retrieval of the cutting Witt [212], there have been no approaches to date which enable the force model parameters from the measured data set. parameters of machine elements in multi-body models, i.e. stiffness Another interesting approach for calculating process forces in and damping coefficients, to be identified in a reliable way without milling is provided by Moreau et al. [147]. The displacement of the subsequent verification using measured data. The dynamic beha- milling tool was measured directly during the process by means of viour is determined by impacting the machine tool structure with a contact-free sensors. Following this, the frequency response of the dynamic force and measuring the response in the form of a tool was determined by means of impulse hammer testing. On the displacement. The measured frequency response function (FRF) is basis of known displacement in stable and unstable processes and used as a basis for the subsequent curve-fitting procedure, which compliance of the tool, conclusions about the process forces were decreases the amount of data in FRF by mathematical approximation drawn. of the curve. Comprehensive treatment of measurement procedures In plunge milling operations, the force prediction was studied in is presented in [11,29,107,187,200]. [58] by D’Acunto et al. The authors used a mechanistic model on The number of uncertain parameters in complex machine tool the basis of specific cutting pressure coefficients for predicting models is generally very high. A manual correction of the values is forces. The model does not include the influence of process extremely complicated and impractical. Considering this, Altinats dynamics and tool wear. The latter phenomenon was addressed by et al. developed a method for optimising multi-body model Ozlu et al. [157], who proposed a model for calculating cutting parameters on the basis of measured frequency response functions forces in an orthogonal cutting process under consideration of (Fig. 8) [11]. This method is not suitable, however, for carrying out friction in primary and secondary shear zones. an optimisation of all the parameters at once. Only the vibration Rapid development of new production processes, e.g. HPC (high modes should be selected which are determined by certain performance cutting) machining, is leading researchers to recon- components. For instance, the parameters of the anchoring sider some established models that do not cope with the relevant elements may be optimised by observing that range of the requirements of modern machining processes. Brecher et al. [35] frequency response function (FRF) where such vibrations might presented a test bench for experimental identification of the occur. Beginning with a certain initial value, the different parameters of a complex force model for a milling process based on parameters can be optimised iteratively. Additional work on this the study of orthogonal axial turning. Fig. 9 represents the test set- topic was carried out in [178]. up. Such a construction allows individual observation of the inner and outer modulation of chip thickness in order to accurately 3.2.2. Process determine dynamic specific cutting-force parameters. On machining process side, accurate modelling is of great The results of this study are detailed in [42]. The model importance for achieving a reliable simulation of production characteristics obtained in this research will provide higher levels processes. Beginning with the pioneering research of Kienzle, of accuracy for stability simulations compared to conventional many approaches for predicting cutting forces, e.g. mechanistic, methods. linear, etc., were developed [73,121,182]. In recent years, many analyses were carried out with the aim of improving force models 3.3. Overview of simulation approaches for different processes. Budak et al. developed orthogonal to oblique cutting model which enables the prediction of the cutting The state-of-the-art simulation of cutting processes under force [50]. consideration of machine and process properties can be carried out along with different methods. When simulating the interactions between a machine, workpiece and process, a distinction is generally made between a simulation using a substitute model of machine properties and a coupled simulation, as revealed by Witt

Fig. 8. Measurement of the dynamic behaviour of a machining centre [11]. Fig. 9. Test bench for analysing the coefficients of dynamic cutting forces [35]. 592 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

In [174], Schermann et al. carried out some explicit finite element calculations, as shown in Fig. 10 (bottom right). A complete machine model was coupled with a finite element model of a turning process. This involved extremely long calculation times. Furthermore, it was not possible to represent process stability due to the above mentioned reasons. As shown in Fig. 10 (bottom centre), Witt analysed the coupling of a flexible multi- body simulation and an analytical process model [212]. The machining process was represented by means of suitable models in a digital block simulation, and coupled with a flexible multi-body machine model [11,33]. Both the surface properties of the workpiece for modelling the regenerative effect as well as the geometrical machining history were calculated in subprograms of Fig. 10. Overview of approaches for coupled simulation [212]. the digital block simulation. With the aid of this simulation approach, a comprehensive representation of machining processes [212] in Fig. 10. The substitute model combined with a suitable is possible, taking into account the process forces, process stability force model implies a representation of machine properties. Many and machining result. approaches use some analytical models to represent the cutting process combined with machine properties in the form of 3.4. Model integration frequency response functions, which are either measured or simulated. By means of curve-fitting, the frequency response 3.4.1. Turning function can be represented in a suitable form in the time domain. The modelling of production processes is used for predicting an Such process simulations using measured FRF are carried out in outcome depending on the chosen settings. Simulation of the [10,20,72,114,117,183,185,206] in order to simulate the process machine tool–process system is used in a majority of published forces, process stability and resulting workpiece surface in turning studies for analysing the stability of machining. Beyond this, there and milling, as presented in Fig. 10. A similar procedure is chosen in are approaches for predicting workpiece surface quality or for [221], the only difference being that the machine properties is analysing and optimising NC-routines for a machining task, etc. provided by means of finite element simulation (Fig. 10, top The stability of turning operations was recently addressed in centre). Another option for representing the cutting process is the [52,156,157]. Ozlu and Budak [156] presented an analytical finite element simulation of chip formation. The approach approach for modelling the stability of turning operations. Along presented by Piendl and Aurich [158], considers the structural– with the multi-dimensional dynamics of the system, the authors mechanical behaviour of a machine and a workpiece. They used a considered the true cutter geometry in the turning process model substitute workpiece and tool integrated into an FE model of the (Fig. 11: stability chart, green square (For interpretation of the cutting process, which is presented in Fig. 10 (top right). This references to colour, the reader is referred to the web version of the approach is limited by the number of elements such models can article.): stable test trial, red dot: chatter). The study revealed a include. This means that neither the workpiece surface nor several considerable influence of the nose radius on the stability of rotations of the tool may be simulated. In addition, some common turning. This issue was further developed in [157]. The article methods of representing chip formation in the FE cutting provided a comparison of multidirectional and single-directional simulation do not provide geometrical information about the simulation systems in the context of true geometry modelling. The workpiece surface behind the cutting edge. Damage criteria are conclusion was drawn that single directional systems do not used to delete elements in the area of the chip root. Where cutting provide reliable results for inserts with a larger corner radius or simulations are carried out with the aid of Arbitrary Lagrangian inclination angle. Simulation using the multi-dimensional stability Eulerian (ALE) methods, the material flows through a previously models was recommended for such systems. defined workpiece mesh. Neither of these approaches is suitable for representing the resulting workpiece surface. This is required, however, for simulating regenerative vibra- tions [183]. The above-mentioned approach is thus only suitable for representing chip formation and process forces but not for the simulation of process instability, e.g. regenerative chatter. The representation of machine and workpiece properties as well as those of the manufacturing process by suitably coupling different simulation environments forms the basis of coupled simulation. Generally, finite element models and flexible multi-body models are suitable for representing the structural–mechanical properties of a machine and a workpiece. A comparative survey of coupled systems is provided in [194] by To¨nshoff et al., who proposed an approach for elastic-kinematic modelling of the stiffness of a machine tool structure on the basis of a multi-body simulation as opposed to a common FEA approach. In order to represent a machining process, analytical models are suitable. So too are finite element models (with some limitations to the simulation possibilities). In [25], Berkemer proposed that a simplified analytical process force model should be coupled with a finite element model of the machine, as presented in Fig. 10 (bottom left). The displacements between workpiece and tool are fed into the force model, where the force components are calculated. These force components influence the machine structure. The process model is integrated as a first order delay component. Here, a precise description of the cutting process and an evaluation of the process stability is hard to achieve. Fig. 11. Analytical simulation of dynamic stability in turning [156]. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 593

Fig. 13. Static process machine interaction [64].

of the model at hand, Denkena et al. were able to study different Fig. 12. Simulation of dynamic stability in boring operations [10]. control strategies as well as simulate process forces and energy consumption. Another topic addressed by the scientists of the 3.4.2. Drilling University of Hannover was the issue of milling of thin-walled A fundamental review of modelling boring and drilling workpieces [64]. The study revealed the correlation between the processes was provided by Altintas and Weck [10]. Different process forces and the induced deformation of the workpiece. The modelling approaches are highlighted in this keynote paper. In proposed model includes the feedback on workpiece deflection addition, it also details the challenges arising from the process into the process simulation (Fig. 13). The same problem was properties, e.g. nonlinear dynamics of boring operations and the studied by Altintas et al. [16] and Corduan et al. [57]. Altintas dependency of cutting forces acting on a drill from its vibrations in proposed a model considering the dynamical behaviour of a all directions (Fig. 12). In [52], the above-mentioned theory of Ozlu flexible thin-wall workpiece and a rigid tool for prediction of a et al. for turning [156,157] was expanded upon to include boring three-dimensional workpiece surface finish form. Corduan et al. processes. In [26], Biermann et al. present a method of simulation proposed a simulation model for predicting the workpiece profile, for a deep-hole drilling process, which enables the calculation of including data on the macro and micro profile. In [87], Gonzalo stability charts for this operation. The results of this research are et al. describe another approach for simulating thin-walled used in [27], which deals with the development of a controlling machining. In this analysis, a mechanistic model of the milling system for chatter suppression, in particular spiralling in deep- process was coupled with a compliant model of the workpiece, hole drilling. The above mentioned reports are based on some obtained from an FEM-model. The authors pointed to the high level earlier study on related problems carried out in [205]. Some further of consistency of the simulation results for stable processes, and research on this topic is presented in contributions of Roukema and identified the need to consider process damping for achieving Altintas. They modelled the mechanics, dynamical behaviour and improved prediction of chatter. chatter stability of drilling operations [164,165]. Insperger et al. [114] contributed to the understanding and Jrad et al. [116] studied a drilling process with respect to cutting modelling of run-out phenomenon for milling operations. The run- forces. The complex geometry of the drill cutting edge was out effect is observed when the cutting forces acting on individual modelled. The elementary forces were calculated using a thermo- cutting teeth are different. Due to this, the main excitation mechanical model for oblique cutting from Moufki et al. [148] to frequency lies between tooth passing frequency and spindle achieve an elementary partition of the cutting edge. After final rotation frequency. The authors modelled the stability of a 2DOF calculation of the sum, a conclusion about process forces was system with run-out, and concluded that the stability boundaries drawn. remain unchanged, while the chatter frequencies are qualitatively An analysis of tapping operations is carried out in the article by affected. A similar task was worked on by Szalai et al. [188], who Lee [137]. A model for the tapping torque is provided under analysed an unstable case due to period-two vibrations. consideration of friction. Ahn et al. [6] employed this knowledge Altintas and Budak addressed the analytical modelling of for analysing synchronisation errors in ultra-high-speed tapping. milling processes [12,48,49] (Fig. 14). The authors deal with an To avoid excessive torques on the tap, some recommendations on analytical calculation of the milling force, identification of work- tolerances for synchronisation errors were elaborated upon results piece and tool deflections and their use in the milling process of this analysis. simulation. They solved the problem of varying dynamics in milling by means of Fourier series expansion of periodic terms and 3.4.3. Milling and sawing Floquet’s theorem. Possible implementation of the theory for Advances in the modelling of milling over the past decades are modelling other processes, such as milling with variable pitch detailed in the extensive review of Altintas and Weck in [10]. cutters and five-axis milling, are discussed in [12,49]. Modelling of Recently, a vast contribution to this topic was made by many the end-milling process is carried out in [155,195]. The approach of researchers relating to various approaches. The latest state-of-the- Tunc et al. [195] employs the force model of Ozturk et al. [154] for art is presented in the following papers. Altintas and Merdol [15] simulated the complete part machin- ing in virtual environment by considering the frequency response function on tool center point as well as mechanics and dynamics of milling process for the calculation of process forces. Fortunato et al. [77] contributed to the simulation of the machining process. He compared analytical and FEM approaches for calculating cutting forces and identified their pros and cons. Denkena et al. modelled the stability of the milling system with adaptronic elements [63]. The authors developed a parametric model of the spindle unit, taking into account the influence of actuators on the dynamic behaviour of the system. Together with a machining process model, the developed simulation system allowed a prediction of stability charts to be made. With the aid Fig. 14. Stability simulation in milling [12]. 594 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

