Optimization of Different Workout Variables Throughout CNC Turning of ASTM 316 Deploying ANOVA
N. K. Kund1, Shweta Siktta Swain2
1N. K. Kund*, Department of Production Engineering, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India.
2Shweta Siktta Swain, Department of Production Engineering, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 4548-4552 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8478118419/2019©BEIESP | DOI: 10.35940/ijrte.D8478.118419
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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: Blueprint of examination regarding ANOVA remains developed and executed for evaluating effect of various workout variables like V, F and D on surface unevenness throughout CNC turning of ASTM 316 steel using coated carbide insert. 3D graphs through momentous surface unevenness got developed and utilized for evaluating average surface unevenness through ideal design situations. Evidently, text interface impressions are extraneous. Research findings through different mathematical analyses provided the effective guideline for choosing appropriate machine settings to realize surface unevenness within the stipulated limit during stated turning operation. Ideal machining situations got determined to minimize the surface unevenness of same. Current research evidently divulges that multicoated carbide inserts performed marvelously at optimum workout variables combination of V = 150 m/min, F = 0.10 mm/rev with D = 0.4 mm. Ultimate range of Ra with Rz are 0.16 μm ≤ Ra ≤ 0.52 μm and 1.4 μm ≤ Rz ≤ 3.1 μm, respectively. Besides, Ra is below recommended safety limit 1.5 μm (i.e. Ra < 1.5 μm) for turning using coated carbide inserts. 3D surface plots got developed with changing 2 variables and fixing third one. Wholly, both unevenness variables (Ra and Rz) increase with F. Also, both unevenness variables (Ra and Rz) decrease with increase in V. But, D got quite insignificant impact on both unevenness variables (Ra and Rz). Probability plot of Ra is depicted for trialing statistical cogency of representations. Residuals discrepancies appear along approximately linear route.
Keywords: Surface Unevenness, CNC Turning, ASTM 316 Steel, ANOVA, Workout Variables, Workpiece.
Scope of the Article: Design Optimization of Structures.