Abstract
Energy-saving and emission reduction are recognized as the primary measure to tackle the problems associated with climate change, which is one of the major challenges for humanity for the forthcoming decades. Energy modeling and process parameters optimization of machining are effective and powerful ways to realize energy saving in the manufacturing industry. In order to realize high quality and low energy consumption machining of computer numerical control (CNC) lathe, a multi-objective optimization of CNC turning process parameters considering transient-steady state energy consumption is proposed. By analyzing the energy consumption characteristics in the process of machining and introducing practical constraints, such as machine tool equipment performance and tool life, a multi-objective optimization model with turning process parameters as optimization variables and high quality and low energy consumption as optimization objectives is established. The model is solved by non-dominated sorting genetic algorithm-II (NSGA-II), and the pareto optimal solution set of the model is obtained. Finally, the machining process of shaft parts is studied by CK6153i CNC lathe. The results show that 38.3% energy consumption is saved, and the surface roughness of workpiece is reduced by 47.0%, which verifies the effectiveness of the optimization method.
Highlights
As the main equipment of computer numerical control (CNC) machining, the CNC machine tool is widely used in various fields of manufacturing
The energy consumption composition characteristics of the CNC lathe machining process are analyzed, the transient process energy consumption is introduced into the energy consumption model of a CNC lathe, and the transient-steady state energy consumption model of a CNC lathe is constructed, which further improves the accuracy of the model
This paper takes energy saving in the machining process of CNC lathe as one of the optimization objectives
Summary
As the main equipment of (computer numerical control) CNC machining, the CNC machine tool is widely used in various fields of manufacturing. Yan et al [25] used cutting energy consumption, machining efficiency and surface quality as optimization models of milling process parameters and carried out optimization by gray correlation analysis and the surface response method. Li et al [26,27] carried out energy efficiency optimization for multi-step CNC planar milling process parameters, established target functions, such as energy efficiency and processing cost, and solved the multi-objective optimization model by applying the multi-objective particle swarm algorithm based on adaptive grid and continuous taboo algorithm, and obtained the optimal configuration of cutting parameters and work steps. A multi-objective optimization model is established, which takes the spindle speed, feed rate and cutting depth as the optimization variables, and the high quality and low energy consumption machining of the CNC machine tool as the optimization objective. The effectiveness and practicability of the optimization method are verified by a case study
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