Abstract
Purpose
Glass is a brittle material produced from silica, which has fine material properties, Owing to its sophisticated material properties, glass has found wide application in various high-technological fields such as aviation, aerospace, communication, optics, biomedical and electronics. However, glass is known as difficult to machine material because of its tendency to brittle fracture during machining. This paper aims to investigate the effects of cutting parameters on surface quality and machining time during micro-milling of brittle glass components.
Design/methodology/approach
A comprehensive genetic algorithm-based optimization strategy is used for selection of process parameters such as cutting speed, feed rate and depth of cut. Effectiveness of the proposed strategy is validated by conducting micro-milling cutting experiments on soda-lime glass material.
Findings
Results showed that the generated surface quality drastically decrease with increase in the amount of removed material. Lower depth of cut and feed rate result in less amount of cracks formed on machined surface. Also, it is observed that the increase in cutting speed results in better surface quality. Having desired surface quality in shorter machining time directly reduces energy consumed during manufacturing, which is reducing environmental impact of glass parts.
Originality/value
The novelty of this research work lies in simultaneously considering the effects of cutting speed, feed rate, depth of cut on surface quality and machining time for micro-milling operation of brittle glass material. The model is able to find optimum process parameters for high surface quality and minimum machining time.