Fig. 15. Stability simulation of five-axis milling [185]. Fig. 17. Co-simulation of machine tool and processes [33]. simulative identification of optimum cutting parameters, e.g. and a cutting process [33]. They argued in favour of better quality spatial cutter positioning or cutting strategy. Ozturk et al. [155] predictions relating to process forces and stability boundaries carried out a stability analysis of the five-axis milling process with (Fig. 17). Later on, Brecher et al. [36] presented a method for the ball end mills. He formulated geometrical interdependencies and coupled simulation of a flexible multi-body machine tool structure coupled them with the force calculation algorithm in order to with a three-dimensional FEA-based turning model. The authors derive stability charts. stated that the FE calculation of process forces without further The issue of process stability and quality of the machined optimisation is very time intensive. A simplified model on the basis surface was addressed by Weinert and Surmann [184,207].In of approximated characteristic diagrams was thus used for the [184], a simulation model capable of precise machining simulation, coupled simulation. This approach allowed the surface roughness i.e. calculation of an arbitrary chip thickness at a random time, of the machined workpiece to be determined. along with a dynamics-enabled cutting tool is presented. The In [37] three different approaches were used to carry out a simulation system predicts the vibration behaviour of the cutting coupled simulation of machine and process. The first one deals tool along a path programmed in an NC-program. Since the with the FE-based process coupled with a substitute model of a dynamics of the tool is taken into account, the chatter prediction machine and workpiece. This coupled system is also referred to in a function is achieved as well. An extension to this simulation separate article by Schermann et al. [174] (Fig. 18). The second system to include a photorealistic workpiece surface generation is approach employed an FE model of a machine and the cutting provided in [185,207]. The surface representation allows to process. The third one incorporated a flexible multi-body model of measure surface roughness and surface location error (Fig. 15). a machine structure and an analytical model of the process. The This approach was further elaborated by Enk and Surmann in results obtained from these approaches were compared, thereby [72,186] for processes with changing tool engagement conditions. revealing the limitations and providing suggestions for further The experimental set-up which is described enables the radial improvement. depth of immersion to be changed, resulting in a variation of the Ho¨vel [110] contributed to research in cutting processes with a tool vibration pattern. The model is capable of both machined defined cutting edge. She carried out a finite element simulation of surface generation as well as the prediction of stability charts for the cutting process and coupled it with the modelled elastic such non-stationary processes. structure of a lathe. As a result of this, a more accurate calculation A thorough analysis of sawing processes may be found in [217]. of the cutting forces and more precise chip formation could be A dynamic model of the process includes not only a chatter effect modelled. but also the influence of torsional vibration in sawing (Fig. 16). In Britz and Ulbrich [43] carried out a coupled simulation of a lathe addition, a concept was presented for adaptive control of the depth structure and a turning process. Both rigid and flexible multi-body of cut for stabilising the process. models were used to represent the machine tool structure. A face- milling process was simulated and the process forces were 3.5. Co-simulation calculated by means of the model. In [32], the modelling of a turning process coupled with a machine structure is described. An overview of simulation approaches was presented in Section Brandt et al. developed a coupled model to simulate an unbalanced 3.3. The coupled simulation was defined as a relatively new spindle and its influence on the workpiece surface quality. approach, permitting simultaneous usage of two different simula- Za¨h and Schwarz [218] presented an approach for using virtual tion environments with data exchange by means of a suitable machine tool models for design tasks. They described a method for interface. This section deals with the latest developments in identifying the optimum characteristics of the structural compo- coupled simulation. nents and controls as well as for analysing the influence of the Brecher and Witt presented an approach for simulating a machining process, including interactions between a machine tool

Fig. 16. Regenerative torsional instability in sawing [217]. Fig. 18. Coupled model, forces and quasi-static displacements in turning [174]. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 595

Fig. 19. Dynamic co-simulation of the machine tool and processes [180]. Fig. 21. Co-simulation of spindle systems and HSC processes [33]. machining process. Mense and Uhlmann [142] proposed an 3.6. Spindle-speed effects innovative use of the coupled simulation. They drew conclusions about necessary design changes, e.g. damping and mass distribu- The dynamic behaviour of milling machines is influenced to a tion, for improving machining stability on the basis of calculated great extent by the properties of the spindle-bearing system. This stability charts. is valid especially for HPC milling operations. Brecher et al. [33] The connection of a coupled simulation system with a PC-based presented a study of the influence of spindle rotation on the NC system was achieved by Hamm et al. [100].Za¨h and Siedl dynamic behaviour of the system. [219,220] were confronted with the challenge of simulating The authors developed a simulation system allowing the crucial considerable machine axes movement. The proposed solution elements of a spindle unit, i.e. spindle shaft, bearings and tool employs coupled multi-body simulation that takes into account a interface, to be modelled precisely (Fig. 21). A non-linear flexible model of machine tool components together with feed dependency of the bearing stiffness on the spindle speed was drive controls. A similar approach is described in [146] by Mo¨hring outlined. Dynamic properties dependent on spindle rotation et al. Schwarz [180] continued investigations in this area and permitted an increase in the accuracy of the calculated stability published a study of the interactions during a turning process with chart by means of the coupled simulation. a lathe structure. He employed the multi-body simulation under A similar study was carried out by Abele and Fiedler [1], who consideration of the feed drive controls. Furthermore, some pointed out the discrepancies in the stability chart calculated improvements on the machining process side were proposed in without consideration of the real behaviour of the spindle-bearing order to consider all the relevant interdependencies in the model system (Fig. 22). (Fig. 19). Altintas and Cao developed a dynamic model of spindle that In [75], Fleischer et al. identified the importance of an considers speed and preload dependent stiffness of angular contact appropriate and accurate machining process model for coupled bearings. The effect of gyroscopic and centrifugal forces on the simulation and discussed several parameters that influence the stiffness and damping matrices are considered in the Timoshenko- accuracy of the process model. based nonlinear finite element model of the complete spindle Abele et al. [2] presented a new approach and discussed some system. The authors coupled the spindle design, analysis and practical issues on performing milling operations using an milling process dynamics in a virtual environment to achieve an industrial robot. Abele et al. [3] considers the static behaviour of optimal spindle construction [13,55]. aroboticstructureand[4] presents a method for the analytical identification of the stiffness of the robot structure in the entire 3.7. Tool wear and process damping working space. A simulation system that includes a flexible multi-body model of the robot structure and a model of the Tool wear is often claimed to be the reason for some milling process is presented in [5].Thedevelopedmodel discrepancies in the modelled and real characteristics of machin- permitted an agreeable prediction of tool displacement due to ing processes, e.g. process forces and damping, since this non- process load in the settled boundary conditions of experiment linear effect requires non-trivial modelling approaches. A number (Fig. 20). of recent scientific articles propose different methods for model- A peculiar approach that considers thermal effects in a co- ling tool wear and process damping. simulation system was presented in [68]. Two modelling The research by Budak and Kayhan [51] deals with a practical environments for machine and process were employed for the identification of the influence of vibratory cutting conditions on coupled simulation of the Charpy impact test. The temperature- tool life. The results indicated significant reduction of tool life due dependent interactions in the system were described by means of to chatter (Fig. 23). Elbestawi et al. [70] modelled an interference analytical models. between the tool flank and the wavy surface generated. The

Fig. 20. Milling with industrial robots—co-simulation of robot and process [5]. Fig. 22. Stability simulation of HSC processes [1]. 596 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

Fig. 23. Chatter effects on tool life [51]. resulting damping due to the tool flank wear was modelled and an increase in the stability boundaries was observed. Za¨h and Schwarz [222] presented an innovative force model which considers dynamic material behaviour, nonlinear friction ratios as well as dynamic tool wear (Fig. 24). A further approach is presented by Altintas et al. [14]. The authors considered the regenerative vibrations x(t), slope (dx/ dt  1/V) and curvature (d2x/dt2  1/V2) terms of the inner waves which effect the process damping, and noted an increase in chatter stability with progressive tool wear (Fig. 25). The implementation of the new force model allowed a more accurate calculation of Fig. 25. Slope and surface curvature dependency of process damping [14]. stability boundaries for low-speed machining. Filice et al. [74] studied different friction modelling approaches and compared the results. The authors argued in favour of The regenerative effect is of special interest for this paper as it including thermal influences in the force model validation. occurs due to the process–machine interaction. The analysis of the grinding process always has to consider 4. Developments describing undefined cutting edge the process and machine behaviour. The process–machine phenomena interaction studied in different papers may be summarised in a meta-model that has been described in a similar form by 4.1. Analysis of interaction phenomena Younis [214],Inasaki[111], Schiefer [173],Klotz[130],Folkerts [76] and Schu¨ tte [179]. As a high-precision machining process, grinding determines the Fig. 26 represents the closed-loop description by Schiefer [173]. surface roughness, the shape and the dimensional accuracy of In the upper part, the dynamic system compliance is described. It workpieces, and directly influences the quality of the finished consists of the dynamic machine behaviour [102], the contact parts. Due to the fact that grinding processes are generally placed compliance [131,76] as well as the grinding wheel and workpiece at the end of the whole process chain, grinding inaccuracy often behaviour [66,160]. The calculation of the process models, such as results in rejects and high costs. On the one hand, grinding material removal, wheel wear, workpiece surface and grinding irregularities occur as burning, grinding commas, hairline cracks forces, is shown in the lower part of Fig. 26. In macroscopic model on the workpiece surface or geometrical deviations. On the other approaches, those calculations are usually carried out separately, hand, the causes of these grinding irregularities can include whereas in microscopic model approaches, the calculation of some dynamic instabilities in the machine–grinding wheel–workpiece physical effects may be combined, for example material removal system, such as chatter vibrations or dynamic deflections [101]. and surface generation with single-grain models. In the case of regenerative chatter, the vibration is related to the The system shown can become unstable and chatter can occur surface waviness that was generated earlier during the process due to the re-entering workpiece and the grinding-wheel surface itself, re-entering the grinding area. A special characteristic of the in the contact kinematics [113]. Alternatively, an abrupt change in grinding process in comparison to the other metal-cutting material removal in speed-stroke grinding leads to a dynamic processes described earlier is that not only the workpiece but deflection in the grinding zone and thus to marks on the workpiece also the grinding wheel can be the bearer of the regenerative effect. surface [129]. The regenerative effect on the workpiece side is characterised by a rapidly increasing vibration amplitude, which can be seen and measured on the workpiece. In contrast to this, the vibrations caused by the effect on the wheel side increase much more slowly.

Fig. 24. Consideration of tool wear [222]. Fig. 26. Process—machine interaction in grinding [173]. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 597

more complex analytical formula in simulation to analyse the measured compliance-response (Fig. 27, lower right corner). In the selective approach, the parts of the machine that are modelled in great detail are usually the grinding wheel and the workpiece, sometimes the centre lathe and, for centerless grinding, the regulating wheel and the support blade. Herzenstiel et al. presented an FE model of the grinding wheel [106]. Jansen discretised the grinding wheel and its spindle with finite elements and concentrated on the compliance of the grinding machine structure in elastic bearings [115]. On the workpiece side, FE simulations have been carried out in cases where the compliance of the workpiece cannot be neglected. Denkena et al. built an FEM model of a drill to simulate workpiece deflection during a tool grinding process, and compared the simulated deflections with the Fig. 27. Measurement of the dynamic behaviour of machine tool and grinding wheel measured ones [60]. Schu¨ tte concentrated on dynamic deflection [38,101]. in particular. He calculated in FEM and measured natural oscillation forms and frequencies of both the grinding wheel 4.2. Identification of model parameters and the workpiece [179].

