Ueml: Towards a Unified Enterprise Modelling Language
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Steps in Enterprise Modelling Aroadmap
Steps in Enterprise Modelling aRoadmap Joannis L. Kotsiopoulos\ (Ed.), Torsten Engel2, Frank-Walter Jaekel3, Kurt Kosanke4, Juan Carlos Mendez Barreiro 5, Angel Ortiz Bas6, Michael Petie, and Patrik Raynaud8 1Zenon S.A., Greece, 2Fztr PDE, Germany, 3FhG-IPK, Germany, 4CIMOSA Association, Germany, 5AdN Internacional, S.A. de C. V., Mexico, 6Universidad Politecnica de Valencia, Spain, 7Univ. Notre-Dame de Ia Paix, Namur, Belgium, 8PSA, France, [email protected] Abstract: see Quad Chart on page 2 1 INTRODUCTION Advances in Information Technology have made Enterprise Modelling possible for many enterprises of today. A variety of software tools has ap peared in the market, processing power has dramatically increased, model ling architectures have evolved and even matured. Despite such advances however, widespread use of models, as a strategic decision support tool en compassing large industrial sectors, remains unattainable. The working group analysed the current situation, identified major problems and issues as causes and suggested a roadmap for the next steps in Enterprise Modelling. The following Quad-Chart (Table 1) summarises the work of the group that addressed those requirements. It identifies the approach taken to resolve the issues and proposes a project and ideas for future work for testing and enhancing the proposed solutions. The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-0-387-35621-1_43 K. Kosanke -
Enterprise Architecture and Systems Engineering
Enterprise Architecture and Systems Engineering Peter Webb BMT Defence Services Limited, United Kingdam, [email protected] Abstract: Factors such as the end of the cold war and increasing globalisation in tenns of competition and social responsibility have significantly increased the complex ity of events addressed both by governments and by industry. Furthennore, their responses are increasingly more constrained by economic and environ mental issues. It is clear that the large complex "socio-techno-economic" sys tems (i.e. enterprises) that may comprise as well as create and deliver these re sponses must be both agile and efficient. An approach to the analysis, design and specification of such enterprises is presented which draws on state of the art Enterprise Architecture concepts and Systems Engineering techniques. The resulting EA/SE method enables clear justification of design, definition of in terfaces and derivation of validated requirements. Comparisons are drawn to Zachman and ISO 15704 - GERA concepts. 1 INTRODUCTION This paper describes how enterprise architecture concepts and systems engineering techniques have been combined to provide a new approach to the analysis, design and specification of enterprises. It has been named the Enterprise Architecture I Systems Engineering (EA/SE) method. Enterprise architecture provides a rich but generic framework that guides the construction of enterprise models. Furthermore, it enables stakeholder needs and expectations to be identified and traced to technological design while facilitating integration efforts. Systems engineering provides the tools and techniques to create "well engineered" enterprise architectures. In particular, it uses modelling as a means for analysis, improvement and validation of proposed solutions. Sys- The original version of this chapter was revised: The copyright line was incorrect. -
DATA MODELS to SUPPORT METROLOGY by Saeed
DATA MODELS TO SUPPORT METROLOGY by Saeed Heysiattalab A dissertation submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mechanical Engineering Charlotte 2017 Approved by: ______________________________ Dr. Edward P. Morse ______________________________ Dr. Robert G. Wilhelm ______________________________ Dr. Jimmie A Miller ______________________________ Dr. M. Taghi Mostafavi ______________________________ Dr. Jing Xiao ii ©2017 Saeed Heysiattalab ALL RIGHTS RESERVED iii ABSTRACT SAEED HEYSIATTALAB. Data models to support metrology (Under the supervision of Dr. EDWARD P. MORSE) The Quality Information Framework (QIF) is a project initiated in 2010 by the Dimensional Metrology Standards Consortium (DMSC is an American Standards Developing Organization) to address metrology interoperability. Specifically, the