Multivariate process capability analysis applied to AISI 52100 hardened steel turning
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Hard turning operations have been extensively investigated owing to their ability to reduce process cycle time, increase process flexibility, ensure high-dimensional accuracy, and enable machining without a cutting fluid. These processes are rather common for dealing with multiple quality characteristics. To evaluate the process ability and meet customer needs, multivariate statistical techniques are recommended for estimating the capability indices. Principal component analysis can be applied to reducing the problem dimension and estimate process capability indices. The aim of this study was to assess the capability of AISI 52100 hardened steel turning operations and achieve process specifications. Multivariate process capability indices were calculated to assess five roughness parameters of surface finishing. By using a weighted approach of principal component analysis, a new method is proposed for estimating the process capability indices. The results highlight not only the relevance of conducting a multivariate capability analysis in the case of actual machining but also how successfully the proposed method was performed.
KeywordsProcess capability index Hard turning Roughness Principal component analysis
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- 5.Bouacha K, Yallese MA, Mabrouki T, Rigal JF (2010) Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool. Int J Refract Met Hard Mater 28(3):349–361. https://doi.org/10.1016/j.ijrmhm.2009.11.011 CrossRefGoogle Scholar
- 7.Paiva AP, Campos PH, Ferreira JR, Lopes LGD, Paiva EJ, Balestrassi PP (2012) A multivariate robust parameter design approach for optimization of AISI 52100 hardened steel turning with wiper mixed ceramic tool. Int J Refract Met Hard Mater 30(1):152–163. https://doi.org/10.1016/j.ijrmhm.2011.08.001 CrossRefGoogle Scholar
- 16.Pearn WL, Kotz S (2006) Encyclopedia and handbook of process capability indices - a comprehensive exposition of quality control measures. https://doi.org/10.1142/9789812773753
- 17.Peruchi RS, Paiva AP, Balestrassi PP, Ferreira JR, Sawhney R (2014) Weighted approach for multivariate analysis of variance in measurement system analysis. Precis Eng 38(3):651–658. https://doi.org/10.1016/j.precisioneng.2014.03.001 CrossRefGoogle Scholar
- 36.Vannman K (1995) A unified approach to capability indices. Stat Sin 5:805–820 http://www3.stat.sinica.edu.tw/statistica/j5n2/j5n227/j5n227.htm MATHGoogle Scholar