The accumulated compliance of the machine tool and the 4.2.2. Process process models will be described separately in the following Due to the large number of abrasive grains with unknown time- section. dependent geometry and distribution, grinding is a complex material-removal operation. Different approaches for modelling 4.2.1. Machine tool the grinding process were presented in the Annals of the CIRP [46]. Machine tools react with dynamic deformation to the forces The models are generally used to predict grinding forces, applied to them by the process. Different approaches have temperatures, grinding energies, surface integrity, etc., depending therefore been developed to measure, model and thus predict on the purpose [199]. Within the kinematic-geometrical approach, those deformations. a distinction can be made between microscopic and macroscopic The measurement can either be carried out during the process models [28,46]. On the one hand, the complex microscopic models [209] or offline, tracing compliance-response functions or, if typically allow a detailed view into process behaviour. On the other necessary, conducting a detailed modal analysis [107]. Force hand, the macroscopic models are used for simplified and rapid induction and measurement in grinding machines can be simulations of the grinding process. complicated because of the restricted accessibility, form and Microscopic approaches consider different complex or simpli- contact conditions at the grinding wheel and the regulating wheel fied 2D and 3D shapes of single grains and their statistical or in the case of centreless grinding. In spite of this, the conventional measured distribution on the grinding wheel [112,120,191,227]. compliance-response measurement procedure and the modal Much of the research relates to the extensive classification for analysis for grinding machines as shown in Fig. 27 on the left measured grain shapes as presented in [18,213]. Early 2D side are common knowledge. However, the specifics of grinding approaches for micro simulation were made in the 1960s and demand more adequate measurements. The motion of the wheels 1970s by Yoshikawa [215,216], Kassen [118] and Law [136]. They is usually measured at the spindle or at an unloaded part of the concentrated on the prediction of surface quality by tracing single- wheel. The contact deflection and the wheel deformation are often grain passes through the workpiece. 3D approaches emerged with neglected. Hannig developed a tool for displacement measurement the increasing power of computer systems [46]. These models take in the force-path that combines all sensors and actors in one into account machine, material and process parameters, and allow device. Using an adapter in the form of a workpiece, he was able to the calculation of single grain forces, stress distributions, chip measure the system deflection, taking all the effects into account, thickness, as well as the number of static and kinematic cutting as shown in the upper left section of Fig. 27 [101]. Contact edges. More generally, they assisted in understanding the grinding deflections have also been measured in grinding tests carried out process in a greater detail. by Ko¨nig et al. [131] and in measurement comparisons in the There exist numerous kinematic-geometrical models, Refs. loaded and unloaded part of a wheel by Folkerts [76]. Folkerts [28,46,168] present detailed summaries. Most of the mentioned demonstrated that contact deflections are nearly constant at all models assume ideal total material removal by solid grains. On one frequencies. Hannig revealed that contact compliance only affects hand, the loads and stresses can be calculated in FEM [60] for every the real part of the compliancy-response function, whereas the single grain by using material models [65]. On the other hand, the imaginary part does not change. forces that are generated can be calculated using modified Kienzle Different approaches for the modelling of machine tools are equations together with the knowledge of the accumulated provided in [11]. Simplifications of the machine model for grinding machined material and the chip cross-section [28,121,122].A greatly depend on the grinding process under consideration. The 2D single-grain scratching model in FEM was developed by Klocke main modelling methods for grinding machines are finite element, et al. [127] (Fig. 31, upper left corner) and Brinksmeier et al. [45]. multi-body simulation, boundary element and analytical methods This created fundamental insights into the relationship between [28]. Generally speaking, a distinction is made between full cutting speed, chip thickness and cutting efficiency that correlate machine models and a selective approach, where only small parts well to results obtained from experiments. Denkena et al. [65] are of the machine are modelled in greater detail. currently carrying out a scratching simulation for integration into a Hoffmann used a flexible multi-body simulation to develop a process–machine interaction model that is described in Section full machine model for a speed-stroke grinding machine, and 4.5. 3D FE scratch simulations have been presented in [128] integrated a drive control model in his simulation [109]. (Fig. 31, lower left corner). Approaches using finite element methods have been described Macroscopic approaches describe the geometry of the tool- by Denkena et al. [65] and Herzenstiel et al. [106], for example. In workpiece penetration zone without detailed specifications of the past, simple analytical models were often used to approximate the grinding wheel topography or modelling single grains. the machine, for example with a single mass oscillator represent- Macroscopic parameters, such as the total material removal rate ing the main resonance. Research by Alldieck [7], Salje and Dietrich [101], are generally used to determinate grinding forces in [169], Hannig [102], Weck et al. [201] and Michels [144] uses a combination with modified Kienzle equations (Fig. 28). In this 598 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

Fig. 28. Identification and modelling of the grinding process behaviour [101].

case, extensive empirical data is necessary to calculate grinding forces [28,209].

Fig. 30. Kinematic 3D simulation of surface generation, taking into account the 4.3. Overview of simulation approaches plastic and elastic behaviour of the workpiece [168].

The machine model and the process model can be combined in two different ways for grinding to generate a complete interactive micro- and macro-geometry of the grinding wheel and calculates simulation approach, as shown in Fig. 29. the forces of every single grain. The sum thereof represents the In the model integration technique, both parts are modelled in total cutting force over time. This force serves as an input value for the same simulation environment. In this type of simulation, a the machine model, which calculates the displacements of the simplified process or machine model is usually integrated into an different machine system components over time, including the existing enhanced model of its counterpart. macro-geometrical deflection of the grinding wheel as presented If both models run simultaneously in different simulation in Fig. 31 (right). Based on the new contact conditions, the process environments and communicate with each other in synchronised model recalculates the grinding forces. The loop is repeated in each cycles, the technique is called co-simulation. In this case, complex time step until forces and displacements converge [106]. machine and complex process models that might have been Numerous 2D models have been developed using model developed independently may be combined. integration over the past decade to simulate the chatter phenomena in cylindrical plunge grinding. The models are usually 4.4. Model integration based on the chatter loop described in Section 4.1, focusing on different parts of the whole model. A process–machine interaction using a microscopic approach Schu¨ tte developed the 2D simulation model represented in was carried out by Sakakura et al., who investigated the interaction Fig. 32 [179]. The goal of this work was to analyse nonlinear between the grinding grains and the workpiece surface [168] oscillation in external cylindrical grinding. He thus created a model (Fig. 30). in a single simulation environment that integrated the simulation Unlike traditional models where the surface evaporates out of of the grinding contact and system dynamics. He carried out the way of a rigid grain [191,227], Sakakura et al. consider both the extensive dynamic FEM and experimental studies of the workpiece elastic deflection of the grains, which can be measured, and elastic and the grinding wheel. The contact and abrasion simulation is a and plastic deformation of the workpiece surface before the actual conventional macroscopic approach with a process model from cut is made. Through the simulated deformation and the pile up regression analysis of grinding tests. The roughness of the grinding zone, the resulting workpiece surface is much closer to the real wheel contour is generated via random radius variation across the measured one. perimeter. However, abrasive and possibly irregular wear of the Herzenstiel et al. [106] present a concept for a comprehensive grinding wheel is not considered. The abrasion of the workpiece is grinding model that combines machine and process models calculated from the material evaporation in the penetration zone. (Fig. 31 right). The process model is based on the kinematic- The calculated forces from the penetration zone provide the input geometrical simulation by Zitt [227]. It takes into account the values for the dynamic calculation of workpiece and machine, leading to the dynamic movement of machine parts. From the new dynamic position, the new contact zone is recalculated which, in turn, provides new grinding forces.

Fig. 29. Simulation approaches for process machine interaction. According to [97]. Fig. 31. Small and large scale of FEA in grinding [106,128]. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 599

Fig. 32. Chatter simulation and suppression in external grinding [179]. Fig. 34. Co-simulation of spindle and process for NC-shape grinding [115,209]. Alldieck uses an elaborated approach for the simulation of plunge grinding in the time domain [7]. The 2D simulation tool an analytical solution for the occurrence of geometrical lobes. The takes into account detailed parameters on the process part and transformation back into the time domain enhances the simulation includes static and dynamic compliance on the machine part. of real workpiece surface development. Alldieck simulates the penetration zone with a macroscopic model Hannig transfers Alldieck’s [7] simulation algorithm to centre- that includes the material removal rate, and calculates abrasion, less grinding with its much more complex geometry and grinding wheel wear as well as the response force of the lathe interaction, as presented in Fig. 33 [101,102]. He calculates the centre. These forces are applied in the machine model that current workpiece dynamics and the position of the workpiece at calculates the actual dynamic compliance for the three machine the regulating wheel, as well as on the support blade in the parts via fitted compliance-response functions. Weck and Hennes complex grinding gap geometry. His advanced surface penetration [201] developed an advanced simulation model of the traverse algorithm takes into account the microscopic compliance of the grinding process based on Alldieck’s model. roughness peaks, while allowing a loss of contact in waviness Centreless grinding occupies a special position among the valleys of the workpiece surface. grinding processes for rotationally symmetric workpieces due to its highly complex geometry. As the workpiece is not centered by a 4.5. Co-simulation lathe centre but is supported at its outer surface, process instabilities are possible even in absence of machine dynamics. NC shape grinding has been researched by Jansen, Weinert et al. As the very first approach, Dall [59] developed a mathematical in a co-simulation [115,208,209]. Some representative results are description of the rounding process. Rowe [166] implemented the presented in Fig. 34. The purpose of this research is the simulation first geometric computer simulations. Later, simulation advances of free-form surface grinding with toroid grinding wheels. The where achieved by Friedrich [83]. Gurney [88] was the first to main challenge in this process is the complex and varying contact define the term ‘geometrical instability’. Furukawa et al. [84] area between the grinding wheel and workpiece. Hence, the developed an integrative analytic approach based on Gurney that is machine structure undergoes varying loads from the process, still used and has been improved by Miyashita [145], Zhou leading to significant shape errors, as described by Okuyama et al. [225,226], Epureanu [69], Lizarralde [138] and Gallego [85,86]. [153]. Gurney [88], Reeka [161] as well as Harrison and Pearce [103] Jansen’s simulation consists of three distinguishable parts in developed the today most commonly known geometric stability different simulation environments. The geometric-kinematic simu- maps for centreless grinding machines. lation discretises the workpiece and the kinematics of the grinding In more recent developments, Guo et al. [99] and Kim [123] machine. It is also able to predict the grinding forces in an represented the workpiece contour in same manner as Schu¨ tte approximate way. The finite element simulation describes the [179]. They used optimum round grinding and regulating wheel response of the grinding machine to the contact between the geometries as well as optimum flat support blade geometries with grinding wheel and the workpiece, taking dynamic friction into single point contact of the workpiece to the tools. Lizarralde [138] account. The removal predictor uses the contact forces to and Gallego [85] represent an analytical approach to centreless approximately calculate the real infeed. The global outcome is the grinding, incorporating contact compliance into their calculations. real workpiece form, which deviates from the programmed one. Transforming the equation into the frequency domain, they derive Denkena et al. presents a combined simulation approach for tool grinding in [65], as presented in Fig. 35. The purpose is to simulate the grinding process and the resulting shape and surface quality of drills and end mills. The grinding process under analysis

Fig. 35. Modelling and co-simulation of the process–machine interaction in tool Fig. 33. Centreless grinding: simulation of process–machine interaction [101,102]. grinding [65]. 600 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 is characterized by complex three-dimensional engagement et al. [135], Franzke and Hirt [80], Großmann [96], Meier [141], conditions, high material removal rates, yielding to greatly varying Schapp [172] and Wiemer [211]. static and dynamic workpiece properties, and a complex interac- tion of process, grinding wheel, workpiece and machine. Denkena 5.2. Identification of model parameters et al. take an integrated approach that comprises multiscale modelling and experimental aspects. A macroscopic material 5.2.1. Machine tool removal model based on surface/surface intersection has been The accuracy of a forming process is defined by the deflection developed to calculate the current workpiece geometry [66]. and tilting behaviour of the machine and the tool system under the A microscopic material removal model has been implemented process load. To characterise the accuracy of the machine, the axial as an FEM single grain scratch to predict grinding forces in a later and tilting stiffness is used. For presses, the standardised state. Analysis of static and dynamic grinding wheel and workpiece measurement of these machine parameters is carried out at the compliance has been carried out using FEM. Empirical data from bottom dead centre position of the ram and with a static load tool grinding experiments has also been collected [60]. according e.g. to DIN 55189 [67], VDI 3193 [196] and VDI 3194 Klocke et al. likewise use an elaborated approach to simulate [197]. A continuative approach to identify the press stiffness as a speed stroke grinding [129]. Combining the works of Hoffmann on 6 Â 6 flexibility matrix is shown in [17,56]. Furthermore, in [22],an flexible multi-body simulation with moving machine parts approach for the dynamic measurement of axial and tilting [108,109] and Zeppenfeld’s research on speed-stroke grinding stiffness of press machines is given. [223,224], they generate an integrative tool that is able to simulate Knowledge of the press parameters for stiffness and clearance is both the grinding process and the dynamic and static machine not sufficient to draw direct conclusions regarding machine behaviour. In addition, the machine model integrates virtual drive behaviour during the forming process. This is because, in most control loops as mentioned in Section 4.2. cases, the loads during the process are unknown. Measurements during the forming process are therefore necessary. Freiherr 5. Developments describing forming phenomena [81,82] developed an optical system with two laser light sources and two gauge heads for measuring ram deflection and tilting of a The numerical computation of forming processes, based on the press. The system is mounted on a press table and ram within the finite element analysis (FEA), has been established as an efficient working room of the machine which could be difficult for tool within process development. By using simulation, important measurement during warm forming processes. Schapp used an aspects specific to forming can be analysed prior to initial forming optical laser measurement system (Lasertracker) for the measure- tests and the dies can be optimised accordingly [133]. This leads to ment of press behaviour during a forging process [34,170,172]. The a decrease in manufacturing and development time as well as to an analyses reveal that this kind of approach can be used to measure increase in quality and productivity [152]. the machine behaviour under process load with only negligible The benefit of the simulation for the user greatly depends on the interruption to the production process. The measurement can be quality of the results. Only those computation results are useful used for presses which have a rigid connection into the ground. which provide a highly precise representation of the real situation Wiemer [211] gives a comprehensive overview of different [149]. While this is already the case for material flow computation, approaches for modelling and simulating mechanical press the dimensions of formed workpiece still cannot be determined in machines. In recent research activities from Blau et al. [30], a satisfactory manner. The main reason for the insufficient Großmann et al. [90–92], Krimm [134], Schapp [172], Wiemer et al. accuracy of the simulation results is the non-realistic representa- [211] particular attention has been paid to modelling the nonlinear tion of the machine behaviour within the simulation of the forming elastic load–deflection behaviour of the ram guiding system, as this process [94,172]. has a crucial effect on the machine behaviour under load. Schapp [40,172] compared the simulation accuracy of machine 5.1. Analysis of interaction phenomena behaviour under process load by calculating with different types of press models and carrying out measurements during real forging The high flow stress of the workpiece material causes extreme tests (Fig. 37). The press models, which allow nonlinear elastic loads on the machine and tool system, resulting in considerable computation of machine behaviour, demonstrate a high level of deflections of these components. This, in turn, influences the simulation accuracy compared to the forging tests. Furthermore, workpiece dimensions and accuracy [31]. Thus there are interac- the work reveals that an analytical, nonlinear elastic machine tions between the process, the machine and the tool system model programmed in a high-level-language is sufficient for the (Fig. 36). These interactions complicate the optimisation of tool simulation of the machine behaviour of forging presses. and process design that should lead to high workpiece accuracy. Increasing workpiece accuracy by taking into account the 5.2.2. Process interactions of machine and process when simulating forming In metal forming, process modelling and simulation is used to processes is thus an important objective in recent research predict material flow, stress and temperature distributions, activities from Behrens [24], Brecher [40], Engel and Geiger stresses and forces exerted on tools, and potential sources of defects and failures. It is even possible to predict product