QIF supports the exchange of metrology-relevant information throughout the product lifecycle from the design stage through manufacturing, inspection, maintenance, and recycling / end-of-life processing. The QIF standard is implemented through a set of XML schemas called "Application Schemas" along with common core "XML schema libraries". Of these schemas, QIF Measurement Resources and QIF Rules are the two application schemas on which this research is focused. QIF Measurement Resources is an application schema developed to provide standard representations of physical measuring tools and components, and can be used to support measurement planning, statistical studies, traceability, etc. The Resources schema was supported by the creation of a new hierarchy of metrology resources in support of the product lifecycle. The QIF Rules schema is under development to provide the language with which manufacturers can define how dimensional measurement equipment is selected for various tasks, and how this equipment is used during the measurement task. -
Fundamentals of Enterprise Systems Engineering (ESE)* Outline
1 On Complex Adaptive System Engineering (CASE) Brian E. White, Ph.D. Director, Systems Engineering Process Office (SEPO) The MITRE Corporation 12 May 2008 8th Understanding Complex Systems Symposium University of Illinois at Champaign-Urbana 12-15 May 2008 Public Release Case Number: 08-1459 © 2008 The MITRE Corporation. All rights reserved Fundamentals of Enterprise Systems Engineering (ESE)* Outline Big Ideas Basics of ESE – Making it an engineering discipline Next generation systems thinking An example ____________ * ESE can be thought of as the same as complex systems engineering (CSE) 2 [White, 2008b] © 2008 The MITRE Corporation. All rights reserved but there can be nuances of difference. See Charts 8 and 44. Big Ideas Complex systems abound – Mega-projects in transportation, the environment, U.S. DoD’s Global Information Grid (GIG), etc. – Internet culture—massive connectivity and interdependence Complexity theory applies – Much activity in complexity science across many fields – University interest in developing ideas for engineering (MIT, Johns Hopkins, UCSD, USC, Stevens, UVM, U of I, Old Dominion) Complexity is embedded in everyday knowledge – The Gardener metaphor (vs. The Watchmaker) – Biology and natural evolutionary processes – The way we think, our language/semantics – Markets (viz., The Wisdom of Crowds, The Black Swan) Traditional Systems Engineering (TSE) methods may not help – But temptation is strong to keep trying them One can dependably, but not predictably, build complex systems – Using systems thinking and Complex Systems Engineering (CSE) 3 [White, 2008b] © 2008 The MITRE Corporation. All rights reserved A Spectrum of Systems See Notes Page System: An instance of a set of degrees of freedom* having relationships with one another sufficiently cohesive to distinguish the system from its environment.** *Normally grouped into subsets or elements **This cohesion is also called system identity Less complex More complex Pre-specified Evolving 4 [White, 2008b] and [Kuras-White, 2005] © 2008 The MITRE Corporation. -
Modelling, Analysis and Design of Computer Integrated Manueactur1ng Systems
MODELLING, ANALYSIS AND DESIGN OF COMPUTER INTEGRATED MANUEACTUR1NG SYSTEMS Volume I of II ABDULRAHMAN MUSLLABAB ABDULLAH AL-AILMARJ October-1998 A thesis submitted for the DEGREE OP DOCTOR OF.PHILOSOPHY MECHANICAL ENGINEERING DEPARTMENT, THE UNIVERSITY OF SHEFFIELD 3n ti]S 5íamc of Allai]. ¿Hoot (gractouo. iHHoßt ¿Merciful. ACKNOWLEDGEMENTS I would like to express my appreciation and thanks to my supervisor Professor Keith Ridgway for devoting freely of his time to read, discuss, and guide this research, and for his assistance in selecting the research topic, obtaining special reference materials, and contacting industrial collaborations. His advice has been much appreciated and I am very grateful. I would like to thank Mr Bruce Lake at Brook Hansen Motors who has patiently answered my questions during the case study. Finally, I would like to thank my family for their constant understanding, support and patience. l To my parents, my wife and my son. ABSTRACT In the present climate of global competition, manufacturing organisations consider and seek strategies, means and tools to assist them