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Generative adaptable design enabled by predictive change propagation
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AI
DOI：10.1016/j.cirp.2026.04.082.png)
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Abstract
En 中文
Adaptable design provides a systematic method to generate candidate designs under uncertain requirements and quantitatively evaluate their adaptabilities. Considering the impact of design change propagation, this paper presents a framework for generative adaptable design, in which extra design effort is formulated as information content to evaluate design adaptability. Design change propagation is modeled using a hidden Markov model, and entropy is employed to characterize propagation uncertainty and guide the generation of adaptable design strategies. A case study on nonstandard automation equipment demonstrates that the proposed approach enables the generation of adaptable design solutions with controlled design effort.
Keywords:
Adaptable design
Design change propagation
Hidden Markov model
Information content
Design strategy