Fig. 37. Coupled simulation of forging process and nonlinear elastic machine Fig. 36. Interaction of the press and the forming process [71]. models [40]. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 601 microstructure and properties as well as elastic recovery and residual stresses [8]. Approaches and possibilities for the numerical simulation of forming processes are presented in [8,21,105,162,163,172,210]. The accuracy of FE process simulation depends on reliable input data, namely on CAD data relating to the die geometry, the speed and force characteristics of the press used for forming, the flow stress of the deforming material as a function of strain, the strain rate and temperature in the range relevant to the process, as well as friction characteristics at the interface between the deforming material and the die. A broad overview of modelling and testing approaches and techniques for predicting material response with the latest developments in research laboratories and industrial applications is provided in [9,19,150]. Fig. 39. Offline coupling of a deep-drawing process and machine simulation [23,24].

5.3. Overview of simulation approaches cess. A phenomenological approach is used to generate the Comprehensive modelling of the forming process demands the machine model, which is based on the results of experimental coupling of subsystems, as the machine, tool and workpiece all measurements. The machine simulation takes into account the influence the forming process. Principle concepts coupling the FE nonlinear stiffness characteristic of the connecting rod, ram guides workpiece model and machine model are presented in [98]. Fig. 38 and machine frame, as well as the deflection of the bolster plate gives an overview of coupling variants which are classified and the ram collective. The clearances in the bearings and ram according to their method of integration. guides are likewise considered by the measuring data selected as In case of offline coupling, process force progressions of the input values. In order to consider the mutual influence between the entire forming process are computed with the workpiece model. process simulation and the machine simulation, an iterative With these process force progressions, the machine behaviour is combined simulation was developed. The cycle comprises four computed separately in the machine simulation. So one simulation steps that are carried out one by one (Fig. 39). typically uses the complete results from an entire run of the other Meier et al. [141] presented a robot-based forming process in simulation. The cycle will be repeated until convergence of the which the path design of the robot was computed using offline simulations is reached. coupling of FEA and multi-body simulation (MBS). Roboforming is In the model integration approach, the workpiece model is a method in incremental sheet-metal forming for a low number of typically extended by a simplified machine model within the same pieces. The principle is based on flexible shaping by means of two simulation environment (usually FEA). The integrated model industrial robots. The compliances of the machine structures allows direct interaction between the process load and tool involved and the springback effects of the workpiece are the main position as a result of the machine behaviour. influencing factors on dimensional accuracy in incremental sheet- In co-simulation, both simulations run simultaneously in metal forming. This is evident in roboforming, where the robots’ different simulation environments and communicate to each stiffness is low compared to a conventional machine tool. The other in synchronised cycles. In this case, detailed machine models, driven path deviates significantly from the planned path, and the e.g. from multi-body simulation, can be coupled with FE workpiece shapes produced are thus of insufficient quality. To predict these models. The synchronisation and exchange of simulation data is deviations and to compensate the tool path, a simulation model carried out by a special coupling tool. focusing on the interaction between the forming process and the In the following the results of recent research activities are robot structure was developed. By coupling both models itera- outlined with respect to the interactions between machine and tively, an adjusted TCP path is generated that compensates the process in the simulation of forming processes using the different path deviations. To validate the coupled simulation model, a simulation approaches. measurement using an external optical coordinate measuring machine was carried out. The computed tool-tip positions were 5.4. Offline coupling of process and machine simulations validated by comparing them with the measured positions. The results demonstrate a high level of consistency. In [23,24] Behrens et al. presented an approach for the optimised simulation of metal forming processes by means of 5.5. Model integration the FE method that takes into account machine properties. The approach is an offline coupling of FE process simulation and a An example of model integration when modelling the process– machine simulation in a higher programming language. It is tool-machine interactions in cold forging is presented in [71,135] exemplified by a three-stage multi-engaged deep-drawing pro- by Engel, Geiger, Kroiß and Vo¨lkl. The process under analysis is an axially symmetric forward extrusion process on a stroke-con- trolled press. Cold-forged parts are produced with stroke- controlled presses in many cases. The deflection of these mechanical presses caused by high loading during the forging process directly influences the actual punch stroke. However, the deflection does not only affect the press itself but also the tool system up to the punch. In addition, the prestressed die is also deformed elastically during the forging process. The deflection of these components, which leads to a change in the punch stroke, influences the workpiece dimensions. This is used to determine the stiffness of the press indirectly using the evolution of the workpiece length depending on the actual punch stroke (Fig. 40). For the stiffness calculation, experiments and an FE simulation of the example process were Fig. 38. Simulation approaches for process–machine interaction according to [97]. applied. However, the behaviour of the whole press is not linear 602 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

Fig. 40. Consideration of the resulting press stiffness in the FE process simulation Fig. 42. Simulation of sheet-metal forming process with advanced forming process [135]. model [96,97]. due to initial effects caused by the press drive system. These non- to the implementation of the press behaviour. The stiffnesses of the linear effects at low forming loads are constant and can be die-cushion drive, the guidance, the pressure pin, and the pin modelled by a shift factor in the FE simulation. At high forming guidance are represented by substitutional springs (Fig. 41, right). loads, the deflection of the whole press, including the tool system, The analyses demonstrate that the effect of the blankholder reveals a linear behaviour and can be modelled by a spring deflection on the example drawn part is greater than the influence element. The model consisting of a shift factor and a spring of ram tilting. element with the stiffness of press and tool system is ultimately In [96] the process simulation with the advanced forming integrated into the FE process simulation. Based on this model, an process model is verified with experiments on a single-action optimisation of the influencing parameters and thus the workpiece hydraulic press. During these experiments, the static tilting and accuracy was made. stiffness behaviour of the press were determined by measurement In [93], Großmann et al. presented an approach for model and taken into consideration during the FE forming process model integration that reveals how interactions between the forming with non-linear springs. The elastic properties of the die cushion press, the tool and the sheet-metal forming process can be and forming tool were also considered. The simulation corre- modelled by enhancing conventional FE process models. Sheet- sponds well to the experimental results. Furthermore, the metal forming processes are commonly described by shell experimental results confirm the prediction of wrinkles and cracks elements with simple constitutive equations. The workpiece-die made using a forming limit diagram (Fig. 42). interface is represented by friction and contact law with constant coefficients. Within the concept of an advanced forming process 5.6. Co-simulation model, as described, static effects of the press, such as vertical and horizontal total stiffness and the tilting stiffnesses, are considered. Brecher and Schapp presented in [39,171,172] a method for the For simulation with a rigid ram these parameters are connected as coupled simulation of a forging process with external machine tool concentrated stiffnesses to the centre of gravity of the ram. In a simulation systems and nonlinear elastic press models. The second step the model is enhanced by elastic tool models that approach of co-simulation allows all interactions between the demand elastic embedding in the machine. This implies that the press and the process to be considered in order to improve the press has to be modelled by an elastic ram and an elastic press accuracy of the forging simulation. Fig. 43 describes the method for table. Similar to real press structures, the bearing of the elastic ram incorporating the press behaviour into the forging simulation by in the press is determined by the drive and ram guidance. The enabling data exchange between the process and the machine advanced forming process model is thus extended by distributed simulation. spring elements (Fig. 41, left). This advanced forming process In forging simulations, the entire computation process is model allows the deflection and tilting of the ram and the resulting divided into several steps. When using coupled simulation, the influence on the sheet-metal flow and sheet thickness to be current process load is computed at the end of each step and computed. transferred from the forging simulation to the machine simulation, In [94,95], the advanced forming process model is extended to which then determines the nonlinear elastic relative displacement include elastic die-cushion effects. In reality, the distributed load and tilting of the upper and lower dies. Subsequently, the press on the blankholder surface results from the equilibrium between deflection information is transferred back to the forging simula- the process load, which is variable in time and location, the tion, where the dies are repositioned accordingly. By using this blankholder deflection and deformation. In forming simulations, procedure, the externally computed press behaviour is fully this demands the extension of the model to include the integrated into the computation of the forging process. deformation and deflection of the blankholder. The implementa- The comparison between the simulation results from the tion of the die-cushion model for an elastic blankholder is similar coupled simulation with nonlinear elastic machine models and

Fig. 41. Modelling of press and die cushion in the advanced forming process model [97]. Fig. 43. Co-simulation of the machine and process in forging [172]. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 603

Fig. 45. Modelling of the interaction effects between the roll and the process in flat rolling [79,80].

machine that contains the controlled subsystems of the hydraulic drives. The objective of this analysis is to optimise the hydraulic drive control of the deep-drawing press and to achieve better simulation results with respect to the influence of machine behaviour on the workpiece dimensions.

