A multi-dimension coupling model for energy-efficiency of a machining process. (1st July 2023)

• Record Type: Journal Article
• Authors: Zhao, Junhua; Li, Li; Li, Lingling; Zhang, Yunfeng; Lin, Jiang; Cai, Wei; Sutherland, John W.
• Is Part Of: Energy. Volume 274(2023)
• Publication Date: 2023-07-01
• Subjects: Energy-efficiency -- Multi-dimension coupling -- Machining energy consumption -- Multi-objective optimization -- CNC machining; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2023.127244
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Energy-efficient machining has become imperative for energy conservation of manufacturing sectors. The energy characteristics of machining process tend to be very complex, varying substantially with respect to different configurations of machine tool, workpiece and process parameters. This paper undertakes this challenge and explores the energy consumption characteristics of machining process adaptive to different machine tools, workpieces and process parameters. A multi-dimension coupling model of energy consumption for machining process is first established by considering specifications of machine tools, workpieces and processes. Then the influence factors of energy consumption are systematically analyzed from a multi-dimensional perspective. The internal interact relationship among each dimensional parameter is illustrated. To validate the effectiveness of the proposed energy model and determine the energy-efficient machining configurations with related to machine tools, workpieces and process parameters, a series of experiments are carried out on a CNC vertical machining center. Experimental results show that the optimal machining configurations can effectively reduce energy consumption and simultaneously improve energy-efficiency of CNC machining. Highlights: A multi-dimension energy-efficiency model for machining is developed. Influence factors of energy consumption are analyzed in a multi-dimension manner. Energy-efficient machining configurations are determined by optimal experiments. The significance of the proposed approach is exemplified by machining experiments.