Statistical regression modeling and machinability study of hardened AISI 52100 steel using cemented carbide insert
| Autor: | Amlana Panda, Ashok Kumar Sahoo, Arun Kumar Rout |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | International Journal of Industrial Engineering Computations, Vol 8, Iss 1, Pp 33-44 (2017) |
| Druh dokumentu: | article |
| ISSN: | 1923-2926 1923-2934 |
| DOI: | 10.5267/j.ijiec.2016.7.004 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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