6. Summary and conclusion

For a wide variety of metal-working processes, the state-of-the- art and the state of ongoing research in process–machine interactions have been presented. The large number of projects Fig. 44. Co-simulation of multi-staged forging processes and nonlinear elastic press demonstrates the strong interest in the related research. models [40]. In cutting and grinding, there is a long tradition of viewing the process and the machine tool as an interacting system. Researchers forging tests reveals a high correlation. The press behaviour of forming processes have started to consider press behaviour over transfers onto the shape and the dimensions of the workpiece in the last few years. In all disciplines, there are more or less four reality and in the coupled simulation. With these more precise important steps in the research of process–machine interaction. computation results of the forging simulation, simulation-based First comes the understanding of the modes of interaction. tool optimisation may be achieved and machine individual tool What are the relevant aspects of behaviour? How can the adjustments can already be done in the design stage of the tools interaction be measured and assessed? Secondly, a concept for [39,172]. Furthermore, the coupled simulation allows the devel- modelling the interaction is needed. Where are the interfaces opment of forging errors caused by the press to be reconstructed. between the process and the machine tool? How can all modes of Brecher et al. [40] presented an extended approach for the interaction be included? Thirdly, abstraction of the models is coupled simulation of multi-engaged, multi-staged forging pro- necessary. What are the relevant interaction phenomena? How can cesses (Fig. 44). In addition to the workpiece-based interaction of existing process and machine models be used for the modelling of the different forging stages in single-engaged, multi-stage these phenomena? Lastly, modelling leads to methods of processes, coupled simulation also takes into account the simulating process–machine interactions, which is generally the machine-based interaction. It is because every single die stage goal of the research projects. Prediction of interaction results contributes to the machine behaviour that a change in one of the through simulations can help to improve machines and processes die stages results in a different process load of the press machine in order to obtain a more efficient production system. and so to retroactive effects on all die stages. Especially these two As in a feedback loop, the simulation results can be compared interactions make the optimisation of multi-engaged multi-stage with observed experimental data. This enables the researcher to processes very demanding. The results show that even such gain a closer understanding of the details of process–machine complex interactions can be simulated correctly, thereby forming interactions, starting the four steps again. the basis for a simulation-aided optimisation of multi-engaged Currently and in future projects, this approach will be forging processes. supplemented with cross-functional research. How can mechan- In cold rolling processes, the strip-flatness and the strip- ical and mathematical methods be used to describe interaction thickness profile are highly influenced by the interaction between phenomena independently of the individual process? What are the the process (strip) and the machine (rolls). These influences common grounds for forming, grinding and cutting experts? The include changes in pressure distribution in the roll gap, roll solution to these questions will be found by intensifying deformation phenomena, and strip tension distribution, among interdisciplinary communication. The CIRP research group ‘‘Pro- other things. Modelling such processes using a single FE model that cess Machine Interaction (PMI)’’ has made the first steps in this takes these influences into account is not only difficult to carry out direction. but it also complicates the convergence criteria. This situation is even worse if the contact situation between elastic bodies (work Acknowledgments rolls and backup rolls) has to be considered. Franzke, Puchhala, Dackweiler and Hirt in [78,79,80] presented a concept that meets The authors would like to thank Stephan Ba¨umler, Alexander the above-mentioned requirements efficiently by separating the Guralnik, Marco Tannert and Yuri Trofimov for their efforts in computation of tool elastic effects from the process simulation compiling the state-of-the-art in the field of process-machine (Fig. 45). interactions for this paper. Helduser and Lohse described an approach for the co- The authors are grateful to the following persons for their simulation of a deep-drawing process and a hydraulic press contributions to the preparation of this paper: Professor Altintas, machine in [104]. Here, the FE simulation of the sheet-metal University of British Columbia, Canada; Professors Biermann and forming process is coupled with the mechanical model of the press Weinert, Technical University Dortmund; Professor Denkena and 604 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

Mr. Deichmu¨ ller, Leibnitz Universita¨t Hannover; Professor [27] Biermann D, Weinert K, Enk D, Hossam M, Raabe N (2008) Controlling Approach for the BTA Deep Hole Drilling Process to Avoid Spiralling. Proceed- Großmann and Dr. Wiemer, Technical University Dresden; Professor ings of the 1st International Conference on PMI, Hannover, Germany, 53–60. Smith, University of North Carolina at Charlotte; Professor Za¨h, [28] Biermann D, Aurich J, Blum H, Brecher C, Carstensen C, Denkena B, Klocke F, Technical University Munich, Germany, Professor Abele, Technical Kro¨ger M, Steinmann P, Weinert K (2008) Modelling and Simulation of PMI in Grinding. Production Engineering 3(1):245–252. University Darmstadt, Germany; Professor Ahn, Pusan National [29] Biermann D, Surmann T, Kehl G (2008) Oszillatormodell fu¨ r Werkzeug- University, Korea; Professor Aurich, Technical University Kaisers- maschinen zur Simulation von Zerspanprozessen. wt Werkstattstechnik online lautern, Germany; Professor Budak, Sabanci University, Turkey; 98:185–190. Professor Engel, University of Erlangen-Nu¨ rnberg, Germany; Pro- [30] Blau P, Neugebauer R, Weiß J (2003) Schwerpunkte der Simulation des dynamischen Verhaltens von Umformmaschinen. Proceedings of 10th Sa¨ch- fessor Fleischer, Karlsruhe Technical University, Germany; Professor sische Fachtagung Umformtechnik, ICAFT Chemnitz, Germany, 261–276. Inasaki, Keio University, Japan; Professor Seliger, Technical Uni- [31] Bogon P (1999) Eine aktuelle Aufgabe fu¨ r die Simulation. Ganzheitliche versity Berlin, Germany; Dr. Zatarain, Tekniker, Spain. We would Betrachtung von Maschine, Werkzeug und Prozess, Blech, Rohre. Profile 9:60–65. also like to thank the industrial companies who provided their [32] Brandt C, Karimi H, Piotrowska I, Niebsch J, Ramlau R, Krause A, Riemer O, support in preparing this paper. Maaß P (2008) PMI Model for Turning Processes. Proceedings of the 1st International Conference on PMI, Hannover, Germany, 239–246. [33] Brecher C, Witt S (2006) Simulation of Machine Process Interaction with References Flexible Multi-Body Simulation. Proceedings of the 9th CIRP International Workshop on Modeling of Machining Operations, Bled, Slovenia, 171–178. [1] Abele E, Fiedler U (2004) Creating Stability Lobe Diagrams during Milling. [34] Brecher C, Schapp L, Paepenmu¨ ller F (2006) Gekoppelte Simulation von Annals of the CIRP 53(1):309–312. Presse und Massivumformprozess—Beru¨ cksichtigung (nicht-) linearen [2] Abele E, Kulok M, Weigold M (2005) Analysis of a Machining Industrial Robot. Maschinenverhaltens in der Umformsimulation. wt Werkstattstechnik online Proceedings of the 10th International Science Conference on Prodiction Engineer- 7(8):526–529. ing, Lumbarda, Croatia, . [35] Brecher C, Esser M, Witt S (2007) Simulation of the Process Stability of HPC- [3] Abele E, Weigold M, Kulok M (2006) Increasing the Accuracy of a Milling Milling Operations under Consideration of the Nonlinear Behaviour of the Industrial Robot. Production Engineering 13(2):221–224. Machine Tool and the Cutting Process. Proceedings of the 10th CIRP Interna- [4] Abele E, Weigold M, Rothenbu¨ cher S (2007) Modeling and Identification of an tional Workshop on Modelling of Machining Operations, Calabria, Italy, 437– Industrial Robot for Machining Applications. Annals of the CIRP 56(1):387– 444. 390. [36] Brecher C, Klocke F, Witt S, Frank P (2007) Methodology for Coupling a FEA- [5] Abele E, Bauer J, Rothenbu¨ cher S, Stelzer M, von Stryk O (2008) Prediction of Based Process model with a Flexible Multi-Body Simulation of a Machine the Tool Displacement by Coupled Models of the Compliant Industrial Robot Tool. Proceedings of the 10th International Workshop on Modelling of Machining and the Milling Process. Proceedings of the 1st International Conference on PMI, Operations, Calabria, Italy, 453–468. Hannover, Germany, 223–231. [37] Brecher C, Witt S, Marsolek J, Steinicke M, Piendl S (2007) Konzepte zur [6] Ahn J, Lee D, Kim S, Kim H, Cho K (2003) Effects of Synchronizing Errors on Kopplung von Zerspanprozess-und Maschinensimulation und deren Cutting Performance in the Ultra-High-Speed Tapping. Annals of the CIRP mo¨gliche Umsetzung, Abschlussbericht des Verbundprojektes Simulation 52(1):53–56. industrieller Bearbeitungsprozesse (SindBap), Tagungsband zum Abschluss- [7] Alldieck J (1994) Simulation des dynamischen Schleifprozessverhaltens, kolloquium, Aachen, pp. 107–120. Dissertation, RWTH Aachen University. [38] Brecher C, Hannig S (2007) Wirtschaftliche Messung und Beurteilung der [8] Altan T, Vazquez V (1996) Numerical Process Simulation for Tool and Process dynamischen Systemnachgiebigkeit von Schleifmaschinen, Jahrbuch Schlei- Design in Bulk Metal Forming. Annals of the CIRP 54(2):599–615. fen, Honen. La¨ppen und Polieren 63:198–211. [9] Altan T, Shirgaokar M, Yadav A (2008) Simulation and Optimization of Metal [39] Brecher C, Schapp L (2007) Simulationsunterstu¨ tzte Optimierung von Mehr- Forming Processes—New Applications and Challenges. Proceedings of the 19th stufenwerkzeugen bei Beru¨ cksichtigung des nicht-linear-elastischen Press- Umformtechnisches Kolloquium Hannover – Umformtechnik – Ein Wirtschaftsz- enverhaltens. ZWF 10:620–625. weig mit Potential, Hannover, Germany, 173–186. [40] Brecher C, Schapp L, Tannert M (2008) Simulation-Aided Optimization of [10] Altintas Y, Weck M (2004) Chatter Stability in Metal Cutting and Grinding. Multi-Stage Dies—Coupled Simulation of Forging Processes with Non-Linear- Annals of the CIRP 53(2):619–642. Elastic Machine Models. Proceedings of 1st International Conference on PMI, [11] Altintas Y, Brecher C, Weck M, Witt S (2005) Virtual Machine Tool. Annals of Hannover, Germany, 167–174. the CIRP 54(2):651–674. [41] Brecher C (2008) Schließen der Simulationskette ‘‘Prozess–Maschine– [12] Altintas Y, Budak E (1995) Analytical Prediction of Stability Lobes in Milling. Steuerung’’. Proceedings of Aachener Werkzeugmaschinen Kolloquium, Aachen, Annals of the CIRP 44(1):357–362. Germany, 276–279. [13] Altintas Y, Cao Y (2005) Virtual Design and Optimization of Machine Tool [42] Brecher C, Esser M (2008) The Consideration of Dynamic Cutting Forces in the Spindles. Annals of the CIRP 54(1):379–382. Stability Simulation of HPC-Milling Processes. Proceedings of the 1st Interna- [14] Altintas Y, Eynian M, Onozuka H (2008) Identification of Dynamic Cutting tional Conference on PMI, Hannover, Germany, 7–14. Force Coefficients and Chatter Stability with Process Damping. Annals of the [43] Britz R, Ulbrich H (2008) Lathe: Modeling and Coupling of Process and CIRP 57(1):371–374. Structure. Proceedings of the 1st International Conference on PMI, Hannover, [15] Altintas Y, Merdol D (2007) Virtual High Performance Milling. Annals of the Germany, 231–238. CIRP 55(1):81–84. [44] Brinksmeier E, Heinzel C, Wittmann M (1999) Friction, Cooling and Lubrica- [16] Altintas Y, Montgomery D, Budak E (1992) Dynamic Peripheral Plate Milling tion in Grinding. Annals of the CIRP 48(2):581–598. of Flexible Structures, Transactions of ASME. Journal of Engineering for Indus- [45] Brinksmeier E, Klocke F, Giwerzew A, Vucetic D (2002) Spanbildungsmecha- try 114:137–145. nismen beim Schleifen mit niedrigen Schnittgeschwindigkeiten. IDR 4:285– [17] Arentoft M, Wanheim T (2005) A New Approach to Determine Press Stiffness. 293. Annals of the CIRP 54(1):265–268. [46] Brinksmeier E, Aurich J, Govekar E, Heinzel C, Hoffmeister H, Klocke F, Peters J, [18] Bailey M, Hedges L (1995) Die Kristallmorphologie von Diamanten und ABN, Rentsch R, Stephenson D, Uhlmann E, Weinert K, Wittmann M (2006) IDR – Industrie Diamanten Rundschau, 3/95. Advances in Modeling and Simulation of Grinding Processes. Annals of the [19] Bariani P, Dal Negro T, Bruschi S (2004) Testing and Modelling of Material CIRP 55(2):667–696. Response to Deformation in Bulk Metal Forming. Annals of the CIRP [47] Van Brussel H (1971) Dynamische Analyse van het Verspaningsproces. 53(2):573–596. Katholieke Universiteit Leuven, Dissertation, printed as manuscript. [20] Beer C (1994) CAD/CAP unterstu¨ tzte Generierung ratterfreier NC-Programme [48] Budak E (2006) Analytical Models for High Performance Milling. Part I. fu¨ r das Schaftfra¨sen, Dissertation, RWTH Aachen University. Cutting forces, Structural Deformations and Tolerance Integrity. International [21] Behrens B, Landgrebe D (1999) Anwendung der FE-Simulation auf dreidi- Journal of Machine Tools and Manufacture 46:1478–1488. mensionale Massivumformprozesse – Probleme und Lo¨sungen, Umform- [49] Budak E (2006) Analytical Models for High Performance Milling. Part II. technik 2000 Plus, Bamberg, Germany, pp. 71–80. Process Dynamics and Stability. International Journal of Machine Tools and [22] Behrens B, Brecher C, Hork M, Werbs M (2007) New Standardized Procedure Manufacture 46:1489–1499. for the Measurement of the Static and Dynamic Properties of Forming [50] Budak E, Altintas Y, Armarego E (1996) Prediction of Milling Force Coeffi- Machines. Production Engineering 1(1):31–36. cients from Orthogonal Cutting Data, Transactions of ASME. Journal of Man- [23] Behrens B, Ahrens M, Dietrich F, Poelmeyer J (2007) Modellbildung zur ufacturing Science and Engineering 118(2):216–224. Beru¨ cksichtigung des Maschineneinflusses in der numerischen Simulation [51] Budak E, Kayhan M (2004) Investigating Effects of Chatter Vibrations on Tool von Umformprozessen mittels gekoppelter Simulation. Proceedings of 12th Wear in Turning. Proceedings of 4th CIRP International Seminar on Intelligent Dresdner WZM-Fachseminar, Dresden, Germany, 3.1–3.5. Computation in Manufacturing Engineering, Sorrento, Italy, 679–684. [24] Behrens B, Matthias T, Czora M, Poelmeyer J, Ahrens M (2008) Improving [52] Budak E, Ozlu E (2007) Analytical Modeling of Chatter Stability in Turning and the Accuracy of Numerical Investigations of Multi-Stage Sheet Metal Boring Operations: A Multi-Dimensional Approach. Annals of the CIRP Processes by Coupling a Process FE Analysis with the Machine Simulation. 56(1):401–404. Proceedings of 1st International Conference on PMI,Hannover,Germany, [53] Bryan J (1990) International Status of Thermal Error Research. Annals of the 133–139. CIRP 32(2):645–656. [25] Berkemer J (2006) Simulation der Wechselwirkung von Maschine.VDI [54] Byrne G, Dornfeld D, Denkena B (2003) Advancing Cutting Technology. Annals Schwingungstagung, Fulda, Germany, Regelung und Prozess in hochdyna- of the CIRP 52(2):483–507. mischen Werkzeugmaschinen 325–342. [55] Cao Y, Altintas Y (2004) A General Method for the Modeling of Spindle- [26] Biermann D, Kersting M, Surmann T (2007) Simulation der Prozessdynamik Bearing Systems. Transactions of ASME Journal of Machine Design 126:1089– beim Einlippenbohren. wt-Werkstatttechnik Online 97(11/12):879–883. 1104. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 605

