Research on intelligent expert system of green cutting process and its application. (1st June 2018) - Deng, Zhaohui; Zhang, Hua; Fu, Yahui; Wan, Linlin; Lv, Lishu
Abstract: Due to the urgent need for more flexible and intelligent response to rapid changing customer demand in highly competitive market environment, intelligent optimization of the cutting process parameters based on the cutting process cases were researched, and an expert system (ES) of the green cutting process technology was constructed. Its processor was performed by hybrid reasoning method of cases and rules while part model and process model of the workpiece to be manufactured were carried out. The mathematical model of machine tool energy consumption was given using response surface methodology (RSM) based on experimental data collected from the machining tool manufacturing enterprise. Based on the case library, the basic database, the model library and the rule library, the part model and the process model of the typical machine tool parts were established, thus those formed a knowledge base. The cutting process technology of the head spindle on certain machine tool was optimized as one instance, the process of similar calculation and the optimization procedure was given. The optimization process technology was verified, and it proved the feasibility and applicability of the ES. Those provided one optimization plan and program of green processing technology for the sustainable manufacturing enterprises. The ES of the green cutting process technology could help the technologist of enterprises more rapidly respond to the demands of customers in highly competitive market environment and relieve the impact to the environment. Graphical abstract: Image Highlights: Empiric power functions were obtained, compiled by Matlab and be stored for call The optimization was performed by GRA and CRITIC with QGA based on knowledge base. The ES was constructed and help the technologist plan rapidly green process technology. An optimization program was proposed and applied to achieve sustainable processing.