TY - JOUR
T1 - Evolution modeling of product families for innovative design
T2 - a dynamic network-based approach
AU - Mo, Zhenchong
AU - Cui, Haoran
AU - Huang, Jiahuan
AU - Yan, Yan
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
PY - 2025
Y1 - 2025
N2 - As market diversity and customization requirements surge, the complexity of new product development escalates, making conventional approaches inadequate. Existing research overlooks dynamic design patterns, detached from product family evolution and innovative design. Notably, characterizations of product evolution properties are absent limiting guidance for new product design decisions. Leveraging the unique capabilities of network evolution dynamics, this study introduces an innovative product family modeling approach. Furthermore, we conduct the research conducts in-depth topological analyses to identify and predict the evolutionary trends. Additionally, we present and meticulously quantify novel node evolution modes to anticipate the conceptual framework of future product generations. The efficacy of this method is rigorously verified through its case study in blender design, demonstrating its potential to bridge the gap between product family evolution and innovative design, thereby offering a new perspective for conceptual design.
AB - As market diversity and customization requirements surge, the complexity of new product development escalates, making conventional approaches inadequate. Existing research overlooks dynamic design patterns, detached from product family evolution and innovative design. Notably, characterizations of product evolution properties are absent limiting guidance for new product design decisions. Leveraging the unique capabilities of network evolution dynamics, this study introduces an innovative product family modeling approach. Furthermore, we conduct the research conducts in-depth topological analyses to identify and predict the evolutionary trends. Additionally, we present and meticulously quantify novel node evolution modes to anticipate the conceptual framework of future product generations. The efficacy of this method is rigorously verified through its case study in blender design, demonstrating its potential to bridge the gap between product family evolution and innovative design, thereby offering a new perspective for conceptual design.
KW - Data-driven modeling
KW - Decision making
KW - Network evolution dynamics
KW - Product design
KW - Product engineering
UR - https://www.scopus.com/pages/publications/105025912000
U2 - 10.1007/s10845-025-02756-5
DO - 10.1007/s10845-025-02756-5
M3 - Article
AN - SCOPUS:105025912000
SN - 0956-5515
JO - Journal of Intelligent Manufacturing
JF - Journal of Intelligent Manufacturing
ER -