| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Girardin, François
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (13/13 displayed)
- 2018Estimation and optimization of flank wear and tool lifespan in finish turning of AISI 304 stainless steel using desirability function approachcitations
- 2018Estimation and optimization of flank wear and tool lifespan in finish turning of AISI 304 stainless steel using desirability function approachcitations
- 2017Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN)citations
- 2017Predictive modeling and multi-response optimization of technological parameters in turning of Polyoxymethylene polymer (POM C) using RSM and desirability functioncitations
- 2017Predictive modeling and multi-response optimization of technological parameters in turning of Polyoxymethylene polymer (POM C) using RSM and desirability functioncitations
- 2017Modeling and optimization of turning process parameters during the cutting of polymer (POM C) based on RSM, ANN, and DF methodscitations
- 2017Modeling and optimization of turning process parameters during the cutting of polymer (POM C) based on RSM, ANN, and DF methodscitations
- 2017Quality-productivity decision making when turning of Inconel 718 aerospace alloy: A response surface methodology approach
- 2017Quality-productivity decision making when turning of Inconel 718 aerospace alloy: A response surface methodology approachcitations
- 2016Performance of coated and uncoated mixed ceramic tools in hard turning processcitations
- 2016Performance of coated and uncoated mixed ceramic tools in hard turning processcitations
- 2015Modeling and optimization of tool wear and surface roughness in turning of austenitic stainless steel using response surface methodology
- 2015Modeling and optimization of tool wear and surface roughness in turning of austenitic stainless steel using response surface methodology
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article
Predictive modeling and multi-response optimization of technological parameters in turning of Polyoxymethylene polymer (POM C) using RSM and desirability function
Abstract
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.