[56] Chodnikiewicza K, Balendra R (2000) The Calibration of Metal-forming [86] Gallego I, Lizarralde R, Barrenetxea D, Arrazola P (2006) Precision, Stability Presses. Journal of Materials Processing Technology 106:28–33. and Productivity Increase in Thrufeed Centerless Grinding. Annals of the CIRP [57] Corduan N, Costes J, Lapujoulade F, Larue A (2006) Experimental Approach of 55(1):351–354. Milling Stability of Thin Walled Parts. Comparison with Time Domain Simu- [87] Gonzalo O, Peigne G, Gonzalez D (2006) Thin-Walled Features High Speed lation. Proceedings of the 9th CIRP International Workshop on Modelling of Machining Simulation. Proceedings of the 9th CIRP International Workshop on Machining Operations, Bled, Slovenia, 59–69. Modeling of Machining Operations, Bled, Slovenia, 123–130. [58] D’Acunto A, Al-Ahmad M, Lescalier C, Bomont O (2007) Cutting Force Pre- [88] Gurney J (1964) An Analysis of Centerless Grinding. Journal of Engineering for diction of Vertical Milling Operation using Different Configurations of Cutter Industry 87:163–174. Immersion—Modeling and Experimentation. Proceedings of the CIRP 10th [89] Groche P, Fritsche D, Tekkaya E, Allwood J, Hirt G, Neugebauer R (2007) International Workshop on Modelling of Machining Operations, Calabria, Italy, Incremental Bulk Metal Forming. Annals of the CIRP 56(2):635–656. 165–171. [90] Großmann K (1997) Software-Werkzeuge zur Anlagensimulation – eine [59] Dall A (1946) Rounding Effect in Centerless Grinding. Mechanical Engineering Bestandsaufnahme. Proceedings of 4th Sa¨chsische Fachtagung Umformtechnik 58:325–329. – Wirtschaftsfaktor Umformtechnik, Chemnitz, 216–252. [60] Denkena B, Tracht K, Deichmu¨ ller M (2006) Wechselwirkungen zwischen [91] Großmann K (2003) Simulationspotenzial an Umformmaschinen. Proceedings Struktur und Prozess beim Werkzeugschleifen. wt Werkstattstechnik online 96 of 6th Dresdner Werkzeugmaschinen-Fachseminar, Dresden, Germany, . pp. 11(12):814–819. 1.1–1.47. [61] Denkena B, Tracht K, Clausen M (2005) Predictability of Milling Forces Based [92] Großmann K, Wiemer H, Groche P, Hofmann T (2006) Modellgestu¨ tzte on Specific Cutting Forces. Proceedings of the 8th CIRP International Workshop Analyse von Pressmaschinen auf Grundlage experimentell verifizierter Para- on Modeling Machining Operations, Chemnitz, Germany, 259–266. meter. EFB-Forschungsbericht No. 245, Hannover, Germany, 1–160. [62] Denkena B, Tracht K, Schmidt C (2006) A Flexible Force Model for Predicting [93] Großmann K, Hardtmann A, Wiemer H (2006) Simulation des Blechumform- Cutting Forces in End Milling. Production Engineering 13(1):15–20. prozesses unter Beru¨ cksichtigung des statischen Verhaltens der Press- [63] Denkena B, Mo¨hring H, Will J, Sellmeier V (2006) Prozessstabilita¨t einer maschine. ZWF Zeitschrift fu¨r wirtschaftlichen Fabrikbetrieb 101(10):600–605. piezoaktorisch gelagerten Fra¨sspindel. wt Werkstatttechnik online 9:669–675. [94] Großmann K, Wiemer H, Hardtmann A, Penter L (2007) Faster to Sound Parts [64] Denkena B, Schmidt C (2007) Experimental Investigation and Simulation of by Advanced Forming Process Simulation—Advanced Forming Process Model Machining Thin-Walled Workpieces. Production Engineering 1(4):343–350. Including the Elastic Effects of the Forming Press and Tool. Steel Research [65] Denkena B, Deichmu¨ ller M, Kro¨ger M, Panning L, Carstensen C, Kilian S (2007) International 78:825–830. Modeling and Simulation of the Process Machine Interaction during Tool [95] Großmann K, Wiemer H, Hardtmann A, Penter L (2007) Stand der Simulation Grinding Processes. Proceedings of 10th CIRP International Workshop on Mod- von Umformprozessen mit den elastischen Einflu¨ ssen aus Maschine und eling of Machining Operations, Calabria, Italy, 391–398. Werkzeug. Proccecings of des EFB-Kolloquium – Neue Wege zum wirtschaftli- [66] Denkena B, Deichmu¨ ller M, Kro¨ger M, Popp K, Carstensen C, Schroeder A, chen Leichtbau, vol. T27, Fellbach, Germany, 185–198. Wiedemann S (2008) Geometrical analysis of the complex contact area for [96] Großmann K, Hardtmann A, Wiemer H, Penter L (2008) An Advanced Forming modeling the local distribution of process forces in tool grinding. Proceedings Process Model including the Interactions between Machine, Tool and Process. of the 1st International Conference on PMI, Hannover, Germany, 289–298. Proceedings of 1st International Conference on PMI, Hannover, Germany, 125– [67] DIN 55189 (1988) Machine tools—determination of the ratings of presses for 132. sheet metal working under static load, Beuth Verlag, Berlin, Germany. [97] Großmann K, Wiemer H (2008) Feasibilities of Advanced Forming Process [68] Eberhard P, Gaugele T, Heisel U, Storchak M (2008) A Discrete Element Model Modelling Considering the Interactions with Dies and Machines. Proceedings Used in a Co-simulated Charpy Impact Test and for Heat Transfer. Proceedings of Conference New Developments in Sheet Metal Forming Technology, Fellbach of the 1st International Conference on PMI, Hannover, Germany, 361–368. bei Stuttgart, Germany, 311–350. [69] Epureanu B, Dowell E, Montoya F (1997) Pattern Formation and Linear [98] Großmann K, Wiemer H (1999) Maschine, Werkzeug und Prozess – ein Stability Analysis in Centreless Grinding. Proceedings of the Institution of ganzheitliches System. Proceedings of 6th Sa¨chsische Fachtagung Umformtech- Mechanical Engineers, 619–626. nik, Dresden, Germany, 210–227. [70] Elbestawi M, Ismail F, Du R, Ullagaddi BC (1994) Modelling Machining [99] Guo C, Malkin S, Kovach J, laurich M (1998) Computer Simulation of Below Dynamics Including Damping in the Tool-Workpiece Interface. Journal of Centre and Above Centre Centreless Grinding. Machining Science and Tech- Engineering for Industry 116:435–439. nology 1(2):235–249. [71] Engel U, Kroiß T, Vo¨lkl R (2007) Berechnung der Wechselwirkungen zwischen [100] Hamm C, Dietmair A, Croon N (2006) Gekoppelte ‘‘Offline-Simulation’’ mit Umformmaschine und –prozess auf Basis der Integration eines Pressenmo- bidirektionaler Anbindung einer NC-Steuerung (VNCK), Final Report on the dells in die FE-Fließpresssimulation. Proceedings of the 12th Dresdner WZM- BMBF-Project SimCAT, pp. 41–46. Fachseminar, Dresden, Germany, 9.1–9.12. [101] Hannig S (2006) Analysis and Modelling of the Dynamic Behaviour of [72] Enk D, Surmann T (2006) Analysis of the Cutting Tool Vibration while Milling Grinding Processes, Fortschritts-Berichte VDI Vol. 660/4. with Changing Engagement Conditions. Proceedings of the 9th CIRP Interna- [102] Hannig S (2008) Analyse, Modellierung und Simulation des dynamischen tional Conference on Modeling of Machining Operations, Bled, Slovenia, 139– Verhaltens beim spitzenlosen Einstechschleifen, Dissertation, RWTH Aachen 144. University. [73] Feng H, Azeem A, Wang L (2004) Simplified and Efficient Calibration of a [103] Harrison A, Pearce T (2002) Prediction of Lobe Growth and Decay in Centre- Mechanistic Cutting Force Model for Ball-End Milling. Machine Tools and less Grinding based on Geometric Considerations. Proceedings of the Institu- Manufacture 44:217–268. tion of Mechanical Engineers 1201–1216. [74] Filice L, Micari F, Rizzuti S, Umbrello D (2007) Dependance of Machining [104] Helduser S, Lohse H, Behrens B, Marthiens O, Poelmeyer J (2008) Compre- Simulation Effectiveness on Material and Friction Modelling. Machining hensive Simulation of Hydraulic Deepdrawing Presses Including the Forming Science and Technology 12:370–389. Process. Proceedings of 6th IFK, International Fluid Power Conference, Dresden, [75] Fleischer J, Schmidt J, Schmidt C, Schermann T (2005) Zerspanungssimulation Germany, 171–185. – als wichtiger Baustein zur Kopplung von Prozess und Maschine, Springer [105] Hermann M, Fiderer M, Walters J (2005) State-of-the-Art in Process Simula- Verlag. VDI-Z – integrierte Produktion 2:63. tion of Forming Processes. Proceedings of Conference on New Developments in [76] Folkerts W (1993) Dynamische Prozesskennwerte des Schleifens und deren Forging Technology, Fellbach bei Stuttgart, Germany, 357–372. Einfluss auf das Prozessverhalten, Dissertation, RWTH Aachen University. [106] Herzenstiel P, Ching C, Ricker S, Menzel A, Steinmann P, Aurich J (2007) [77] Fortunato A, Mantega C, Donati L, Tani G (2006) Milling Force Prediction by Interaction of Process and Machine During High Performance Grinding— Means of Analytical Model and 3D FEM Simulations. Proceedings of the 9th Towards a Comprehensive Simulation Concept. International Journal of Man- CIRP International Workshop on Modelling of Machining Operations, Bled, ufacturing Technology and Management 12(1–3):155–170. Slovenia, 211–213. [107] Heylen W, Lammens S, Sas P (2003) Modal Analysis Theory and Testing.KU [78] Franzke M, Puchhala S, Dackweiler H (2007) Modelling the interaction effects Leuven. ISBN 90-7380261-X. between tools and the workpiece for metal forming processes. Proceedings of [108] Hoffmann F, Brecher C (2006) Simulation dynamischer Bahnabweichungen NUMIFORM 2007, 9th International Conference on Numerical Methods in Indus- von Werkzeugmaschinen. Proceedings of VDI Conference ‘‘Elektrisch-mechan- trial Forming Processes, vol. 908, Porto, Portugal, 1489–1494. ische Antriebssysteme’’,Du¨ sseldorf, VDI, 301–314. [79] Franzke M, Puchhala S, Dackweiler H, Hirt G (2008) Gekoppelte Analyse von [109] Hoffmann F (2008) Optimierung der dynamischen Bahngenauigkeit von Massivumformprozessen mit LASTRAN/Shape. Proceedings of MEFORM 2008 – Werkzeugmaschinen mit der Mehrko¨rpersimulation, Dissertation, RWTH Simulation von Umformprozessen, Freiberg, Germany, 119–130. Aachen University. [80] Franzke M, Puchhala S, Dackweiler H, Hirt G (2008) Modeling of Interaction [110] Ho¨vel S (2008) Finite Elemente Simulation von Zerspanvorga¨ngen mit geo- Effects between the Process and Machine during Flat Rolling Process. metrisch bestimmter Schneide, Dissertation, TU Kaiserslautern University. Proceedings of 1st International Conference on PMI, Hannover, Germany, [111] Inasaki I (1977) Selbsterregte Ratterschwingungen beim Schleifen, Metho- 149–156. den zu Ihrer Unterdru¨ ckung. Werkstatt und Betrieb 110(8):521–524. [81] Freiherr T (1999) Experimentelle und rechnergestu¨ tzte Analyse des dyna- [112] Inasaki I (1996) Grinding Process Simulation Based on the Wheel Topography mischen Genauigkeitsverhaltens einer Kurbelpresse, Dissertation, University Measurement. Annals of the CIRP 45(1):347–350. Kassel. [113] Inasaki I, Karpuschewski B, Lee H (2001) Grinding Chatter—Origin and [82] Freiherr T, Wagener H (2004) Laser-Mess-technik als Voraussetzung fu¨ r die Suppression. Annals of the CIRP 50(2):515–534. Weiterentwicklung umformtechnischer Produktionssysteme, wt Werkstatt- [114] Insperger T, Edes B, Mann B, Stepan G (2006) The Effect of Runout on the stechnik online vol. 94/5, pp. 199–203. Chatter Frequencies of Milling Processes. Proceedings of the 9th CIRP Inter- [83] Friedrich D (2004) Prozessbegleitende Beeinflussung des geometrischen national Workshop on Modeling of Machining Operations, Bled, Slovenia, 301– Rundungseffektes beim spitzenlosen Außenrundeinstechschleifen, Disserta- 314. tion, RWTH Aachen University. [115] Jansen T (2007) Entwicklung einer Simulation fu¨ r den NC-Formschleifpro- [84] Furukawa Y, Miyashita M (1970) Chatter Vibration in Centerless Grinding. zess mit Torusschleifscheiben, Dissertation, TU Dortmund University. Bulletin of the JSME 13(64):1274–1283. [116] Jrad M, Devillez A, Dudzinski D (2006) Thermomechanical Approach of [85] Gallego I (2007) Intelligent Centerless Grinding: Global Solution for Process Drilling Based on a CAD Definition. Proceedings of the 9th CIRP International Instabilities and Optimal Cycle Design. Annals of the CIRP 56(1):347–352. Workshop on Modeling of Machining Operations, Bled, Slovenia, 247–253. 606 C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607

