Predictive modeling and multi-response optimization of technological parameters in turning of Polyoxymethylene polymer (POM C) using RSM and desirability function - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Measurement - Journal of the International Measurement Confederation (IMEKO) Année : 2017

Predictive modeling and multi-response optimization of technological parameters in turning of Polyoxymethylene polymer (POM C) using RSM and desirability function

Résumé

The present paper focuses on the determination of the optimum cutting conditions leading to minimum surface roughness as well as cutting force, cutting power and maximum productivity, in the case of the turning of the Polyoxymethylene polymer POM C using cemented carbide cutting tool. The optimization is based on the response surface methodology, RSM, (desirability function approach). Furthermore, the analysis of variance (ANOVA) is exploited to establish the statistical significance of the cutting parameters on different technological ones studied. The results revealed that the surface roughness is strongly influenced by feed rate with a large contribution, followed by cutting depth, whereas, the cutting speed has no influence. Regarding cutting force, it is found that depth of cut and feed rate are the most significant terms. The RSM allowed the optimization of the cutting conditions for minimal surface roughness, cutting force, cutting power and maximal material removal rate.
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Dates et versions

hal-01999564 , version 1 (30-01-2019)

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Amel Chabbi, Mohamed Athmane Yallese, Ikhlas Meddour, Mourad Nouioua, Tarek Mabrouki, et al.. Predictive modeling and multi-response optimization of technological parameters in turning of Polyoxymethylene polymer (POM C) using RSM and desirability function. Measurement - Journal of the International Measurement Confederation (IMEKO), 2017, 95, pp.99-115. ⟨10.1016/j.measurement.2016.09.043⟩. ⟨hal-01999564⟩
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