Skip to main content
SpringerLink
Log in

Tool and Techniques for Adaptable Design

  • Chapter
  • First Online:
Adaptable Design

Part of the book series: Research on Intelligent Manufacturing ((REINMA))

  • 103 Accesses

Abstract

Modular structure allows a product to have independent function units that can be added or replaced on the product to meet requirement changes. Modularity is one of the most important features of adaptable products (APs).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. K.K. Ali, M.S. Saed, Product Design for Modularity (Kluwer Academic, Norwell, MA, USA, 2002)

    Google Scholar 

  2. J.S. Arora, Introduction to Optimum Design (McGraw-Hill, New York, NY, USA, 1989)

    Google Scholar 

  3. K. Backhaus, J. Jasper, K. Westhoff, J. Gausemeier, M. Grafe, J. Stöcklein, Virtual reality based conjoint analysis for early customer integration in industrial product development. Procedia CIRP 25, 61–68 (2014)

    Article  Google Scholar 

  4. J.C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms (Plenum, New York, NY, USA, 1981)

    Book  Google Scholar 

  5. Y. Chen, Q. Peng, P. Gu, Methods and tools for the optimal adaptable design of open-architecture products. Int. J. Adv. Manuf. Technol. 94, 991–1008 (2018). https://doi.org/10.1007/s00170-017-0925-6

  6. C. Chung, Q. Peng, The selection of tools and machines on web-based manufacturing environments. Int. J. Mach. Tools Manuf 44(2–3), 315–324 (2004)

    Google Scholar 

  7. C. Chung, Q. Peng, A hybrid approach to selective-disassembly sequence planning for de-manufacturing and its implementation on the Internet. Int. J. Adv. Manuf. Technol. 30, 521–529 (2006). https://doi.org/10.1007/s00170-005-0038-5

    Article  Google Scholar 

  8. C. Chung, Q. Peng, Enabled dynamic tasks planning in web-based virtual manufacturing environments. Comput. Industry 59, 82–85 (2008)

    Article  Google Scholar 

  9. C. Chung, Q. Peng, Tool selection-embedded optimal assembly planning in a dynamic manufacturing environment. Comput. Aided Des. 41(7), 501–512 (2009)

    Article  Google Scholar 

  10. H. Fazeli, Q. Peng, Efficient extraction of information from correlation matrix for product design using an integrated QFD-DEMATEL method. Comput.-Aided Des. Appl. 18(5), 1131–1145. https://doi.org/10.14733/cadaps.2021.1131-1145.

  11. J.K. Gershenson, G.J. Prasad, S. Allamneni, Modular product design: a life-cycle view. J. Integr. Des. Process. Sci. 3(4), 13–26 (1999)

    Google Scholar 

  12. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning (Addison-Wesley, Reading, MA, USA, 1989)

    Google Scholar 

  13. G. Hong, L. Hu, D. Xue, Y.L. Tu, Y.L. Xiong, Identification of the optimal product configuration and parameters based on individual customer requirements on performance and costs in one-of-a-kind production. Int. J. Prod. Res. 46(12), 3297–3326 (2008)

    Article  Google Scholar 

  14. X. Kang, Q. Peng, Tool feasibility analysis for fixture assembly planning. J. Manuf. Sci. Eng. Trans. ASME 130(4), 041010-1–041010-9 (2008)

    Google Scholar 

  15. X. Kang, Q. Peng, Integration of CAD models with product assembly planning in a Web-based 3D visualized environment. Int. J. Interact. Des. Manuf. 8, 121–131 (2014). https://doi.org/10.1007/s12008-014-0220-9

    Article  Google Scholar 

  16. J.R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection (The MIT Press, Cambridge, MA, USA, 1992)

    Google Scholar 

  17. M. Martinez, D. Xue, A modular design approach for modeling and optimization of adaptable products considering the whole product life-cycle spans. J. Mech. Eng. Sci. 232(7), 1146–1164 (2018)

    Article  Google Scholar 

  18. P.J. Newcomb, B. Bras, D.W. Rosen, Implications of modularity on product design for the life cycle. J. Mech. Des. 120(3), 483–490 (1998)

    Article  Google Scholar 

  19. Q. Peng, Virtual manufacturing for dynamic product development: problems and solutions, in Proceedings of the Canadian Society for Mechanical Engineering Forum 2010. June 7–9, 2010, Victoria, BC, Canada (2010)