to stay competitive. Computer Integrated Manufacturing (CIM) offers a number of potential opportunities for improving manufacturing systems. However, a number of researchers have reported the difficulties which arise during the analysis, design and implementation of CIM due to a lack of effective modelling methodologies and techniques and the complexity of the systems. The work reported in this thesis is related to the development of an integrated modelling method to support the analysis and design of advanced manufacturing systems. A survey of various modelling methods and techniques is carried out. The methods SSADM, IDEFO, IDEF1X, IDEF3, IDEF4, OOM, SADT, GRAI, PN, 10A MERISE, GIM and SIMULATION are reviewed. -
Enterprise Modelling: from Early Languages to Models Transformation Bruno Vallespir, Yves Ducq
Enterprise modelling: from early languages to models transformation Bruno Vallespir, Yves Ducq To cite this version: Bruno Vallespir, Yves Ducq. Enterprise modelling: from early languages to models transforma- tion. International Journal of Production Research, Taylor & Francis, 2018, 56 (8), pp.2878 - 2896. 10.1080/00207543.2017.1418985. hal-01836662 HAL Id: hal-01836662 https://hal.archives-ouvertes.fr/hal-01836662 Submitted on 12 Jul 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ENTERPRISE MODELLING: FROM EARLY LANGUAGES TO MODELS TRANSFORMATION Bruno Vallespir, Yves Ducq Univ. Bordeaux, CNRS, IMS, UMR 5218, 33405 Talence, France [email protected], [email protected] Abstract During the last thirty years, enterprise modelling has been recognised as an efficient tool to externalise the knowledge of companies in order to understand their operations, to analyse their running and to design new systems from several points of view: functions, processes, decisions, resources, information technology. This paper aims at describing the long evolution of enterprise modelling techniques as well as one of the future challenges of these techniques: the transformation of enterprise models. So, in a first part, the paper describes the evolution of enterprise modelling techniques from the divergence era to the convergence period. -
H)EF3 Technical Report Version 1.0 Chard J. Mayer Christopher P
L. H)EF3 Technical Report Version 1.0 _| i L, _chard J. Mayer Christopher P. Menzel : i_:_pa_la S.D. Mayer Know!edge Based Systems Laboratory L Depar tment- 0 fin-dustrial Engineering Texas A&M University College Station TX 77843 Reviewed by Michad-K, Painter, Capt, USAF Armstrong Laboratory Logistics Research Division Wright-Patterson =Air Force Base, Ohio 45433-6503 :_ _=_January 1991 i _: ?_ | - , i (NASA-CR-I90279) {RESEARCH ACCOMPLISHED AT N92-26587 THE KNOWLEDGE BASED SYSTEMS LAB: IDEF3, VERSION 1.0] (Texas A&M Univ.) 56 p Unclag G]/_I 0086873 L == ; IDEF3 Technical Report Version 1.0 Richard J. Mayer Christopher P. Menzel Paula S.D. Mayer Knowledge Based Systems Laboratory Department of Industrial Engineering Texas A&M University College Station TX 77843 Reviewed by Michael K. Painter, Capt, USAF Armstrong Laboratory Logistics Research Division Wright-Patterson Air Force Base, Ohio 45433-6503 January 1991 umd w _- :7. m w Preface This paper describes the research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University. Funding for the Laboratory's research in Integrated Information System Development Methods and Tools has been provided by the Air Force Armstrong Laboratory, Logistics Research Division, AFWAL/LRL, Wright-Patterson Air Force Base, Ohio 45433, under the technical direction of USAF Captain Michael K. Painter, under subcontract through the NASA RICIS Program at the University of Houston. The authors and the design team wish to acknowledge the technical insights and ideas provided by Captain Painter in the performance of this research as well as his assistance in the preparation of this report. -
The IDEF Family of Languages
