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Customized product design information feedback technology based on tentative design chain reconstruction

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Abstract

The design process of customized products involves dynamic feedback on customer requirements, design alterations, design knowledge, and other information. Current technologies for designing customized products focus on implementing product functions, but are short of effective support for design information feedback. The paper introduces a feedback technology of customized product design information based on tentative design chain reconstruction, whereby a tentative design chain and a corresponding design assignment matrix (DAM) are built in accordance with the logical relationship between the design assignments of the customized product. The tentative design chain is reconstructed through matrix decomposition to optimize the implementation path of the design assignments. Based on the reciprocal relationship between information transfer and feedback path for the design of a customized product, the feedback path of the customized product design information is extracted. The implementation method for feedback are put forward so that the design strategy of the customized product can be adjusted promptly with the feedback information between assignments. The feedback technology of the customized product design information based on the tentative design chain reconstruction is verified by application in the design of the elevator traction sheave. The results show that it helps to reduce the degree of the cross correlation between design assignments, and simplifies the design process of the elevator traction wheel.

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Abbreviations

m i (i = 1,2, … n):

Node i of the tentative design chain of the customized product, where n is the total number of the nodes

arc i (i = 1,2 …, m):

Transfer path i of design information from node mx to node my, where m is the total number of the transfer paths

q xy :

Coupling intensity of design information from node mx to node my

DAM n×m :

DAM

DAM′ :

Reconstructed DAM

DAM″ :

Transposed matrix of DAM′

M :

Coupled design assignment block matrix

m ij (i ≠ j, j ≤ n):

Element of DAM

CII :

Coupling intensity indicator

CII i :

Mean coupling between design assignments of the set of the coupled design assignments

CII o :

Mean coupling between design assignments of the set of the coupled design assignment with all external design assignments

w ij :

Coupling intensity between coupled design assignments

r :

Row (column) of the first design assignment of the coupled design assignment set in the DAM

s :

Row (column) of the last design assignment of the coupled design assignment set in the DAM

n cii :

Total number of the design assignments

Q i :

Structural sensitivity

MI i :

Association strength between the inputs of the i-th design assignment

MO i :

Association strength between the outputs of the i-th design assignment

f c :

Feedback process function between design assignments

(x i)c :

Change information of the previous design assignment xi

y c :

Change information of the current design assignment y

D i :

Set of design information

(D i)c :

Set of design alteration information

IN i :

Number of paths for design information input

V i :

Visit times of the design information

TI i :

Coupling intensity of input design information of each design assignment in the block matrix of the DAM

TO i :

Coupling intensity of output design information of each design assignment in the block matrix of the DAM

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Acknowledgments

This research was funded by the National Natural Science Foundation of China (Grant No. 51875516 and No. 51905476), the Public Welfare Technology Application Projects of Zhejiang Province, China (Grant No.LGG22E050008), the Key Scientific and Technological Projects Keqiao District Shaoxing City of China (2021JBGS205).

Author information

Authors and Affiliations

  1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China

    Lemiao Qiu, Huifang Zhou, Zili Wang, Yiming Zhang, Shuyou Zhang & Longwu Pan

  2. Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province, Zhejiang University, Hangzhou, 310027, China

    Lemiao Qiu, Zili Wang, Yiming Zhang & Shuyou Zhang

Authors
  1. Lemiao Qiu
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  2. Huifang Zhou
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  3. Zili Wang
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Corresponding author

Correspondence to Zili Wang.

Additional information

Lemiao Qiu received his Ph.D. degree in Mechanical Engineering in State Key Lab. of CAD&CG from Zhejiang University, China, in 2008. He is currently an Associate Professor in the Department of Mechanical Engineering, Zhejiang University, China. His research interests include product digital design, manufacturing informatization, design and stimulation for complex equipment.

Huifang Zhou received the B.S. degree in School of Mechanical Engineering from Shandong University, China, in 2017. She is currently a Ph.D. candidate in the School of Mechanical Engineering, Zhejiang University, China. Her research interests include engineering optimization, product configuration design and machine learning algorithms.

Zili Wang is currently a Research Associate at the Department of Mechanical Engineering, Zhejiang University, Hangzhou, China. He received the Ph.D. degree from the Department of Mechanical Engineering, Zhejiang University, Hangzhou, China, in 2018. His research interests include computer-aided design, intelligent manufacturing, digital-twin-based design, and designing optimization.

Yiming Zhang is an Assistant Professor with the Department of Mechanical Engineering at Zhejiang University (ZJU). His research focuses on engineering optimization and decision making under uncertainty. Prior joining ZJU in 2021, he has been working at GE Research Center as a lead engineer since 2018. He obtained Ph.D. from the University of Florida in 2018. He has 30+ publications and been serving on multiple technical committees including AIAA non-deterministic approaches, DOE America Makes. He has been chairing multiple AIAA conference sessions on surrogate, optimization and uncertainty quantification.

Shuyou Zhang was born in Zhejiang, China in 1963. He received his M.S. degree in Department of Mechanical Engineering from Zhejiang University in 1991, the Ph.D. degree in State Key Lab. of CAD&CG from Zhejiang University in 1999. He is currently a Professor in Zhejiang University and an Assistant Director of Computer Graphics Professional Committee for China Engineering Graphic Society. His research search areas and descriptors include technology of product digital design, technology of design and stimulation for complex equipments, engineering and computer graphics and key technology for enterprise informatization.

Longwu Pan received his M.S. degree in Mechanical Engineering in State Key Lab. of CAD&CG from Zhejiang University, China, in 2019. His research interests include product digital design, manufacturing informatization, design and stimulation for complex equipment.

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Qiu, L., Zhou, H., Wang, Z. et al. Customized product design information feedback technology based on tentative design chain reconstruction. J Mech Sci Technol 36, 6123–6133 (2022). https://doi.org/10.1007/s12206-022-1127-1

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  • DOI: https://doi.org/10.1007/s12206-022-1127-1

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