Producing Optimum Quality Grinding Spindle Using Hardened AISI 4340 Steel through a Cylindrical Grinding Process
Manikandan.M1, Prabagaran.S2, Sivaram.N.M3, Milon Selvam Dennison4

1Manikandan.M*, Research Scholar, Mechanical Engineering, Karpagam Academy of Higher Education, India.
2Prabagaran.S, Professor, Mechanical Engineering, Karpagam Academy of Higher Education, India.
3Sivaram.N.M, Mechanical Engineering, National Institute of Technology Puducherry, Karaikal, India.
4Milon Selvam Dennison, Mechanical Engineering, Kampala International University, Kampala, Uganda.

Manuscript received on November 12, 2019. | Revised Manuscript received on 21 November, 2019. | Manuscript published on December 10, 2019. | PP: 447-454 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6437129219/2019©BEIESP | DOI: 10.35940/ijitee.B6437.129219
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Abstract: The intent of this study is to produce optimum quality grinding spindle using hardened AISI 4340 steel through the cylindrical grinding process. Primarily the AISI 4340 steel specimens are cut according to the product specification and subjected to rough machining. Then the steel specimens are subjected to a heat-treatment process to enhance the mechanical property hardness so that the specimen becomes wear-resistant. The experimental runs are planned depending on Taguchi’s L27(37) array and conducted in a cylindrical grinding machine (Toyoda G32 cylindrical grinding machine). The surface roughness of the machined specimens is measured using a calibrated surface roughness tester. A prediction model is created through regression analysis for the outcome. The significance of the selected grinding factors and their levels on surface roughness is found by analysis of variance (ANOVA) and F-test and finally. An affirmation test is directed to produce the ideal components. 
Keywords: Grinding Spindle, Cylindrical Grinding, AISI 4340, Taguchi, Regression Analysis, ANOVA.
Scope of the Article: Regression and Prediction