[117] Kalveram M (2005) Analyse und Vorhersage der Prozessdynamik und der [153] Okuyama S, Kitajima T, Yui A (2004) Theoretical Study on the Effect of Form Prozessstabilita¨t beim Hochgeschwindigkeitsfra¨sen, Dissertation, TU Dort- Error of Grinding Wheel Surfaces Under Free Form Grinding. Key Engineering mund University. Materials 257–258:147–152. [118] Kassen G (1969) Beschreibung der elementaren Kinematik des Schleifvor- [154] Ozturk E, Budak E (2005) Modelling of 5-Axis Milling Forces. Proceedings of ganges, Dissertation, RWTH Aachen University. the 8th CIRP International Workshop on Modelling of Machining Operations, [119] Kegg R (1965) Cutting Dynamics in Machine Tool Chatter. ASME Journal of Chemnitz, Germany, 319–326. Engineering for Industry 87(4):464–470. [155] Ozturk E, Ozlu E, Budak E (2007) Modeling Dynamics and Stability of 5-axis [120] Kempa B (2000) Zahnflankenprofilschleifen mit galvanisch-gebundenem Milling Processes. Proceedings of the 10th CIRP International Workshop on CBN, Dissertation, RWTH Aachen University. Modeling of Machining Operations, Calabria, Italy, 469–476. [121] Kienzle O (1952) Die Bestimmung von Kra¨ften und Leistungen an spanenden [156] Ozlu E, Budak E (2006) Analytical prediction of stability limit in turning Werkzeugen und Werkzeugmaschinen. VDI Z 94(11–12):299. operations. Proceedings of the 9th CIRP International Workshop on Modeling of [122] Kienzle O (1954) Einfluss der Wa¨rmebehandlung von Sta¨hlen auf die Machining Operations, Bled, Slovenia, 99–106. Hauptschnittkraft beim Drehen. Stahl Eisen 74:530–551. [157] Ozlu E, Budak E, Molinari A (2007) Thermomechanical Modeling of Ortho- [123] Kim K (2003) 2-Dimensional Modelling of Centreless Grinding, Interference gonal Cutting Including the Effect of Stick-Slide Regions on the Rake Face. Phenomena, Infeed (Plunge) Process. International Journal of KSPE 4(4):32– Proceedings of the CIRP 10th International Workshop on Modelling of Machining 38. Operations, Calabria, Italy, 59–66. [124] Kleiner M, Geiger M, Klaus A (2003) Manufacturing of Lightweight Compo- [158] Piendl S, Aurich J (2006) FEM Simulation of Chip Formation coupled with nents by Metal Forming. Annals of the CIRP 52(2):521–542. Process Dynamics. Journal of Manufacture and Engineering 220:1597–1604. [125] Klocke F, Eisenbla¨tter G (1997) Dry Cutting. Annals of the CIRP 46(2):519–526. [159] Polacek M (1970) Stabilita¨t von Werkzeugmaschinen. WB Werkstatt und [126] Klocke F, Krieg T (1999) Coated Tools for Metal Cutting—Features and Betrieb 103:657–663. Applications. Annals of the CIRP 48(2):515–525. [160] Popp K, Kro¨ger M, Deichmu¨ ller M, Denkena B (2008) Analysis of the Machine [127] Klocke F, Raedt H, Hoppe S (2001) 2D-FEM Simulation of the Orthogonal HSC Structure and Dynamic Response of a Tool Grinding Machine. Proceedings of Process. Proceedings of the Fourth CIRP International Workshop of Machining the 1st International Conference on PMI, Hannover, Germany, 299–307. Operations, Delft, Netherlands, 117–124. [161] Reeka D (1967) U¨ ber den Zusammenhang zwischen Schleifspaltgeometrie [128] Klocke F (2003) Modelling und Simulation in Grinding. Proceedings of the 1st und Rundheitsfehler beim spitzenlosen Schleifen, Dissertation, RWTH European Conference on Grinding, Aachen, Fortschritt-Berichte VDI, 8.1– Aachen University. 8.27. [162] Roll K, Altan T, Tekkaya, A, Herrmann M (1999) Virtuelle Umformtechnik, [129] Klocke F, Duscha M, Hoffmann F, Wegner H, Zeppenfeld C (2008) Proceedings Umformtechnik 2000 Plus, Bamberg, Meisenbach, pp. 255–274. of the 1st International Conference on PMI. Machine–Grinding Wheel–Work- [163] Roll K (2007) Simulation der Blechumformung. Proceedings of 12th Dresdner piece Interaction in Speed Stroke Grinding 259–266. WZM-Fachseminar, Dresden, Germany, 1.1–1.14. [130] Klotz N (1987) Beurteilung des statischen und dynamischen Verhaltens von [164] Roukema J, Altintas Y (2007) Generalized Modeling of Drilling Vibrations, Umfangsschleifmaschinen, Dissertation, RWTH Aachen University. Part I. Time Domain Model of Drilling Kinematics, Dynamics and Hole [131] Ko¨nig W, Schreitmu¨ ller H, Ho¨nscheid W (1972) Untersuchung des Spitzen- Formation. International Journal of Machine Tools and Manufacture losschleifens, Forschungsbericht des Landes Nordrhein-Westfalen, Nr. 2288, 47(9):1455–1473. Westdeutscher Verlag Opladen. [165] Roukema J, Altintas Y (2007) Generalized Modeling of Drilling Vibrations. [132] Ko¨nig W, Cronja¨ger L, Spur G, To¨nshoff K, Vigneau M, Zdeblick J (1990) Part II. Chatter Stability in Frequency Domain. International Journal of Machine Machining of New Materials. Annals of the CIRP 39(2):673–681. Tools and Manufacture 47(9):1474–1485. [133] Ko¨ rner E, Szentmihalyi V, Lutz M (2003) Rechnergestu¨ tzte Entwicklung von [166] Rowe W, Barash M (1964) Computer Method for Investigating the Inherent Pra¨zisionsumformteilen. Proceedings of the Confernce Neuere Entwicklungen Accuracy of Centerless Grinding. International Journal of Machine Tool Design in der Massivumformung, Fellbach bei Stuttgart, Germany, June 3–4, 279– and Research 4:91–116. 298. [167] Rivie`re-Lorphe`vre E, de Arizon J, Filippi E, Dehombreux P (2007) Cutting [134] Krimm R (2006) Berechnung der lastabha¨ngigen Maschinenauffederung zur Forces Parameters Evaluation in Milling Using Genetic Algorithm. Proceed- Verku¨ rzung der Anlaufzeit neuer Transferwerkzeugsa¨tze, Dissertation, Uni- ings of the CIRP 10th International Workshop on Modelling of Machining versity of Hannover. Operations, Calabria, Italy, 237–243. [135] Kroiß T, Vo¨lkl R, Engel U, Geiger M (2008) Modeling of Process–Tool–Machine [168] Sakakura M, Tsukamoto S, Fujiwara T, Inasaki I (2008) Visual Simulation of Interactions in Cold Forging. Proceedings of the 1st International Conference on the Grinding Process. Proceedings of IMechE Part B Journal of Engineering PMI, Hannover, Germany, 175–182. Manufacture 222:1233–1239. [136] Law S, Wu S (1973) Simulation Study of the Grinding Process. Transactions of [169] Salje E, Dietrich W (1982) Analysis of Self Excited Vibrations in External the ASME Journal of Engineering for Industry 1(73):972–978. Cylindrical Plunge Grinding. Annals of the CIRP 56(1):255–258. [137] Lee D (2001) Modeling of High-Speed Tapping Torque Considering Friction [170] Schapp L, Brecher C, Paepenmu¨ ller F (2006) Gekoppelte Simulation von Force. KSPE 18:67–73. Maschine und Prozess in der Massivumformung. Schmiede-Journal 3:22–25. [138] Lizarralde R, Barrenetxea D, Gallego I, Marquinez J (2005) Practical Applica- [171] Schapp L, Brecher C, Paepenmu¨ ller F (2007) Vorstoß in neue Dimensionen – tion of New Simulation Methods for the Elimination of Geometric Instabil- Kopplung von Umformsimulation mit nicht-linearen Pressenmodellen. ities in Centerless Grinding. Annals of the CIRP 54(1):273–276. Schmiede-Journal 3:22–24. [139] van Luttervelt C, Childs T, Jawahir I, Klocke F, Venuvinod P (1998) Present [172] Schapp L (2008) Gekoppelte Simulation von Maschine und Prozess in der Situation and Future Trends in Modelling of Machining Operations. Annals of Massivumformung, Dissertation, RWTH Aachen University. the CIRP 47(2):587–626. [173] Schiefer K (1980) Theoretische und experimentelle Stabilita¨tsanalyse des [140] Malkin S, Guo C (2007) Thermal Analysis of Grinding. Annals of the CIRP Schleifprozesses, Dissertation, RWTH Aachen University. 56(2):760–782. [174] Schermann T, Marsolek J, Schmidt C, Fleischer J (2006) Aspects of the [141] Meier H, Reese S, Bertsch C, Laurischkat R (2008) Increase of the Dimensional Simulation of a Cutting Process with ABAQUS/Explicit Including the Inter- Accuracy of Sheet Metal Parts utilizing a Model-Based Path Design for Robot- action between the Cutting Process and the Dynamic Behaviour of the Based Forming Processes. Proceedings of 1st International Conference on PMI, Machine Tool. Proceedings of the 9th CIRP International Workshop on Modeling Hannover, Germany, 141–148. of Machining Operations, Bled, Slovenia, 163–170. [142] Mense C, Uhlmann E (2007) Analysis of the Milling Machine Operating [175] Schmidt C (2006) Level Curve Based Geometry Representation for Cutting Behaviour for Process Stability Prediction and Machine Tool Optimisation. Force Predicition. Annals of DAAAM & Proceedings of the 17th Int. DAAAM Proceedings of the 10th CIRP International Workshop on Modeling of Machining Symposium, Vienna, Austria, 367–368. Operations, Calabria, Italy, 421–428. [176] Schmoeckel D, Hielscher C, Huber R (1999) Metal Forming of Tubes and [143] Merrit H (1965) Theory of Self-Excited Machine-Tool Chatter Contribution to Sheets with Liquid and Other Flexible Media. Annals of the CIRP 48(2):497– Machine-Tool Chatter. Journal of Engineering for Industry 87(4):454–477. 513. [144] Michels F (1999) Stabilisierung des Schleifprozesses mit aktiven Systemen, [177] Schulz H, Moriwaki T (1992) High-Speed Machining. Annals of the CIRP Dissertation, RWTH Aachen University. 41(2):637–643. [145] Miyashita M, Hashimoto F, Kanai A (1982) Diagram for Selecting Chatter Free [178] Schumacher A (2004) Optimierung mechanischer Strukturen – Grundlagen und Conditions of Centerless Grinding. Annals of the CIRP 31(1):221–223. industrielle Anwendungen. Springer Verlag. [146] Mo¨hring W, Fischer R, Melchinger A (2006) Simulation großer Verfahrwege [179] Schu¨ tte O (2003) Analyse und Modellierung nichtlinearer Schwingungen in der FEM, Abschlussbericht des BMBF- Verbundforschungsprojekts Sim- beim Außenrundeinstechschleifen, Dissertation, University of Hannover. CAT, pp. 47–50. [180] Schwarz F (2006) Prognose von Prozess-Struktur-Wechselwirkungen bei [147] Moreau V, Costes J, Fores C (2007) Investigation on Tool Dynamic Behaviour Werkzeugmaschinen. Newsletter 3 8:1–3. in a Milling Process Using Displacement Sensors. Proceedings of the 10th CIRP [181] Smith J, Tobias S (1961) The Dynamic Cutting of Metals. International Journal International Workshop on Modeling of Machining Operations, Calabria, Italy, of Machine Tool Design and Research 1:283–292. 485–490. [182] Ste´pa´n G, Insperger T (2000) Stability of the milling process. Periodica [148] Moufki A, Devillez A, Dudzinski D, Moulinari A (2004) Thermomechanical Polytechnica Series Mechanical Engineering 44:47–57. Modelling of Oblique Cutting and Experimental Validation. International [183] Ste´pa´n G, Szalai R, Insperger T (2003) Nonlinear Dynamics of High-speed Journal of Machine Tools and Manufacture 44:971–989. Milling Subjected to Regenerative Effect, Nonlinear Dynamics of Production [149] Muckelbauer M, Bo¨se L (2000) Virtuelle Prozessentwicklung mit Schmiede- Systems. Wiley-VCH. pp. 111–128. simulationssoftware. Schmiede-Journal 9:36–37. [184] Surmann T, Weinert K, Kalveram M (2005) Simulation of Cutting Tool [150] Neugebauer R, Altan T, Geiger M, Kleiner M, Sterzing A (2006) Sheet Metal Vibrations for the Milling of Free Formed Surfaces. Proceedings of the 8th Forming at Elevated Temperatures. Annals of the CIRP 55(2):793–816. CIRP International Workshop on Modeling of Machining Operations, Chemnitz, [151] Neugebauer R, Denkena B, Wegener K (2007) Mechatronic Systems for Germany, 175–182. Machine Tools. Annals of the CIRP 56(2):657–686. [185] Surmann T (2006) Geometric Model of the Surface Structure Resulting from [152] Ngaile G, Altan T (2003) Simulations of Manufacturing Process—Past, Present the Dynamic Milling Process. Proceedings of the 9th CIRP International Con- and Future. Proceedings of ICTP 271–283. ference on Modeling of Machining Operations, Bled, Slovenia, 187–192. C. Brecher et al. / CIRP Annals - Manufacturing Technology 58 (2009) 588–607 607

