| 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
Performance of coated and uncoated mixed ceramic tools in hard turning process
Abstract
The present contribution deals with the study of the effects of cutting speed, feed rate and depth of cut on the performance of machining which traditionally named “machinability”. The focus is made on the effect of the pre-cited cutting parameters on the evolution of surface roughness and cutting force components during hard turning of AISI D3 cold work tool steel with CC6050 and CC650 ceramic inserts. Also, for both ceramics a comparison of their wear evolution with time and its impact on the surface equality was proposed. The planning of experiments was based on Taguchi’s L16 orthogonal array. The analysis of variance (ANOVA), the signal-to-noise ratio and response surface methodology (RSM) were adopted. Consequently, the validity of proposed linear regression model was checked and the most important parameter affecting the surface roughness and cutting force components were determined. Furthermore, in order to determine the levels of the cutting regime that lead to minimum surface roughness and minimum machining force the relationship between cutting factors was analyzed. The results revealed that the surface quality obtained with the coated CC6050 ceramic insert is 1.6 times better than the one obtained with uncoated CC650 ceramic insert. However, the uncoated ceramic insert was useful in reducing the machining force.