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Abstract

Beside the creative activities in product development, the design process involves multiple routine tasks that are subject to automation. Techniques like knowledge-based engineering, what is commonly understood as the merging of computer-aided design, object-oriented programming and artificial intelligence, have been discussed since years, but have not yet achieved a significant breakthrough. But in particular the actual debate on digitization and artificial intelligence draws much attention on fostering new automation potentials in design of products and services. This article aims at taking an actual snapshot in which fields of application knowledge-based engineering systems and artificial intelligence are used in product development. Therefore, the authors conducted a systematic literature review, limited to scientific literature of the last five years. The literature analysis and synthesis is condensed within a concept matrix that documents actual applications and shows further research potentials.

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References

  1. Ullman, D.G.: The Mechanical Design Process, 4th edn. Mcgraw-Hill, New York (2009)

    Google Scholar 

  2. Vajna, S.: CAx für Ingenieure: eine praxisbezogene Einführung, 2nd edn. Springer, Heidelberg (2009)

    Google Scholar 

  3. Verhagen, W.J.C., Bermell-Garcia, P., van Dijk, R.E.C., Curran, R.: A critical review of Knowledge-Based Engineering: an identification or research challenges. Adv. Eng. Inform. 26(1), 5–15 (2012)

    Article  Google Scholar 

  4. Gembarski, P.C., Li, H., Lachmayer, R.: Template-based modelling of structural components. Int. J. Mech. Eng. Robot. Res. 6(5), 336–342 (2017)

    Article  Google Scholar 

  5. Chapman, C.B., Pinfold, M.: The application of a knowledge based engineering approach to the rapid design and analysis of an automotive structure. Adv. Eng. Softw. 32(12), 903–912 (2001)

    Article  MATH  Google Scholar 

  6. Milton, N.R.: Knowledge Technologies, 3rd edn. Polimetrica sas, Monza (2008)

    Google Scholar 

  7. Sabin, D., Weigel, R.: Product configuration frameworks - a survey. IEEE Intell. Syst. Appl. 13(4), 42–49 (1998)

    Article  Google Scholar 

  8. Boyle, Y., Brown, D.C.: A review and analysis of current computer-aided fixture design approaches. Robot. Comput. Integr. Manuf. 27(1), 1–12 (2011)

    Article  Google Scholar 

  9. Gembarski, P.C.: Komplexitätsmanagement mittels wissensbasiertem CAD – Ein Ansatz zum unternehmenstypologischen Management konstruktiver Lösungsräume. TEWISS, Garbsen (2018)

    Google Scholar 

  10. Schreiber, G., Wielinga, B., de Hoog, R., Akkermans, H., Van de Velde, W.: CommonKADS: a comprehensive methodology for KBS development. IEEE Expert 9(6), 28–37 (1994)

    Article  Google Scholar 

  11. Stokes, M.: Managing Engineering Knowledge: MOKA: Methodology for Knowledge Based Engineering Applications. Wiley-Blackwell, London (2001)

    Google Scholar 

  12. Barták, R., Salido, M.A., Rossi, F.: Constraint satisfaction techniques in planning and scheduling. J. Intell. Manuf. 21(1), 5–15 (2010)

    Article  Google Scholar 

  13. Felfernig, A., Hotz, L., Bagley, C., Tiihonen, J.: Knowledge-Based Configuration: From Research to Business Cases. Newnes. Morgan Kaufmann, Amsterdam (2014)

    Chapter  Google Scholar 

  14. vom Brocke, J., Simons, A., Niehaves, B., Riemer, K., Plattfaut, R., Cleven, A.: Reconstructing the giant: on the importance of rigour in documenting the literature search process. In: Proceedings of the European Conference on Information Systems (ECIS), Verona, Italy, pp. 2206–2217 (2009)

    Google Scholar 

  15. Webster, J., Watson, R.T.: Analyzing the past to prepare the future: writing a literature review. MIS Q. xiii–xxiii (2002)

    Google Scholar 

  16. Martins, T.W., Anderl, R.: Feature recognition and parameterization methods for algorithm-based product development process. In: 37th Computers and Information in Engineering Conference, pp. 1–11. The American Society of Mechanical Engineers, Cleveland (2017)

