PARAMETRIC ANALYSIS AND MULTI OBJECTIVE OPTIMIZATION OF CUTTING PARAMETERS IN TURNING OPERATION OF AISI 4340 ALLOY STEEL WITH CVD CUTTING TOOL

Energy conservation and emission reduction is an essential consideration in sustainable manufacturing. However, the traditional optimization of cutting parameters mostly focuses on machining cost, surface quality, and cutting force, ignoring the influence of cutting parameters on energy consumption in cutting process. This paper presents a multi-objective optimization method of cutting parameters based on grey relational analysis and response surface methodology (RSM), which is applied to turn AISI 304 austenitic stainless steel in order to improve cutting quality and production rate while reducing energy consumption. Firstly, Taguchi method was used to design the turning experiments. Secondly, the multi-objective optimization problem was converted into a simple objective optimization problem through grey relational analysis. Finally, the regression model based on RSM for grey relational grade was developed and the optimal combination of turning parameters (ap = 2.2 mm, f = 0.15 mm/rev, and v = 90 m/s) was determined. Compared with the initial turning parameters, surface roughness (Ra) decreases 66.90%, material removal rate (MRR) increases 8.82%, and specific energy consumption (SEC) simultaneously decreases 81.46%. As such, the proposed optimization method realizes the trade-offs between cutting quality, production rate and energy consumption, and may provide useful guides on turning parameters formulation.

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Multi-Objective Optimization of Turning Operation of Stainless Steel Using a Hybrid Whale Optimization Algorithm

Journal of Manufacturing and Materials Processing ◽

10.3390/jmmp4030064 ◽

2020 ◽

Vol 4 (3) ◽

pp. 64 ◽

Cited By ~ 2

Author(s):

Mahamudul Hasan Tanvir ◽

Afzal Hussain ◽

M. M. Towfiqur Rahman ◽

Sakib Ishraq ◽

Khandoker Zishan ◽

...

Keyword(s):

Surface Roughness ◽

Stainless Steel ◽

Optimization Algorithm ◽

Cutting Parameters ◽

Whale Optimization Algorithm ◽

Multi Objective Optimization ◽

Turning Operation ◽

Multi Objective ◽

Whale Optimization ◽

Optimum Cutting

In manufacturing industries, selecting the appropriate cutting parameters is essential to improve the product quality. As a result, the applications of optimization techniques in metal cutting processes is vital for a quality product. Due to the complex nature of the machining processes, single objective optimization approaches have limitations, since several different and contradictory objectives must be simultaneously optimized. Multi-objective optimization method is introduced to find the optimum cutting parameters to avoid this dilemma. The main objective of this paper is to develop a multi-objective optimization algorithm using the hybrid Whale Optimization Algorithm (WOA). In order to perform the multi-objective optimization, grey analysis is integrated with the WOA algorithm. In this paper, Stainless Steel 304 is utilized for turning operation to study the effect of machining parameters such as cutting speed, feed rate and depth of cut on surface roughness, cutting forces, power, peak tool temperature, material removal rate and heat rate. The output parameters are obtained through series of simulations and experiments. Then by using this hybrid optimization algorithm the optimum machining conditions for turning operation is achieved by considering unit cost and quality of production. It is also found that with the change of output parameter weightage, the optimum cutting condition varies. In addition to that, the effects of different cutting parameters on surface roughness and power consumption are analysed.

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