Selection of cutting parameters in high-speed machining is one of the most important tasks to achieve the required level of quality. Evolutionary algorithms are often used to obtain the optimal parameters corresponding to a single value of surface finish. In most practical applications, it is necessary to determine the cutting speed, feed, and depth of cut to meet the required surface finish. In the present work, high-speed end-milling has been studied, and an objective function for surface finish is obtained by Response Surface Methodology using results of carefully designed experiments. Testing of differential evolution and genetic algorithms using the classical Himmelblau function reveals that the performance of differential evolution is better. Therefore, differential evolution is used in the present work with a newly proposed objective function, and the machining parameters for the required surface finish are obtained.

Shunmugam M S

Department of Mechanical Engineering

Function evaluation

Genetic algorithms

Milling (machining)

Parameter estimation

Surface structure

Differential evolution algorithm

END-MILLING

High-speed machining

Response surface methodology

Surface finish

Finishing

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Parameter Selection Based on Surface Finish in High-Speed End-Milling Using Differential Evolution

Materials and Manufacturing Processes

Metal cutting is an important machining operation in the manufacture of almost all engineering components. Cutting technology has undergone several changes with the development of machine tools and cutting tools to meet challenges posed by newer materials, complex shapes, product miniaturization and competitive environments. In this paper, challenges in macro and micro cutting are brought out. Conventional and micro end-milling are included as illustrative examples and details are presented along with discussion. Lengthy equations are avoided to the extent possible, as the emphasis is on the basic concepts. © 2015, The Institution of Engineers (India).

Journal of The Institution of Engineers (India): Series C

Machining Challenges: Macro to Micro Cutting

High-speed end-milling is used for production of variety of parts, dies, and molds made of hardened EN24 steel which are widely used in power and transport industries. Since desired productivity and quality are important in these industries, different strategies are needed for rough and finish end-milling operations. In this paper, a framework is presented for integrating different requirements of high-speed end-milling. In flat end-milling experiments, slots are machined in hardened EN24 steel using single insert cutter under different sets of cutting parameters for roughing and finishing operations. For rough end-milling, the responses such as material removal volume, tool wear and cutting forces are measured with respect to cutting time. A response surface is developed to predict material removal volume and a set of cutting parameters is selected for a given range of material removal volume using differential evolution (DE) algorithm till the tool wear reaches certain value. The experimental data is also used to develop Bayesian-based artificial neural network (ANN) model. Using this ANN model, reference values for cutting force and cutting time are generated for rough end-milling. Similarly, DE is used to predict a set of cutting parameters for a given range of surface roughness using response surface model. The reference cutting force is obtained for finish end-milling using ANN model. These reference values are useful in the monitoring and implementation of control strategy for the high-speed end-milling operations. © 2012 Springer-Verlag London Limited.

International Journal of Advanced Manufacturing Technology

Investigations into high-speed rough and finish end-milling of hardened EN24 steel for implementation of control strategies

This paper investigates numerical and experimental study of end milling of titanium alloy Ti–6% Al–4% V using carbide insert based cutting tool. The experiments were carried out under dry cutting conditions. The cutting speeds selected for the experiments are 20,30,40,50 mmin–1. The feed rates used in the experiment were 0.02, 0.04, 0.06 and 0.08 mmrev–1, while depth of cut is kept constant at 1.0 mm. For conducting the experiments single insert based cutting tool is based. For a range of cutting speeds and feeds measurements of cutting force, surface roughness and cutting temperature have been recorded. From the experimental study it can be seen that cutting speed has the significant effect on temperature when compared to feed/tooth. Further it is also found that cutting speed of 30 m min−1 and feed rate of 0.02 mm rev−1 could be used for machining Ti alloy. Moreover the experimental and numerical cutting force values are compared.

Volume 2A: Advanced Manufacturing

Study on Cutting Forces and Surface Finish During End Milling of Titanium Alloy

In a Computer-Aided Process Planning (CAPP) system, one of the important steps is the selection of machining parameters which yield optimum results. In this paper, a face-milling operation has been considered. The machining parameters such as number of passes, depth of cut in each pass, speed and feed are obtained using a genetic algorithm, to yield minimum total production cost while considering technological constraints such as allowable speed and feed, dimensional accuracy, surface finish, tool wear and machine tool capabilities.

International Journal of Machine Tools and Manufacture

Selection of optimal conditions in multi-pass face-milling using a genetic algorithm

Choice Reviews Online

Genetic algorithms in search, optimization, and machine learning

Encyclopedia of Biopharmaceutical Statistics

Response Surface Methodology

Evolutionary Computation

Evolutionary Algorithms for Constrained Parameter Optimization Problems

Journal of Materials Processing Technology

Application of Taguchi method in the optimization of end milling parameters

Parameter selection based on surface finish in high-speed end-milling using differential evolution

Journal	Materials and Manufacturing Processes
ISSN	10426914
Open Access	No