A multi-objective decision-making method for machining process plan and an application. (1st July 2020) - Lv, Lishu; Deng, Zhaohui; Meng, Huijuan; Liu, Tao; Wan, Linlin
Abstract: The processing parameters/plan decision of the machine tool can effectively realize the coordinated optimization of production efficiency, processing quality, resource consumption and environmental emissions. However, the current research has problems such as single decision-making objectives, high degree of subjective decision-making, and large error in decision-making results. Against this backdrop, our research proposes a multi-objective decision-making method for a machining process plan. Firstly, the resource consumption and environmental emissions of machining process are analyzed based on an input-process-output (IPO) model. Then, in view of the complex interplay between traditional indicators and environmental impact indicators, we propose a combination weight determined by an analytic hierarchy process (AHP) and the criteria importance through intercriteria correlation (CRITIC) method, which considers subjective weight and objective weight. Thirdly, we set positive and negative reference sequences using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, and the gray correlation and Euclidean distance are used for sorting each experimental group (processing parameters). Finally, an experimental case study is performed on a spindle sleeve made of GCr15, the machining type include turning, grinding, and drilling. The optimal processing parameters are determined to achieve coordinated optimization of resource consumption, processing quality, and production efficiency. Graphical abstract: Image 1060 Highlights: The combination weight determined by AHP and CRITIC, which take the subjective and objective weights into consideration. Gray correlation and Euclidean distance are used to comprehensively sort each experimental group. The relationship was established between multi-objective decision-making model and processing parameters. The method is helpful to select the best processing parameters for green machining process plan.