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| Naji, M. |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Casati, R. |
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| Kočí, Jan | Prague |
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| Ali, M. A. |
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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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Živković, Aleksandar
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Topics
Publications (9/9 displayed)
- 2024High performance thermoelectrics from low-cost and abundant CuS/CuI composites
- 2024High performance thermoelectrics from low-cost and abundant CuS/CuI compositescitations
- 2024Fabrication of ZnO Scaffolded CdS Nanostructured Photoanodes with Enhanced Photoelectrochemical Water Splitting Activity under Visible Lightcitations
- 2024Fabrication of ZnO Scaffolded CdS Nanostructured Photoanodes with Enhanced Photoelectrochemical Water Splitting Activity under Visible Light
- 2022A grey fuzzy approach to the selection of cutting process from the aspect of technological parameterscitations
- 2021Arc Synthesis, Crystal Structure, and Photoelectrochemistry of Copper(I) Tungstate
- 2020Exploring the formation of intrinsic p-type and n-type defects in CuOcitations
- 2019Tuning the electronic band gap of Cu2O via transition metal doping for improved photovoltaic applications
- 2019Tuning the electronic band gap of Cu2O via transition metal doping for improved photovoltaic applicationscitations
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article
A grey fuzzy approach to the selection of cutting process from the aspect of technological parameters
Abstract
This study deals with the selection of the cutting process using the grey fuzzy relation approach. The analysis was performed using plasma arc machining, laser beam machining, and abrasive waterjet machining on three different workpiece thicknesses with different cutting speeds. The objective was to select the best cutting process considering several performance characteristics such as machining time, dimensional accuracy, kerf width, and surface roughness. Data normalization, grey relation coefficients, fuzzy inference system, and grey fuzzy relation grade are used to evaluate the machining performances of the machining processes. The developed fuzzy model can be used to study the effects of different cutting processes on technological features. The results show that the grey fuzzy technique can be effectively used for the analysis and selection of cutting processes. ; Web of Science ; 12 ; 24 ; art. no. 12589