CHAPTER 10 The IDEF Family of Languages Christopher Menzel, Richard J. Mayer The purpose of this contribution is to serve as a clear introduction to the modeling languages of the three most widely used IDEF methods: IDEFO, IDEFIX, and IDEF3. Each language is presented in turn, beginning with a discussion of the underlying "ontology" the language purports to describe, followed by presentations of the syntax of the language - particularly the notion of a model for the language - and the semantical rules that determine how models are to be interpreted. The level of detail should be sufficient to enable the reader both to understand the intended areas of application of the languages and to read and construct simple models of each of the three types. 1 Introduction A modeling method comprises a specialized modeling language for represent ing a certain class of information, and a modeling methodology for collecting, maintaining, and using the information so represented. The focus of this paper will be on the languages of the three most widely used IDEF methods: The IDEFO business function modeling method, the IDEFIX data modeling method, and the IDEF3 process modeling method. Any usable modeling language has both a syntax and a semantics: a set of rules (often implicit) that determines the legitimate syntactic constructs of the language, and a set of rules (often implicit) the determines the meanings of those constructs. It is not the purpose of this paper is to serve as an exhaus tive reference manual for the three IDEF languages at issue. Nor will it dis cuss the methodologies that underlie the applications of the languages. -
A Framework for Enterprise Systems Engineering Processes
A Framework for Enterprise Systems Engineering Processes Dr. Robert S. Swarz Dr. Joseph K. DeRosa Tel: +1 781-271-2847 Tel: +1 781-271-3332 Email: [email protected] Email: [email protected] Fax: +1 781-271-2841 Fax: +1 781-271-3803 The MITRE Corporation 202 Burlington Road Bedford, MA 01730-1420 U.S.A. Abstract: In this paper, we describe how traditional systems engineering processes, such as those delineated in the ANSI//EIA 632 standard, are becoming inadequate for today’s complex systems, in which there is a rich set of interconnections and interrelationships between all of the systems in an enterprise. We further suggest that a new discipline (or an extension of the old discipline) is developing in response, called Enterprise Systems Engineering (ESE). We next explain some salient characteristics of complex adaptive systems and motivate how these properties, such as variation, interaction, and selection can be used to shape the evolution of the enterprise. We outline five important new processes: Technology Planning, Capability-Based Engineering Analysis, Enterprise Architecture, Strategic Technical Planning, and Enterprise Analysis and Assessment that can be used to exercise a degree of control beyond that which can be afforded by traditional means. Key words: Enterprise Systems Engineering, Evolution, Variety, Selection, Process, Enterprise Architecture, Capabilities ICSSEA 2006 Swarz & Derosa 1. INTRODUCTION In 1999, the Electronic Industries Alliance (EIA) published their Processes for Engineering a System. This has become an American National Standard (ANSI/EIA 632), and is consistent with the approach being taken by the International Standards Organization’s standard ISO 15288. In addition, the Institute of Electrical and Electronics Engineers (IEEE) standard 1220 represents an application of EIA 632 to the electronics and electrical industry. -
Analysis of Methods TECHNICAL REPORT
Analysis of Methods Final Report Richard J. Mayer, ed. Knowledge Based Systems Laboratory Texas A&M University March 8, 1991 w -o _0 co ! m f_ U cD C 0 Z 0 Cooperative Agreement NCC 9-16 Research Activity No. IM.06: Methodologies for Integrated 0 Information Management Systems r CDOC NASA Johnson Space Center Information Systems Directorate Information Technology Division -J • 0 _D A _OE e._ ,t C I LL -C,-- ::2" I C" m E Research Institute for Computing and Information Systems v;I _0 University of Houston-C/ear Lake TECHNICAL REPORT The RICIS Concept The University of Houston-Clear Lake established the Research lnsUtute for Computing and Information Systems (RICIS) in 1986 to encourage the NASA Johnson Space Center (JSC) and local industry to actively support research in the computing and information sciences. As part of thls endeavor. UHCL proposed a partnership with JSC to Jointly define and manage an integrated program of research in advanced data processing technology needed for JSC's main missions, including administrative, engineering and science responsi- bilities. JSC agreed and entered into a continuing cooperative agreement with UHCL beginning in May 1986, to Jointly plan and execute such research through RICIS. Additionally, under Cooperative Agreement NCC 9-16, computing and educaUonal facilities are shared by the two instituUons to conduct the research. The UHCL/RICIS mission is to conduct, coordinate, and disseminate research and professional level edueaUon in computing and information systems to serve the needs of the government, industry, community and academia. RICIS combines resources ofUHCLand Itsgateway affiliatestoresearch and develop materials, prototypes and publications on topics of mutual interest to its sponsors and researchers. -