    Google Scholar 

  20. Q. Peng, C. Chung, C. Yu, T. Luan, A networked virtual manufacturing system for SMEs. Int. J. Comput. Integr. Manuf. 20(1), 71–79 (2007)

    Article  Google Scholar 

  21. Q. Peng, F.R. Hall, P.M. Lister, Application and evaluation of VR-based CAPP system. J. Mater. Process. Technol. 107(1–3), 153–159 (2000)

    Article  Google Scholar 

  22. Q. Peng, X. Kang, T. Zhao, Effective virtual reality based building navigation using dynamic loading and path optimization. Int. J. Autom. Comput. 6(4), 335–343 (2009)

    Article  Google Scholar 

  23. Q. Peng, C. Yu, A visualised manufacturing information system for mass customisation. Int. J. Manuf. Technol. Manag. 11(3/4), 278–295 (2007)

    Article  Google Scholar 

  24. Y. Shi, Q. Peng, A spectral clustering method to improve importance rating accuracy of customer requirements in QFD. Int. J. Adv. Manuf. Technol. 107, 2579–2596 (2020). https://doi.org/10.1007/s00170-020-05204-1

    Article  Google Scholar 

  25. H. Song, F. Chen, Q. Peng, Improvement of user experience using virtual reality in open-architecture product design. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 232(13), 1–12 (2017). https://doi.org/10.1177/0954405417711736

    Article  Google Scholar 

  26. N. Suh, Axiomatic Design: Advances and Applications (Oxford University Press, New York, 2001)

    Google Scholar 

  27. H. Wang, D. Xue, An intelligent zone-based delivery scheduling approach. Comput. Industr. 48(2), 109–125 (2002)

    Article  Google Scholar 

  28. Y. Xiao, Q. Peng, Body gesture-based user interaction in design review, in Proceedings of ASME IDETC/CIE, August 06–09, DETC2017-67415 (2017)

    Google Scholar 

  29. D. Xue, A multi-level optimization approach considering product realization process alternatives and parameters for improving manufacturability. J. Manuf. Syst. 16(5), 337–351 (1997)

    Article  Google Scholar 

  30. D. Xue, J.H. Rousseau, Z. Dong, Joint optimization of performance and cost in integrated concurrent design: the tolerance synthesis part. J. Eng. Des. Autom. 2(1), 73–89 (1996)

    Google Scholar 

  31. D. Xue, H. Wang, D.H. Norrie, A fuzzy mathematics-based optimal delivery scheduling approach. Comput. Industr. 45(3), 245–259 (2001)

    Article  Google Scholar 

  32. H. Yang, D. Xue, Y.L. Tu, Modeling of the non-linear relations among different design and manufacturing evaluation measures for multi-objective optimal concurrent design. Concurr. Eng. Res. Appl. 14(1), 43–53 (2006)

    Article  Google Scholar 

  33. J. Zhang, Y. Chen, D. Xue, P. Gu, Robust design of configurations and parameters of adaptable products. Front. Mech. Eng. 9(1), 1–14 (2014)

    Article  Google Scholar 

  34. Y. Zhang, J.K. Gershenson, An initial study of direct relationships between life-cycle modularity and life-cycle cost. Concurr. Eng. Res. Appl. 11(2), 121–128 (2003)

    Article  Google Scholar 

  35. C. Zhao, Q. Peng, P. Gu, Development of a paper-bag-folding machine using open architecture for adaptability. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 229(S1), 155–169 (2015). https://doi.org/10.1177/0954405414559281

    Article  Google Scholar 

  36. L. Zhao, Q. Peng, Development of a CMM training system in virtual environments, in Proceedings of ASME IDETC/CIE, DETC2010-28274 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tianjin University, Tianjin, China

    Peihua Gu

  2. University of Calgary, Calgary, AB, Canada

    Deyi Xue

  3. University of Manitoba, Winnipeg, MB, Canada

    Qingjin Peng

  4. Shantou University, Shantou, China

    Jian Zhang

Authors
  1. Peihua Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Deyi Xue
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qingjin Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jian Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peihua Gu .

Rights and permissions

Reprints and permissions

Copyright information

© 2024 Huazhong University of Science and Technology Press

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gu, P., Xue, D., Peng, Q., Zhang, J. (2024). Tool and Techniques for Adaptable Design. In: Adaptable Design. Research on Intelligent Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-99-5869-6_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-5869-6_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-5868-9

  • Online ISBN: 978-981-99-5869-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation