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Authors
Affiliations
1 Mechanical Engineering Department, M.V.S.R. Engineering College, Nadergul, Hyderabad-501510, Telangana, IN
Source
International Journal of Engineering Research, Vol 4, No 7 (2015), Pagination: 363-367
Abstract
Manufacturing or production is one of the most important sectors of any field. It involves various steps or processes to convert raw materials into finished products. With the more precise demands of modern engineering products and competition to provide good quality, the surface finish, dimensional accuracy along with metal removal rate (MRR) plays a very important role. The selection of optimum cutting conditions (depth of cut, feed and speed) is an important element of process planning for every machining operation. In order to optimize the output parameters i.e., MRR, power consumption and surface roughness, the process variables are varied. Inspite of major advancements in metal cutting practices, the metal cutting industries continues to suffer from major drawback of not running the machine tools at their optimum operating condition. Furthermore, their prediction helps in the analysis of optimization problems in machining economics, in adaptive control applications, in the formulation of simulation models used in cutting databases. In the present work full factorial design of experiments (DOE) technique is used in order to find the effect of input parameters on MRR and surface roughness for Micro Alloyed Steel Roller Shaft work material of an under carriage at Berco Undercarriages India Pvt Ltd. Contribution of each factor on output is determined by Analysis of Variance (ANOVA) and using MAT LAB software the optimum values of process parameters for MRR and surface roughness are generated.
Keywords
DOE, ANOVA, Factors, MRR, Surface Roughness.
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