Dahbi, S. and El Moussami, H. and Ezzine, L. (2016) Multiple regression model for surface roughness using full factorial design. In: UNSPECIFIED.

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....


This paper describes the modeling of surface roughness in turning of AISI 1042 Steel at four cutting parameters: cutting speed, feed rate, depth of cut and tool nose radius. Full factorial design is implemented to investigate the effects of interactions of these parameters on surface roughness. By using the multiple regression method, we developed a model with high correlation coefficient of 99.55 and error of 0.07. Moreover, a good agreement was observed between estimated and experimental surface roughness in this model. The effects of cutting parameters and their interactions on surface roughness were investigated by using the analysis of variance. © 2015 International Institute for Innovation, Industrial Engineering and Entrepreneurship - I4e2.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Regression analysis; Turning, ANOVA analysis; Correlation coefficient; Cutting parameters; Full factorial design; Modeling of surface roughness; Multiple regression methods; Multiple regression model; Multiple regressions, Surface roughness
Subjects: Business, Management and Accounting
Divisions: SCIENTIFIC PRODUCTION > Business, Management and Accounting
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:44
URI: http://eprints.umi.ac.ma/id/eprint/1684

Actions (login required)

View Item View Item