Product Realization Process Modeling
NAT’L INST. OF STAND & .TECH R I.C III! Ill" I" 'I mill mill II ml II II AlllDM NISTIR 5745 Product Realization Process Modeling: A study of requirements, methods and and research issues Kevin W. Lyons U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Gaithersburg, MD 20899 Michael R. Duffey Richard C. Anderson George Washington University QC 100 NIST .056 NO. 5745 1995 Product Realization Process Modeling: A study of requirements, methods and and research issues Kevin W. Lyons U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Gaithersburg, MD 20899 Michael R. Duffey Richard C. Anderson George Washington University June 1995 c U.S. DEPARTMENT OF COMMERCE Ronald H. Brown, Secretary TECHNOLOGY ADMINISTRATION Mary L. Good, Under Secretary for Technology NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY Arati Prabhakar, Director . r•^ - . 'it'/ ' ' ' ' - ' ' -•*'1 X' . r • ^.,' v./f/v ’• '^^,. • T,?. - ^ •' V.y' ’ ' :AIa ' / ><- l> r / PRP Modeling: Page 2 1. Introduction 7 2. Definition of a PRP Model 8 3. Overview of PRP Methods and Modeling Issues in Manufacturing Industries 9 3.1 PERT-based Models 9 3.2 IDEF-based Models 10 3.3 Traditional PRP Modeling Practices 12 3.4 Emerging PRP Model Applications in Industry 14 3.5 Industry Requirements for PRP Models 14 4. Modeling Issues for Advanced PRP Computer Tools 16 4. 1 Activity Network Representations 17 4.2 Representing Design Iteration and Activity "Overlapping" 18 4.3 Uncertainty Modeling of a PRP 20 4.3.1 Some Simulation Considerations 20 4.3.2 Activity Duration Uncertainty 21 4.3.3 Concurrent Activities and Stochastic Modeling 22 4.3.4 Alternative Representations of Uncertainty 23 4.4 Representing Economic Information 24 4.5 Data Collection and Validation Issues for PRP Models 27 4.6 Knowledge-Based Representations in PRP Models 28 5. -
Enterprise Engineering Methods and Tools Which Facilitate Simulation, Emulation and Enactment Via Formal Models
15 Enterprise engineering methods and tools which facilitate simulation, emulation and enactment via formal models R.H. Weston and P.J. Gilders MSI Research Institute, Dept. ofManufacturing Engineering, Loughborough University of Technology, Loughborough, Leics, UK. Tel: +441509 222907, Fax: +441509 267725 R.H. [email protected], [email protected] Abstract In the current industrial environment of increasing competition in a globalised marketplace, businesses must strive to closely satisfy ever changing customer desires. Correspondingly, manufacturing systems need be more responsive to the evolution of business requirements and ensure that they directly support these changing demands. Enterprise modelling has contributed significantly to achieving these goals by providing a greater level of consistency between high level requirements definition and lower level system design. However, in order to be truly useful to businesses, enterprise models must be of sufficient detail and provide adequate scope to enable the models to be translated into workable business solutions. Additionally, the variety of available enterprise modelling methods and tools need to be positioned by a common framework, such that relationships between different modelling methods can be identified. This paper introduces the work carried out at the MSI Research Institute at Loughborough University which aims to provide a toolset to support the lifecycle of enterprise modelling and to support model enactment through the provision of runtime control, resource allocation and information management. Additionally, the paper provides an example application of part of the toolset and concludes by positioning the toolset within the GERAM framework for enterprise modelling. Keywords Enterprise, lifecycle, formal, systems, integration, manufacturing, modelling P.