    Google Scholar 

  17. Furian, R., Von Lacroix, F., Correia, A., Faltus, S., Flores, M., Grote, K.-H.: Evaluation of a new concept of a knowledge based environment. In: The 3rd International Conference on Design Engineering and Science, Pilsen, Czech Republic, pp. 186–191 (2014)

    Google Scholar 

  18. Konrad, C., Löwer, M., Schmidt, W.: Varianzsteuerung integraler Produkte durch den Prozessbegleitenden Einsatz von Data-Mining Werkzeugen. In: Brökel, K., et al. (eds.) Gemeinsames Kolloquium Konstruktionstechnik, DuEPublico, vol. 15, pp. 213–222 (2017)

    Google Scholar 

  19. Fender, J., Duddeck, F., Zimmermann, M.: Direct computation of solution spaces. Struct. Multidiscip. Optim. 55(5), 1787–1796 (2017)

    Article  Google Scholar 

  20. Graff, L., Harbrecht, H., Zimmermann, M.: On the computation of solution spaces in high dimensions. Struct. Multidiscip. Optim. 54(4), 811–829 (2016)

    Article  MathSciNet  Google Scholar 

  21. Müller, M., Roth, M., Lindemann, U.: The hazard analysis profile: linking safety analysis and SysML. In: Annual IEEE Systems Conference, Orlando, USA, pp. 1–7 (2016)

    Google Scholar 

  22. Colombo, G., Pugliese, D., Klein, P., Lützemnberger, J.: A study for neutral format to exchange and reuse engineering knowledge in KBE applications. In: International Conference on Engineering, Technology and Innovation, Bergamo, Italien, pp. 1–10 (2014)

    Google Scholar 

  23. Chechurin, L.S., Wits, W.W., Bakker, H.M., Vaneker, T.H.J.: Introducing trimming and function ranking to solidworks based on function analysis. In: Cavallucci, D., et al. (eds.) Procedia Engineering, vol. 131, pp. 184–193. Elsevier

    Google Scholar 

  24. Luft, T., Roth, D., Binz, H., Wartzack, S.: A new “knowledge-based engineering” guideline. In: 21st International Conference on Engineering Design, Vancouver, Canada, pp. 207–216 (2017)

    Google Scholar 

  25. Oellrich, M.: Webbasierte Konstruktionsmethoden-Unterstützung in der frühen Phase der Produktentwicklung (Dissertation), Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg, Hamburg (2015)

    Google Scholar 

  26. Hjertberg, T., Stolt, R., Poorkiany, M., Johansson, J., Elgh, F.: Implementation and management of design systems for highly customized products – state of practice and future research. In: Curran, R., et al. (eds.) Transdisciplinary Lifecycle Analysis of Systems, pp. 165–174. IOS Press, Amsterdam (2015)

    Google Scholar 

  27. Relich, M., Śwíc, A., Gola, A.: A knowledge-based approach to product concept screening. In: Omatu, S., et al. (eds.) Distributed Computing and Artificial Intelligence, 12th International Conference. Advances in Intelligent Systems and Computing, vol. 373. Springer, Cham (2015)

    Chapter  Google Scholar 

  28. Gembarski, P.C., Li, H., Lachmayer, R.: KBE-modeling techniques in standard CAD-systems: case study – autodesk inventor professional. In: Proceedings of the 8th World Conference on Mass Customization, Personalization, and Co-Creation, MCPC 2015, pp. 215–233. Springer, Cham (2015)

    Google Scholar 

  29. Zhang, L.L., Chen, X., Falkner, A., Chu, C.: Open configuration: a new approach to product customization. In: Felfernig, A., Forza, C., Haag, A. (eds.) 16th International Configuration Workshop, pp. 75–79. Novi Sad, Serbia (2014)

    Google Scholar 

  30. Zeng, F., Li, B., Zheng, P., Xie, S. (S.Q.): A modularized generic product model in support of product family modeling in one-of-a-kind production. In: 2014 IEEE International Conference on Mechatronics and Automation, pp. 786–791. IEEE, Tianjin (2014)

