Challenges in the industrial implementation of generative design systems: An exploratory study

Abstract The aim of this paper is to investigate the challenges associated with the industrial implementation of generative design systems. Though many studies have been aimed at validating either the technical feasibility or the usefulness of generative design systems, there is, however, a lack of research on the practical implementation and adaptation in industry. To that end, this paper presents two case studies conducted while developing design systems for industrial uses. The first case study focuses on an engineering design application and the other on an industrial design application. In both cases, the focus is on detail-oriented performance-driven generative design systems based on currently available computer-assisted design tools. The development time and communications with the companies were analyzed to identify challenges in the two projects. Overall, the results show that the challenges are not related to whether the design tools are intended for artistic or technical problems, but rather in how to make the design process systematic. The challenges include aspects such as how to fully utilize the potential of generative design tools in a traditional product development process, how to enable designers not familiar with programming to provide design generation logic, and what should be automated and what is better left as a manual task. The paper suggests several strategies for dealing with the identified challenges.

[1]  K. Krippendorff.  Bivariate Agreement Coefficients for Reliability of Data , 1970 .

[2]  Jay McCormack,et al.  Speaking the Buick Language: Capturing, Understanding, and Exploring Brand Identity With Shape Grammars , 2004 .

[3]  Jonathan Cagan,et al.  Capturing a rebel: modeling the Harley-Davidson brand through a motorcycle shape grammar , 2002 .

[4]  Adrian Thompson,et al.  An Evolved Circuit, Intrinsic in Silicon, Entwined with Physics , 1996, ICES.

[5]  Damien Motte,et al.  Strategies for consumer control of complex product forms in generative design systems , 2013, DAC 2013.

[6]  John H. Frazer,et al.  Creative design and the generative evolutionary paradigm , 2001 .

[7]  G. Stiny.  Introduction to Shape and Shape Grammars , 1980 .

[8]  Karl T. Ulrich,et al.  Product Design and Development , 1995 .

[9]  Aristid Lindenmayer,et al.  Mathematical Models for Cellular Interactions in Development , 1968 .

[10]  Sivam Krish,et al.  A practical generative design method , 2011, Comput. Aided Des..

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Jonathan Cagan,et al.  A Blend of Different Tastes: The Language of Coffeemakers , 1998 .

[13]  Jonathan Cagan,et al.  A Framework for Computational Design Synthesis: Model and Applications , 2005, J. Comput. Inf. Sci. Eng..

[14]  Imre Horváth,et al.  On some Crucial Issues of Computer Support of Conceptual Design , 2004 .

[15]  Patrick Janssen,et al.  Dexen: A scalable and extensible platform for experimenting with population-based design exploration algorithms , 2015, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[16]  Erik Stolterman,et al.  Design research at CHI and its applicability to design practice , 2013, CHI.

[17]  Malgorzata A. Zboinska.  Hybrid CAD/E platform supporting exploratory architectural design , 2015, Comput. Aided Des..

[18]  Damien Motte,et al.  Complex Product Form Generation in Industrial Design: A Bookshelf Based on Voronoi Diagrams , 2010, DCC.

[19]  Kristina Shea,et al.  Towards integrated performance-driven generative design tools , 2004 .

[20]  Jordan B. Pollack,et al.  Evolution of generative design systems for modular physical robots , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[21]  Donald E. Knuth,et al.  The Metafont book , 1989 .

[22]  K. Eisenhardt.  Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[23]  C. Brodsky.  The Discovery of Grounded Theory: Strategies for Qualitative Research , 1968 .

[24]  Hsiu-Fang Hsieh,et al.  Three Approaches to Qualitative Content Analysis , 2005, Qualitative health research.

[25]  Deen Freelon.  ReCal: Intercoder Reliability Calculation as a Web Service , 2010 .

[26]  David G. Ullman,et al.  The Mechanical Design Process , 1992 .

[27]  Ning Gu,et al.  Towards an integrated generative design framework , 2012 .

[28]  Hau Hing Chau,et al.  EVALUATION OF A 3D SHAPE GRAMMAR IMPLEMENTATION , 2004 .

[29]  Peter J. Bentley,et al.  Introduction to creative evolutionary systems , 2001 .

[30]  Sharan B. Merriam,et al.  Qualitative research and case study applications in education , 1998 .

[31]  Bernard Yannou,et al.  Using evolutionary design to interactively sketch car silhouettes and stimulate designer's creativity , 2012, Eng. Appl. Artif. Intell..

[32]  Rudi Stouffs,et al.  Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms , 2011, Adv. Eng. Informatics.

[33]  Ron Wakkary,et al.  Understanding interaction design practices , 2011, CHI.

[34]  Jonathan Cagan,et al.  Influencing generative design through continuous evaluation: Associating costs with the coffeemaker shape grammar , 1999, Artif. Intell. Eng. Des. Anal. Manuf..

[35]  Doru Talabă,et al.  Product engineering : eco-design, technologies and green energy , 2004 .

[36]  Stephen Wolfram,et al.  A New Kind of Science , 2003, Artificial Life.

[37]  Patrick Janssen,et al.  A generative evolutionary design method , 2006, Digit. Creativity.

[38]  Rivka Oxman,et al.  Theory and design in the first digital age , 2006 .

[39]  Wolfgang Beitz,et al.  Engineering Design: A Systematic Approach , 1984 .

[40]  M. Eriksson.  Fundamentals of a Methodology for Predictive Design Analysis , 2015 .

[41]  M. Lombard,et al.  Content Analysis in Mass Communication: Assessment and Reporting of Intercoder Reliability , 2002 .

[42]  Herbert A. Simon,et al.  The Structure of Ill Structured Problems , 1973, Artif. Intell..

[43]  A. Strauss,et al.  The discovery of grounded theory: strategies for qualitative research aldine de gruyter , 1968 .

[44]  Lucienne Blessing,et al.  DRM, a Design Research Methodology , 2009 .

[45]  Karl Sims,et al.  Artificial evolution for computer graphics , 1991, SIGGRAPH.

[46]  Achim Menges,et al.  Evolutionary structural and spatial adaptation of topologically differentiated tensile systems in architectural design , 2015, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[47]  Peter J. Bentley,et al.  CREATIVE EVOLUTIONARY SYSTEMS , 2001 .

[48]  Robert Bjärnemo,et al.  An Approach to Constraint-Based and Mass-Customizable Product Design , 2011, J. Comput. Inf. Sci. Eng..

[49]  T Weissman Knight,et al.  The Generation of Hepplewhite-Style Chair-Back Designs , 1980 .

[50]  A. Lindenmayer.  Mathematical models for cellular interactions in development. I. Filaments with one-sided inputs. , 1968, Journal of theoretical biology.

[51]  Enrico Rigoni,et al.  MOGA-II PERFORMANCE ON NOISY OPTIMIZATION PROBLEMS , 2004 .

[52]  K. Krippendorff.  Reliability in Content Analysis: Some Common Misconceptions and Recommendations , 2004 .