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<p>To address the collaborative requirements of grinding-cutting processes in in situ integrated machining of large-scale rigid complex components, this study proposes a reconfigurable parallel mechanism with modal-switching capability and a multi-objective cooperative optimization methodology. An integrated kinematic model incorporating both cutting (1T2R) and grinding (2T1R) modes is established through the finite instantaneous screw (FIS) theory, formulating a six-dimensional performance evaluation system encompassing workspace accessibility and virtual power transmission efficiency. A high-precision surrogate model relating design parameters to performance metrics is developed using a global parameter normalization strategy combined with optimal Latin hypercube sampling (Opt LHS) and response surface methodology(RSM), effectively resolving weight deviation issues caused by dimensional heterogeneity in multi-objective optimization. The improved multi-objective particle swarm optimization algorithm generates Pareto front solution sets, with the minimum distance selection criterion identifying optimal parameter configurations balancing dual-mode performance. Experimental validation demonstrates 70.66% workspace expansion in cutting mode, 19.89% maximum load capacity enhancement in grinding mode, and 3.27% reduction in modal transition stability fluctuation. Prototype development based on optimized parameters confirms method feasibility, providing theoretical foundations for multifunctional machining innovations in advanced manufacturing equipment.</p>

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Multi-objective optimization design of reconfigurable parallel mechanism for integrated machining of heavy-duty components

  • 期刊论文

  • 发表日期：

    2025年9月2日

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  • Hong Wang,
  • Yang Qi,
  • Xinqi Tao,
  • Shan Yu

摘要

To address the collaborative requirements of grinding-cutting processes in in situ integrated machining of large-scale rigid complex components, this study proposes a reconfigurable parallel mechanism with modal-switching capability and a multi-objective cooperative optimization methodology. An integrated kinematic model incorporating both cutting (1T2R) and grinding (2T1R) modes is established through the finite instantaneous screw (FIS) theory, formulating a six-dimensional performance evaluation system encompassing workspace accessibility and virtual power transmission efficiency. A high-precision surrogate model relating design parameters to performance metrics is developed using a global parameter normalization strategy combined with optimal Latin hypercube sampling (Opt LHS) and response surface methodology(RSM), effectively resolving weight deviation issues caused by dimensional heterogeneity in multi-objective optimization. The improved multi-objective particle swarm optimization algorithm generates Pareto front solution sets, with the minimum distance selection criterion identifying optimal parameter configurations balancing dual-mode performance. Experimental validation demonstrates 70.66% workspace expansion in cutting mode, 19.89% maximum load capacity enhancement in grinding mode, and 3.27% reduction in modal transition stability fluctuation. Prototype development based on optimized parameters confirms method feasibility, providing theoretical foundations for multifunctional machining innovations in advanced manufacturing equipment.