文章基本信息

标题：Statistical regression modeling and machinability study of hardened AISI 52100 steel using cemented carbide insert
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作者：Panda, A. ; Panda, A. ; Sahoo, A. 等
期刊名称：International Journal of Industrial Engineering Computations
印刷版ISSN：1923-2926
电子版ISSN：1923-2934
出版年度：2017
卷号：8
期号：1
页码：33-44
DOI：10.5267/j.ijiec.2016.7.004
语种：English
出版社：Growing Science Publishing Company
摘要：The present study investigates performance and feasibility of application of low cost cemented carbide insert in dry machining of AISI 52100 steel hardened to (55 ± 1 HRC) which is rarely researched as far as machining of bearing steel is concerned. Machinability studies i.e. flank wear, surface roughness and morphology analysis of chip has been investigated and statistical regression modeling has been developed. The test has been conducted based on Taguchi L16 OA taking machining parameters like cutting speed, feed and depth of cut. It is observed that uncoated cemented carbide insert performs well at some selected runs (Run 1, 5 and 9) which show its feasibility for hard turning applications. The developed serrated saw tooth chip of burnt blue colour adversely affects the surface quality. Adequacy of the developed statistical regression model has been checked using ANOVA analysis (depending on F value, P value and R2 value) and normal probability plot at 95% confidence level. The results of optimal parametric combinations may be adopted while turning hardened AISI 52100 steel under dry environment with uncoated cemented carbide insert.
关键词：Hard turning; Machinability; Cemented carbide; Flank wear; Surface roughness; Regression