Abstract
Optimization design of product structures is a critical point of intelligent manufacturing that is often overlooked, particularly their performance balance involving different uncertainties. It is urgent to connect product consumers, design experts, and manufacturing plants to balance the optimization of product structures. As an input of intelligent manufacturing, an industrial network based on software-defined networking (SND) for product optimization design including structure performance balance is established in this study, which breaks down the barriers between an industrial network and the performance balance optimization of product structures. Accordingly, the high-dimensional coupling clustering of product components is performed through a two-dimensional (2D) plane mapping with a design structure matrix (DSM) that aims at the entire product life cycle (PLC). A random chance-constrained programming model for the performance balance optimization of product structures is developed, where the fuzzy expert evaluation is considered to include heterogeneous uncertainties, and an integrated multi-objective discrete cuckoo algorithm nested with Monte Carlo simulation is designed to solve the model. The rationality and superiority of the proposed method are verified using a case study with a large hydraulic machine tool for sheet stamping where product modules with better comprehensive performance are generated.
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