Experimental study and optimisation in turning process of EN8 steel using RSM with hybrid algorithm approach. (3rd June 2019)

• Record Type: Journal Article
• Authors: Thangarasu, S.K.; Shankar, S.; Prasath, R. Navin
• Is Part Of: International journal of bio-inspired computation. Volume 13:Number 4(2019)
• Page Start: 242
• Page End: 256
• Publication Date: 2019-06-03
• Subjects: firefly algorithm -- response surface methodology -- RSM -- coated carbide inserts -- design of experiments -- swarm intelligent technique -- grey relational analysis -- cuckoo search algorithm -- PSO algorithms -- cutting force -- tool wear -- surface roughness; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

The effects of cutting speed, cutting feed, depth of cut on the output responses in turning were investigated for different tool conditions. Three-factor and three-level fractional experiment designs completed with statistical analysis of variance (ANOVA) were performed. Mathematical models for output responses were developed using response surface methodology (RSM). EN8 steel is work piece material and TiN coated cemented carbide is cutting tool. The experiments were conducted for fresh, worn out tools and the output responses are measured. The responses (cutting force, tool wear, surface roughness) are to be minimised. A quadratic model is developed along with combined optimisation of the response using RSM. For each test the output responses was measured for both tools. Finally an optimum cutting speed of 90 mm/min for fresh tool and 270 mm/min for worn out tool was obtained. The results concluded that PSO algorithm produces better optimisation compared to firefly, cuckoo search algorithms.