[186] Surmann T, Enk D (2007) Simulation of Milling Tool Vibration Trajectories [207] Weinert K, Surmann T, Mu¨ ller H (2006) Modeling of Surface Structures Along Changing Engagement Conditions. International Journal of Machine Resulting from Vibrating Milling Tools. Production Engineering 13(2):133– Tools and Manufacture 47:1442–1448. 138. [187] Surmann T, Biermann D, Kehl G (2008) Oscillator Model of Machine Tools for [208] Weinert K, Blum H, Jansen T, Mohn T, Rademacher A (2006) Angepasste the Simulation of Self Excited Vibrations in Machining Processes. Proceedings Simulationstechnik zur Analyse NC-gesteuerter Formschleifprozesse. ZWF of the 1st International Conference on PMI, Hannover, Germany, 23–29. Zeitschrift fu¨r wirtschaftlichen Fabrikbetrieb 101(7–8):422–425. [188] Szalai R, Mann B, Stephan G (2006) Period-two and Quasi-Periodic Vibrations [209] Weinert K, Blum H, Jansen T, Rademacher A (2007) Simulation Based of High-Speed Milling. Proceedings of the 9th CIRP International Workshop on Optimization of the NCShape Grinding Process with Toroid Grinding Wheels Modeling of Machining Operations, Bled, Slovenia, 107–114. Prod Eng - Research and Development, vols. 1–3. Springer, Berlin. pp. 245–252. [189] Tlusty J (1978) Analysis of the State of Research in Cutting Dynamics. Annals [210] Wienstro¨ er M (2004) Prozesssimulation der Stadienfolge beim Schmieden of the CIRP 27(2):583–589. mittels Ru¨ ckwa¨rtssimulation, Dissertation, University of Hannover. [190] Tlusty J (1993) High-Speed Machining. Annals of the CIRP 42(2):733–738. [211] Wiemer H (2004) Stand und Mo¨glichkeiten der Systemsimulation von [191] To¨nshoff H, Peters J, Inasaki I, Paul T (1992) Modelling and Simulation of mechanischen Pressmaschinen, Dissertation, TU Dresden University. Grinding Processes. Annals of the CIRP 41(2):677–688. [212] Witt S (2007) Integrierte Simulation von Maschine, Werkstu¨ ck und spanen- [192] To¨nshoff H, Karpuschewski B, Mandrysch T (1998) Grinding Process Achieve- dem Fertigungsprozess, Dissertation, RWTH Aachen University. ments and their Consequences on Machine Tools—Challenges and Opportu- [213] Yegenoglu K (1986) Berechnungen von Topografiekenngro¨ßen zur Ausle- nities. Annals of the CIRP 47(2):651–668. gung von cBN – Schleifprozessen, Dissertation, RWTH Aachen University. [193] To¨nshoff H, Arendt C, Ben Amor R (2000) Cutting of Hardened Steel. Annals of [214] Younis M (1972) Theoretische und praktische Untersuchung des Ratterver- the CIRP 49(2):547–566. haltens beim Außenrundeinstechschleifen, Dissertation, RWTH Aachen Uni- [194] To¨nshoff H, Rehling S, Tracht K (2002) An Alternative Approach to Elasto- versity. Kinematic Modelling of Machine Tool Structures. Proceedings of Sixth Inter- [215] Yoshikawa H, Sata T (1968) Simulated Grinding Process by Monte Carlo national Conference on Advanced Manufacturing Systems and Technology Method. Annals of the CIRP 16(4):297–302. (AMST’02), Udine, Italy, 215–223. [216] Yoshikawa H, Peklenik J (1970) Three Dimensional Simulation Techniques of [195] Tunc L, Budak E, Ozturk E (2006) Optimization of 5-Axis Milling Processes the Grinding Process – II, Effects of Grinding Conditions and Wear on the Using Process Models. Proceedings of the 9th CIRP International Workshop on Statistical Distribution of Geometrical Chip Parameters. Annals of the CIRP Modeling of Machining Operations, Bled, Slovenia, 179–186. 18(1):361–366. [196] VDI-guideline 3193, Hydraulic Presses for Cold Forging and Sheet Metal Work- [217] Za¨h M (1993) Dynamisches Prozeßmodell Kreissa¨gen, Dissertation, TU ing—Measuring Instruction for Acceptance, (1986), Beuth Verlag, Berlin, Ger- Mu¨ nchen University. many. [218] Za¨h M, Schwarz F (2005) Struktur- und Regelungsdynamik der virtuellen [197] VDI-guideline 3194, Mechanical Presses for Cold Forging—Measuring Instruction Werkzeugmaschine, iwb. Newsletter 1(13):1–3. for Acceptance, (1989), Beuth Verlag, Berlin, Germany. [219] Za¨h M, Siedl D (2005) Mehrko¨rpersimulation - Schlu¨ sseltechnologie fu¨ r [198] Vormann K (2007) Integrierte Simulation von Zerspanprozess, Werkzeug große Verfahrbewegungen, iwb. Newsletter 1(13):3–5. und Werkzeugmaschine. Abschlussbericht des Verbundprojektes Simulation [220] Za¨h M, Siedl D (2007) A New Method for Simulation of Machining Perfor- industrieller Bearbeitungsprozesse (SindBap). Proceedings of the Final Collo- mance by Integrating Finite Element and Multi-Body Simulation for Machine quium, Aachen, 7–10. Tools. Annals of the CIRP 56(1):383–386. [199] Werner K, Klocke F, Brinksmeier E (2003) Modelling and Simulation of [221] Za¨h F, Schwarz F (2006) Prognose von Prozess-Struktur-Wechselwirkungen Grinding Processes. 1st European Conf. on Grinding, Aachen, . 8.1-8.27. bei Werkzeugmaschinen, iwb. Newsletter 3(14):1–3. [200] Weck M, Brecher C (2006) . Werkzeugmaschinen Fertigungssysteme Messtech- [222] Za¨h M, Schwarz F (2008) Consideration of Tool and Workpiece Temperatures nische Untersuchung und Beurteilung dynamische Stabilita¨t, 7th edition, vol. 5. in a Modular Cutting Force Model. Proceedings of the 1st International Con- Springer-VDI-Verlag, Berlin. ference on PMI, Hannover, Germany, 353–361. [201] Weck M, Hennes N, Schulz A (1998) Dynamic Behaviour of Cylindrical [223] Zeppenfeld C (2005) Schnellhubschleifen von g–Titanaluminiden, Disserta- Traverse Grinding Processes. Annals of the CIRP 50(1):213–216. tion, RWTH Aachen University. [202] Weck M, McKeown P, Bonse R, Herbst U (1995) Reduction and Compensation [224] Zeppenfeld C, Nachmani Z (2006) Mechanisms of Action in Speed Stroke of Thermal Errors in Machine Tools. Annals of the CIRP 44(2):589–598. Grinding of Different Workpiece Materials. Proceedings of the 2nd European [203] Weck M, Staimer D (2002) Parallel Kinematic Machine Tool—urrent State and Conference on Grinding, 11.1–11.28. Future Potentials. Annals of the CIRP 51(2):671–681. [225] Zhou S (1994) A Dynamic Study of the Plunge Centerless Grinding Process [204] Weinert K, Inasaki I, Sutherland J, Wakabayashi T (2004) Dry Machining and and its Effects on Workpiece Out-of-roundness, Dissertation, University of Minimum Quantity Lubrication. Annals of the CIRP 53(2):511–537. Connecticut. [205] Weinert K, Webber O, Peters C (2005) On the Influence of Drilling Depth [226] Zhou S, Gartner J, Howels T (1996) On the Relationship between Setup Dependent Modal Damping on Chatter Vibration in BTA Deep Hole Drilling. Parameters and Lobing Behavior in Centerless Grinding. Annals of the CIRP Annals of the CIRP 54(1):363–366. 45(1):341–346. [206] Weinert K, Gradisek J, Kalveram M (2005) On Stability Prediction for Milling. [227] Zitt U (1999) Modellierung und Simulation von Hochleistungsschleifprozes- International Machine Tools and Manufacture 45:769–781. sen, Dissertation, TU Kaiserslautern University.