Abstract
This exploration is carried out to reveal the outcome of turning factors such as cutting velocity, depth of cut and feed rate on the surface roughness, mean cutting force and tool-work interface temperature on turning cylindrical 655M13 steel alloy components. The experiments are designed based on (33) full factorial design and conducted on a turning centre with Titanium Aluminium Nitride (TiAlN) layered carbide tool of 0.8mm nose radius, simultaneously cutting forces such as feed force, thrust force and tangential force and the tool-work interface temperature are observed using calibrated devices. The surface roughness of the turned steel alloy parts is deliberated by means of a precise surface roughness apparatus. Prediction models are created for average surface roughness, mean cutting force and tool-work interface temperature by nonlinear regression examination with the aid of MINITAB numerical software. The optimum machining conditions are confirmed with the aid of a Genetic Algorithm. The outcome of each turning factor on the surface roughness, mean cutting force and tool-work interface temperature is studied and presented accordingly.
Highlights
The achievement of high quality, in terms of workpiece dimensional accuracy, surface finish, high production rate, less wear on the cutting tools, economy of machining in terms of cost-saving and to increase the performance of the product with reduced environmental impact are the main and effective challenges of modern metal cutting and machining industries (Sharma et al, 2016; Selvam et al, 2016; Krolczyk et al, 2017)
Titanium Aluminium Nitride (TiAlN) is a very fashionable coating applied to the carbide cutting tool insert because TiN acquires some useful properties such as elevated hardness, elevated strength, elevated chemical stability, tremendous resistance to Built-Up Edge formation, little coefficient of friction
While machining steel alloys TiAlN coated carbide tool inserts could be applied at higher feed rates and cutting velocities (Khorasani et al, 2016; Selvam et al, 2016)
Summary
The achievement of high quality, in terms of workpiece dimensional accuracy, surface finish, high production rate, less wear on the cutting tools, economy of machining in terms of cost-saving and to increase the performance of the product with reduced environmental impact are the main and effective challenges of modern metal cutting and machining industries (Sharma et al, 2016; Selvam et al, 2016; Krolczyk et al, 2017). Many researchers and practitioners adapted Design of Experiment (DoE) technique for planning the experiments in the turning of medium carbon steel alloy, few were discussed in the below section; Yang et al, (2017) investigated the processing factors in turning and created a predictor for surface roughness using DoE. Their experimentation reveals the feed was the most prominent factor in roughness, trail by cutting speed. The examination of machining is completed by making utilization of the demonstrated test plan method
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