An Integrated Decision-Making Method of Flexible Process Plan and Cutting Parameter Considering Dynamic Machining Resources

The integration of flexible process planning and cutting parameter optimization is of great significance to reduce energy consumption and shorten production time. Flexible manufacturing system brings great uncertainty to the flexible process planning and cutting parameter optimization. Most studies are conducted in a static manufacturing environment and lack of adaptive capacity to the uncertainty of the machining resources. To this end, an integrated decision-making method of flexible process plan and cutting parameter is proposed to improve energy efficiency. Specifically, the improved AND/OR network graph is employed to describe various types of process flexibility. Secondly, the coupling characteristics between energy consumption and machining resources, cutting parameters, and operation sequences are analyzed. Then, a Markov Decision Process is utilized to simulate the dynamic generation process of flexible process plans and cutting parameters, and the integrated decision-making method considering dynamic machining resources is designed with actor-critic framework. Finally, extensive comparative experiments are carried out to verify the validity of the proposed method. Experimental results indicate that: 1) the proposed method can determine flexible process plans and cutting parameters to adapt to the dynamics of machining resources. 2) The integrated optimization method reduces <inline-formula> <tex-math notation="LaTeX">$E_{total} $</tex-math> </inline-formula> and <inline-formula> <tex-math notation="LaTeX">$T_{p}$</tex-math> </inline-formula> by 3.59% and 3.45% compared to the two-stage optimization method <italic>Note to Practitioners</italic>&#x2014;Decision making of flexible process plans and cutting parameters relies on machining resources in the machining process. Dynamic changes in machining resources make the energy-aware decision of the flexible process plans and cutting parameters a challenging problem. To the best of our knowledge, this paper develops an integrated method of flexible process planning and cutting parameter optimization considering dynamic machining resources that can adapt to the change of machining resources. It may assist decision-makers to provide more practical flexible process plans and cutting parameters based on dynamic machining resources in the machining process.