%0 Journal Article %1 noauthororeditor %A Rana, Vikram Chaturvedi | Mohit Sharma | Ajay %D 2023 %J INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT %K Dry EN-100Cr6 Optimization, Ra, Steel Surface Tool roughness turning, wear, %N 3 %P 510-519 %T Modeling and Optimization of Machining Parameters for Minimizing Surface Roughness and Tool Wear for EN100Cr6 Steel Dry Turning %U https://www.ijtsrd.com.com/engineering/mechanical-engineering/57416/modeling-and-optimization-of-machining-parameters-for-minimizing-surface-roughness-and-tool-wear-for-en100cr6-steel-dry-turning/vikram-chaturvedi %V 7 %X Sustainable manufacturing is a priority because along with the factors like productivity, time cycle and cost optimization in a process, the effect of machining on environment and the operator equally matters. In order to take it in a consideration, dry machining is promoted over the conventional machining procedures. Therefore modelling and optimization is required to figure out correct cutting condition for desirable machinability results. EN100Cr6 range of products like Plates Sheets Steel bars Coil strip Pipe and tubes. During the study about the topic, EN 100Cr6 steel was turned under dry machining situations in order to optimize the way to enhance two factors called as surface roughness Ra and tool wear. As we all know that dumping the coolant and chip mixture is really been a quite tough procedure, that is the why conventional method of turning with a coolant is usually considered harmful for the environment. To find a solution to this problem, RSM was used for building a link between output and input parameters and finding out the optimize solution. The optimum levels of the factors obtained for the cutting conditions are feed rate at 0.10 mm rev, cutting speed at 80.0 m min and depth of cut at 0.680 mm and corresponding the values obtained for tool wear and surface roughness Ra are 0.03502580 mm and 3.380310µm. Model fitness and efficacy were judged by the confirmation tests. The correlation coefficient R2 of 0.9876 for tool wear and 0.9921 for surface roughness indicates a correlation between the predictions of models and results obtained after experiments. So, to minimize the number of experimental trails RSM model has been proved to be the excellent tool to find optimized results. Vikram Chaturvedi | Mohit Sharma | Ajay Rana "Modeling and Optimization of Machining Parameters for Minimizing Surface Roughness and Tool Wear for EN100Cr6 Steel Dry Turning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd57416.pdf Paper URL: https://www.ijtsrd.com.com/engineering/mechanical-engineering/57416/modeling-and-optimization-of-machining-parameters-for-minimizing-surface-roughness-and-tool-wear-for-en100cr6-steel-dry-turning/vikram-chaturvedi

@article{noauthororeditor, abstract = {Sustainable manufacturing is a priority because along with the factors like productivity, time cycle and cost optimization in a process, the effect of machining on environment and the operator equally matters. In order to take it in a consideration, dry machining is promoted over the conventional machining procedures. Therefore modelling and optimization is required to figure out correct cutting condition for desirable machinability results. EN100Cr6 range of products like Plates Sheets Steel bars Coil strip Pipe and tubes. During the study about the topic, EN 100Cr6 steel was turned under dry machining situations in order to optimize the way to enhance two factors called as surface roughness Ra and tool wear. As we all know that dumping the coolant and chip mixture is really been a quite tough procedure, that is the why conventional method of turning with a coolant is usually considered harmful for the environment. To find a solution to this problem, RSM was used for building a link between output and input parameters and finding out the optimize solution. The optimum levels of the factors obtained for the cutting conditions are feed rate at 0.10 mm rev, cutting speed at 80.0 m min and depth of cut at 0.680 mm and corresponding the values obtained for tool wear and surface roughness Ra are 0.03502580 mm and 3.380310µm. Model fitness and efficacy were judged by the confirmation tests. The correlation coefficient R2 of 0.9876 for tool wear and 0.9921 for surface roughness indicates a correlation between the predictions of models and results obtained after experiments. So, to minimize the number of experimental trails RSM model has been proved to be the excellent tool to find optimized results. Vikram Chaturvedi | Mohit Sharma | Ajay Rana "Modeling and Optimization of Machining Parameters for Minimizing Surface Roughness and Tool Wear for EN100Cr6 Steel Dry Turning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd57416.pdf Paper URL: https://www.ijtsrd.com.com/engineering/mechanical-engineering/57416/modeling-and-optimization-of-machining-parameters-for-minimizing-surface-roughness-and-tool-wear-for-en100cr6-steel-dry-turning/vikram-chaturvedi }, added-at = {2023-07-17T12:05:22.000+0200}, author = {Rana, Vikram Chaturvedi | Mohit Sharma | Ajay}, biburl = {https://www.bibsonomy.org/bibtex/2ff3c2be724a52c84e66d4b067268b0a3/ijtsrd}, interhash = {806ea5b994f54ad8172adde1b6e677da}, intrahash = {ff3c2be724a52c84e66d4b067268b0a3}, issn = {2456-6470}, journal = {INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT}, keywords = {Dry EN-100Cr6 Optimization, Ra, Steel Surface Tool roughness turning, wear,}, language = {english}, month = {June}, number = 3, pages = {510-519}, timestamp = {2023-07-17T12:05:22.000+0200}, title = {Modeling and Optimization of Machining Parameters for Minimizing Surface Roughness and Tool Wear for EN100Cr6 Steel Dry Turning }, url = {https://www.ijtsrd.com.com/engineering/mechanical-engineering/57416/modeling-and-optimization-of-machining-parameters-for-minimizing-surface-roughness-and-tool-wear-for-en100cr6-steel-dry-turning/vikram-chaturvedi}, volume = 7, year = 2023 }