    Google Scholar 

  31. Levandowski, C., Müller, J.R., Isaksson, O.: Modularization in concept development using functional modeling. In: Borsato, M., et al. (eds.) Transdisciplinary Engineering: Crossing Boundaries, pp. 117–126. IOS Press, Amsterdam (2016)

    Google Scholar 

  32. Borjesson, F., Hölttä-Otto, K.: A module generation algorithm for product architecture based on component interactions and strategic drivers. Res. Eng. Design 25(1), 31–51 (2014)

    Article  Google Scholar 

  33. Garg, H.: Solving structural engineering design optimization problems using an artificial bee colony algorithm. J. Ind. Manag. Optim. 10(3), 777–794 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  34. Baykasoğlu, A., Ozsoydan, F.B.: Adaptive firefly algorithm with chaos for mechanical design optimization problems. Appl. Soft Comput. 36(11), 152–164 (2015)

    Article  Google Scholar 

  35. Temple, P., Galindo, J., Jézéquel, J.-M., Acher, M.: Using machine learning to infer constraints for product lines. In: SPLC 2016 Proceedings of the 20th International Systems and Software Product Line Conference, pp. 209–218. ACM, New York (2016)

    Google Scholar 

  36. Fuge, M., Peters, B., Agogino, A.: Machine learning algorithms for recommending design methods. J. Mech. Des. 136(10), 101103 (2014)

    Article  Google Scholar 

  37. Abdeen, H., Varró, D., Sahraoui, H., Nagy, A.S., Hegedüs, Á., Horváth, Á.: Multi-objective optimization in rule-based design space exploration. In: ASE 2014 Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering, pp. 289–300. ACM, New York (2014)

    Google Scholar 

  38. Debreceni, C., Ráth, I., Varró, D., De Carlos, X., Mendialdua, X., Trujillo, S.: Automated model merge by design space exploration. In: Stevens, P., Wąsowski, A. (eds.) Fundamental Approaches to Software Engineering. Lecture Notes in Computer Science, vol. 9633. Springer, Heidelberg (2016)

    Chapter  Google Scholar 

  39. Zhu, G.N., Hu, J., Qi, J., Ma, J., Peng, Y.-H.: An integrated feature selection and cluster analysis techniques for case-based reasoning. In: Engineering Applications of Artificial Intelligence, vol. 39, pp. 14–22. Elsevier (2015)

    Google Scholar 

  40. Althuizen, N., Wierenga, B.: Supporting creative problem solving with a casebased reasoning system. J. Manag. Inf. Syst. 31(1), 309–340 (2014)

    Article  Google Scholar 

  41. Hashemi, H., Shaharoun, A.M., Sudin, I.: A case-based reasoning approach for design of machining fixture. Int. J. Adv. Manuf. Technol. 74(1–4), 113–124 (2014)

    Article  Google Scholar 

  42. Moreno, D.P., Yang, M.C., Hernández, A.A., Linsey, J.S., Wood, K.L.: A step beyond to overcome design fixation: a design-by-analogy approach. In: Gero, J.S., Hanna, S. (eds.) Design Computing and Cognition 2014, pp. 607–624. Springer, Cham (2014)

    Google Scholar 

  43. Gembarski, P.C., Bibani, M., Lachmayer, R.: Design catalogues: knowledge repositories for knowledge-based engineering applications. In: Marjanovic, D., Storga, M., Pavkovic, N., Bojcetic, N., Skec, S. (eds.) DS 84: Proceedings of the DESIGN 2016 14th International Design Conference, pp. 2007–2015. The Design Society, Dubrovnik (2016)

    Google Scholar 

  44. Brem, A., Wolfram, P.: Research and development from the bottom up - introduction of terminologies for new product development in emerging markets. J. Innov. Entrepreneurship. Syst. View Time Space 3(9), 1–22 (2014)

    Article  Google Scholar 

  45. Biskjaer, M.M., Dalsgaard, P., Halskov, K.: A constraint-based understanding of design spaces. In: DIS 2014 Proceedings of the 2014 Conference on Designing Interactive Systems, pp. 453–462. ACM, New York (2014)

