Fuzzy Logic Approach on Lead Tin Alloy for Prediction of Machining Parameters by AWJM Process
K.S. Jai Aultrin1, M. DevAnand2, S. MuthuSherin3, R. Rajesh4

1K.S. Jai Aultrin, Associate Professor, Department of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil (Tamil Nadu), India.
2M. Dev Anand, Professor, Department of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil (Tamil Nadu), India.
3S. Muthu Sherin, Assistant Professor, Department of Aerospace Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India.
4R. Rajesh, Associate Professor, Department of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil (Tamil Nadu), India.
Manuscript received on 18 June 2019 | Revised Manuscript received on 11 July 2019 | Manuscript Published on 17 July 2019 | PP: 989-1003 | Volume-8 Issue-1C2 May 2019 | Retrieval Number: A11720581C219/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Last decades have witnessed a rapid growth in the development of harder, difficult and complexity to machine metals and alloys. AWJM is one of the recently developed nontraditional machining process in processing various kinds of hard-to-cut materials nowadays. It is an economical method for heat sensitive materials that cannot be machined by processes that produce heat while machining. Machining parameters play the lead role in determining the machine economics and quality of machining. In this study the consequence of five AWJM process parameters on MRR and SR of an American element named Lead Tin Alloy which is machined by AWJM was experimentally performed and analyzed. According to RSM design, different experiments were conducted with the combination of input parameters on this American element. This paper investigates the prediction of MRR and Surface roughness on Lead Tin Alloy using three different types of membership function on Fuzzy logic (FL) approach.
Keywords: Response Surface Methodology, Fuzzy Logic, Membership Function, Material Removal Rate, Surface Roughness.
Scope of the Article: Manufacturing Processes