Effect of Machining Parameters on Tool Wear and Surface Roughness In Dry and Wet Machining of Aisi 316 Austenitic Stainless Steel by Taguchi Method
Sunil G Dambhare1, Sandeep S Kore2, Firoz Z Pathan3, Sandesh Kurne4
1Sunil G Dambhare, Department of Mechanical Engineering, Dr. D Y Patiul Institute of Engineering Management & Research, Pune (Maharashtra), India.
2Sandeep S Kore, Department of Mechanical Engineering, Dr. D Y Patiul Institute of Engineering Management & Research, Pune (Maharashtra), India.
3Firoz Z Pathan, Department of Mechanical Engineering, Dr. D Y Patiul Institute of Engineering Management & Research, Pune (Maharashtra), India.
4Sandesh Kurne, Department of Mechanical Engineering, Zeal College of Engineering & Research, Pune (Maharashtra), India.
Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 3292-3298 | Volume-8 Issue-9, July 2019 | Retrieval Number: H7441068819/19©BEIESP | DOI: 10.35940/ijitee.H7441.078919
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Stainless steels are widely used to manufacture mechanical components due to excellent mechanical properties. Machining is considered as one of the most critical manufacturing processes in mechanical industry to produce desired shapes and dimensional accuracy of the components. It also affects the performance of the components in its functional requirement. This paper deals with the optimization of cutting parameters in machining operation for AISI 316 austenitic steel with dry and wet environment conditions. The chosen machining parameters in this research are cutting speed, feed rate, and depth of cut as input variables, whereas the response factors are surface roughness and wear rate. Taguchi method with the L9 orthogonal array was used to analyze the process parameters based in dry and wet machining conditions. The Taguchi approach provides the best setting with lower values of surface roughness and wear rate. The regression analysis is performed to obtain a mathematical model of responses in terms of the process parameter. The composite regression optimization gives best setting for dry condition (cutting speed 173 rpm, feed 0.25 mm/rev, and 0.87 mm of the depth of cut) and for wet condition (cutting speed 173 rpm, feed 0.3 mm/rev, and 0.57 mm of the depth of cut). The results show that surface roughness and wear rate are lower in the wet environment than the dry environment.
Keywords: Taguchi method, Regression analysis, composite optimization, surface roughness , tool wear
Scope of the Article: Composite Material