Amaresh Chakrabarti Innovation, Design Study and Sustainability Laboratory (IdeasLab), Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, Karnataka, India Kristina Shea Virtual Product Development Group, Mechanical Engineering, Technische Universita¨t of Mu¨nchen, Garching, Germany Computer-Based Design Robert Stone School of Mechanical, Industrial and Synthesis Research: Manufacturing Engineering, Oregon State University, Corvallis, Oregon An Overview Jonathan Cagan One of the hallmarks of engineering design is the design synthesis phase where the crea- Department of Mechanical Engineering, tivity of the designer most prominently comes into play as solutions are generated to meet Carnegie-Mellon University, underlying needs. Over the past decades, methodologies for generating concepts and Pittsburgh, PA design solutions have matured to the point that computation-based synthesis provides a means to explore a wider variety of solutions and take over more tedious design tasks. Matthew Campbell This paper reviews advances in function-based, grammar-based, and analogy-based syn- Department of Mechanical Engineering, thesis approaches and their contributions to computational design synthesis research in University of Texas at Austin, the last decade. [DOI: 10.1115/1.3593409] Austin, TX Keywords: synthesis, search, optimization, grammars, analogy, biomimetics Noe Vargas Hernandez Department of Mechanical Engineering, College of Engineering, The University of Texas at El Paso, El Paso, TX Kristin L. Wood Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 1 Introduction In this paper, three major synthesis themes are reviewed: func- tion-based synthesis, grammar-based synthesis, and analogy- Engineering design is the process of satisfying requirements by based design. Function-based synthesis focuses on developing developing and synthesizing building blocks into meaningful representations of a design problem in terms of its functions and designs that meet the requirements to fulfill needs and desires. producing solutions from functional models. Grammar-based syn- Requirements satisfaction depends both on how well requirements thesis focuses on developing formal grammars, which contain a are identified, and how well these are applied during the design design vocabulary and rules that are applied interactively or auto- process [1]. The process and resulting design are at times novel, matically by computers for transforming initial designs into a creative and innovative, and at times routine. Design synthesis is wide variety of new designs. Analogy-based design involves iden- the area of research that focuses on developing guidelines, meth- tifying analogical knowledge for solving a given design problem ods and tools for supporting creation of such solutions. Computer- and transferring this knowledge to develop solutions, with special based design synthesis is important for two reasons: it is focus on case-based design and biologically-inspired design. sometimes hard to develop novel solutions due to limitations of knowledge or fixation. Here, computers can help designers explore new directions by providing a wider variety of possibilities thereby 2 Function-Based Synthesis expanding the range of solutions that are normally considered and, possibly, improving novelty. The other difficulty is the tedium in The front end of the conceptual design process has seen few some design synthesis tasks, e.g., during routine design. In this attempts at automation, perhaps due in part to the evolving strat- case, computers can automate tasks, leaving more time for creative egies and methodologies that exist for this phase of design. How- activities, and help reduce errors, thus improving value. ever, over the past decade, several methodologies have coalesced around the functional decomposition and partial solution manipu- lation techniques originally introduced by Pahl and Beitz [2], e.g., Contributed by the CAD/Solid Modeling Committee of ASME for publication in [3–12]. These methodologies take designers through steps that the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received October 5, 2010; final manuscript received February 2, 2011; published help decompose a design problem and build conceptual solutions online June 15, 2011. Assoc. Editor: J. Shah. based on the intended, product functionality. Functional modeling Journal of Computing and Information Science in Engineering JUNE 2011, Vol. 11 / 021003-1 Copyright VC 2011 by ASME Downloaded 29 May 2012 to 128.83.63.20. Redistribution subject to ASME license or copyright; see http://www.asme.org/terms/Terms_Use.cfm methods abstract the intended functionality of a solution from cus- function-behavior-state model [46], function-environment-behavior- tomer needs, ideally removing designer biases that may be intro- structure model [47], function-behavior-component model using duced by focusing on specific solutions too early in the design Bond-graphs [48], and the more recent and comprehensive State- process. This abstraction helps designers generate more complete Action-Part-Phenomena-Input-organ-Effect (SAPPhIRE) model of conceptual solutions and balance design choices among alterna- causality [49], each with associated synthesis support. More com- tive components with the same functionality [2]. plete reviews can be found in Refs. [36, 50–56]. Research into the benefits of structured design methods (e.g., Design Knowledge Collection and Storage. Designers often de- [13]) coupled with research into designers’ reluctance to use them velop conceptual designs that draw inspiration from previous (e.g., [14,15]) seem to point toward the need for the seemingly tedi- design knowledge [57–61]. This inspiration-based approach, a ous stages of systematic design to employ some level of automation form of design by analogy, is discussed further in Sec. 4. Here, we to help integrate the benefits of a structured method with the more consider fundamental underpinnings that allow functional knowl- natural activities of a designer–a need that is most evident during edge about a product or artifact to be collected and stored to sup- the early phases of conceptual development. port knowledge reuse. Computational tools for conceptual design do exist, yet these tools The main objective of using a design repository is to facilitate often address areas that support aspects such as initial requirements storage and retrieval of design knowledge at various levels of gathering (e.g., organizational tools such as the TikiWiki project abstraction, from form to architecture to function, during the prod- [16]), the creation of function structures (e.g., the function grammar uct development process. Building on the functional basis repre- tool developed in Ref. [17]), or optimization of well-established con- sentation, a prototypical design repository–following the National cepts (e.g., [18]) rather than the translation of functional requirements Institute of Standards and Technology (NIST)-proposed format– into creative solutions. has been developed [62–64] to support design archival and reuse– essentially within-domain design by analogy. Currently, the 2.1 Fundamental Developments Supporting repository is housed within the Design Engineering Lab at Oregon Functional Synthesis State University, and contains design information for approxi- mately 150 consumer-based electro-mechanical products. The 2.1.1 Product Function Representations. Function is vari- repository currently follows the NIST schema, and identifies arti- ously described, the two convergent alternative meanings being fact-, function-, failure-, physical-, performance-, sensory-, and device-centric and environment-centric [19,20]. Functional mod- media-related information for each product in XML format [65]. eling is often considered a fundamental abstraction and a key step The variety in levels of abstraction and types of design informa- in the conceptual design process [5,21–26]. Its application allows tion provide innovative ways to approach design. Initially, artifact design problems to be quickly abstracted without the need to con- information in the repository was recorded in spreadsheets in the sider potential components, known solution principles or design form of a collection of files of bills of materials, function compo- impossibilities. Functional modeling from a constrained list of nent matrices, and design structure matrices. This information was computer parseable terms can trace its roots back to value analysis migrated to a more rigorously defined database. with the work of Miles [23] and Rodenacker [27]. This early work More recently, Oregon State has partnered with UT-Austin is expanded through the proposal of additional functions by Roth [66,67], Penn State [65], Virginia Tech, Bucknell [68], University [28], and further formalized through the Koller’s proposal of of Buffalo, Drexel [69], and Texas A&M to expand the types of twelve basic functions [29]. At a high level of abstraction, Pahl design information and breadth of design tool features within the and Beitz develop a list of five generally valid functions and three repository. The design repository serves as a hub for designers for flow types [30]. Hundal then proposes a set of six function classes information exchange and design generation tools. Information [31], but excludes the flow of information, which is re-added by entry and retrieval occurs within a standalone application [70] Little et al.,