Multi-index cutting parameters optimization for surface quality and cutting energy consumption of boring

Abstract

Saving energy is one of the ways to achieve sustainable development. As an important equipment for manufacturing, machine tool has the characteristics of high energy consumption and high emission. In order to cope with reducing energy consumption and carbon emissions without reducing processing quality, the search for optimal cutting parameters requires balancing the contradiction between machining quality and cutting energy consumption, so that cutting parameters can both reduce energy consumption and ensure the quality of processing. It plays an important role in achieving energy saving and emission reduction. In this paper, the processing quality (residual stress, surface roughness) and cutting energy consumption are selected as the optimized multiple indicators, and the selected optimization indicators are analyzed. Weighted grey correlation analysis is used to obtain the multi-index gray correlation degree value, and the multi-index weight coefficient is determined. Based on weighted grey correlation analysis and multi-index orthogonal optimization method, the cutting parameters of the boring process are optimized, and the optimal parameter combination is that cutting depth of 0.05 mm, cutting speed of 120 m/min, and feed rate of 80 mm/min