    Google Scholar 

  46. Münzer, C.: Constraint-based methods for automated computational design synthesis of solution spaces (Dissertation). ETH Zürich, Zürich, Switzerland (2015)

    Google Scholar 

  47. Wang, Q., Yu, X.: Ontology based automatic feature recognition framework. Comput. Ind. 65(7), 1041–1052 (2014)

    Article  Google Scholar 

  48. Yu, R., Gu, N., Ostwald, M., Gero, J.S.: Empirical support for problem–solution coevolution in a parametric design environment. Artif. Intell. Eng. Des. Anal. Manuf. 29(1), 33–44 (2015)

    Article  Google Scholar 

  49. Pan, Z., Wang, X., Teng, R., Cao, X.: Computer-aided design-while-engineering technology in top-down modeling of mechanical product. Comput. Ind. 75, 151–161 (2016)

    Article  Google Scholar 

  50. Trehan, V., Chapman, C., Raju, P.: Informal and formal modelling of engineering processes for design automation using knowledge based engineering. J. Zhejiang Univ. Sci. A 16(9), 706–723 (2015)

    Article  Google Scholar 

  51. Hagenreiner, T., Köhler, P.: Concept development of design driven parts regarding multidisciplinary design optimization. Comput. Aided Des. Appl. 12(2), 208–217 (2015)

    Article  Google Scholar 

  52. Relich, M.: A computational intelligence approach to predicting new product success. In: Proceedings of the 11th International Conference on Strategic Management and its Support by Information Systems, pp. 142–150 (2015)

    Google Scholar 

  53. Hu, J., Qi, J., Peng, Y.: New CBR adaptation method combining with problem–solution relational analysis for mechanical design. Comput. Ind. 66, 41–51 (2015)

    Article  Google Scholar 

  54. Chen, Y., Liu, Z.-L., Xie, Y.-B.: A multi-agent-based approach for conceptual design synthesis of multi-disciplinary systems. Int. J. Prod. Res. 52(6), 1681–1694 (2014)

    Article  Google Scholar 

  55. Fougères, A.-J., Ostrosi, E.: Intelligent agents for feature modelling in computer aided design. J. Comput. Des. Eng. 5(1), 19–40 (2018)

    Google Scholar 

  56. Siqueira, R., Bibani, M., Duran, D., Mozgova, I., Lachmayer, R., Behrens, B.-A.: An adapted case-based reasoning system for design and manufacturing of tailored forming multi-material components. Int. J. Interact. Des. Manuf. (IJIDeM), 1–10 (2019)

    Google Scholar 

  57. Gembarski, P.C., Sauthoff, B., Brockmöller, T., Lachmayer, R.: Operationalization of manufacturing restrictions for CAD and KBE-systems. In: Marjanovic, D., et al. (eds.) DS 84: Proceedings of the DESIGN 2016 14th International Design Conference, pp. 621–630. The Design Society, Dubrovnik (2016)

    Google Scholar 

  58. Brockmöller, T., Gembarski, P.C., Mozgova, I., Lachmayer, R.: Design catalogue in a CAE environment for the illustration of tailored forming. In: Engineering for a Changing World, vol. 59. ilmedia, Ilmenau (2017)

    Google Scholar 

  59. Bibani, M., Gembarski, P.C., Lachmayer, R.: Ein wissensbasiertes System zur Konstruktion von Staubabscheidern. In: Krause, D. et al. (eds.) Proceedings of the 28th Symposium Design for X, pp. 165–176. The Design Society, Bamberg (2017)

    Google Scholar 

  60. VDI: VDI Guideline 2221 - Systematic approach to the development and design of technical systems and products, Beuth, Berlin (1993)

    Google Scholar 

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Plappert, S., Gembarski, P.C., Lachmayer, R. (2020). The Use of Knowledge-Based Engineering Systems and Artificial Intelligence in Product Development: A Snapshot. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019. ISAT 2019. Advances in Intelligent Systems and Computing, vol 1051. Springer, Cham. https://doi.org/10.1007/978-3-030-30604-5_6

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