Reason-A Technical Journal (Formerly Reason-A Technical Magazine)

Subrata Mondal ¹, Asish Bandyopadhyay ², Pradip Kumar Pal ²

Affiliations
1 Mechanical Engineering Department, Techno India- Salt Lake, Sector-V, Kolkata-700 091, IN
2 Mechanical Engineering Department, Jadavpur University, IN

Abstract

The drill-bit assisted abrasive flow machining (AFM) process is usually chosen for finishing operation in manufacturing industries where the fine surface finish of the component is an important criterion and considered as primary response in the present work. A number of experiments have been conducted according to Box-behnken design considering EN 24 as work piece material. Experiments were performed under different machining conditions by varying the parameters such as abrasive particle size, media viscosity, drill bit diameter and number of process cycle. The material removal rate (MRR) has been considered as secondary response of this process. In the present paper, a multi-objective optimization technique using Taguchi based Grey relational analysis has been applied to optimize the process performance of the drill-bit assisted AFM. How could a complicated multiple performance characteristics simplified to a single objective optimization problem has been presented here by this approach. The specific targets are minimum surface roughness and maximum material removal rate. According to importance of quality characteristics there are three criteria for optimization in grey relational analysis, which are „Larger-the-Better‟, „Smaller-the-Better‟ and „Nominal-the-Best‟. In the present analysis the lower value of surface roughness represents smooth surface i.e. better finishing performance, therefore „Lower-the-Better‟ criteria is chosen for surface roughness. On the other hand the higher value of MRR indicates more economical as compared to other finishing processes, therefore „Higher-the-Better‟ is chosen for MRR. In the present work smaller surface roughness and larger MRR are desirable. The optimal parametric setting obtained from grey relational analysis has been validated by a confirmation test.

Keywords

Optimization, Taguchi Method, AFM, GRA, Surface Finish.

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Abhishek Ghosh ¹, Sudip Mandal ², Goutam Nandi ³, Pradip Kumar Pal ¹

Affiliations
1 Department of Mechanical Engineering, Jadavpur University, Kolkata-700032, IN
2 Department of Electronics and Communication Engineering, Jalpaiguri Govt. Engg. College, Jalpaiguri-735102, IN
3 Department of Mechanical Engineering, Jadavpur University, Kolkata- 700032, IN

Abstract

Martensitic stainless steels are very difficult to weld. In this proposed work, effort is given on picking TIG welding optimum input parametric combination to join AISI 420 grade sheets.Welding current, shielding gas flow rate and welding (travel) speed are taken as input parameters. Whereas, ultimate tensile strength (UTS) and ductility (D) i.e. elongation of the weldment are considered as response or output parameters. Initially, response surface methodology (RSM) based face-centered central composite design (CCD) is employed for mathematical modeling by regression analysis. Next, six efficient metaheuristics and RSM optimization have been applied to maximize the output welding parameters. From the simulated results, the optimum parametric setting i.e. best set of welding current, gas flow rate and welding speed is identified in for maximization of UTS and D. Confirmatory tests are also conducted to validate the proposed approach.

Keywords

AISI 420 Grade Martensitic Stainless Steel, Homogeneous TIG Welding, RSM Modeling, Metaheuristic, Optimization.

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