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Extension Design Pattern of Requirement Analysis for Complex Mechanical Products Scheme Design

Author

Listed:
  • Tichun Wang

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Hao Li

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Xianwei Wang

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

Due to the configuration process of a complex product scheme, a design structure often has the characteristics of multi-level, multi-attribute, creativity, and complexity; in order to improve the efficiency and quality of product scheme design, it has important research value to reasonably organize, reason, and reuse design knowledge. In this paper, the extension modeling problem under the extension design mode of complex product scheme is studied, the multitype design knowledge element modeling expression model of complex product scheme design is given, and the extension process model and the implication process model of requirement analysis of complex product scheme design is established. A new demand element weight assignment method based on extension distance is proposed to obtain accurate demand analysis index weight from the perspective of combined qualitative and quantitative analysis. On the basis of constructing the extension correlation degree of demand primitives, this paper puts forward the implementation method of the extension design pattern for the demand analysis of a complex product scheme design and gives the specific implementation algorithm. Finally, an example of product design is given to illustrate the method, and the results show the effectiveness and operability of the method.

Suggested Citation

  • Tichun Wang & Hao Li & Xianwei Wang, 2022. "Extension Design Pattern of Requirement Analysis for Complex Mechanical Products Scheme Design," Mathematics, MDPI, vol. 10(17), pages 1-19, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:17:p:3132-:d:903578
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    References listed on IDEAS

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    1. Yiyun Tao & Kai Meng & Peihuang Lou & Xianghui Peng & Xiaoming Qian, 2019. "Joint decision-making on automated disassembly system scheme selection and recovery route assignment using multi-objective meta-heuristic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 57(1), pages 124-142, January.
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    Cited by:

    1. Weihua Ou & Jianping Gou & Shaoning Zeng & Lan Du, 2023. "Preface to the Special Issue “Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics”—Special Issue Book," Mathematics, MDPI, vol. 11(4), pages 1-4, February.

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