SWARA-CoCoSo method-based parametric optimization of green dry milling processes
Abstract Attaining green environment for various machining processes has now caught the attention of many manufacturing industries. The input parameters involved in those machining processes are mainly responsible for achieving the desired performance as they are directly related to the process outp...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-03-01
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| Series: | Journal of Engineering and Applied Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44147-022-00087-3 |
| _version_ | 1818776053932359680 |
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| author | Partha Protim Das Shankar Chakraborty |
| author_facet | Partha Protim Das Shankar Chakraborty |
| author_sort | Partha Protim Das |
| collection | DOAJ |
| description | Abstract Attaining green environment for various machining processes has now caught the attention of many manufacturing industries. The input parameters involved in those machining processes are mainly responsible for achieving the desired performance as they are directly related to the process outputs. Hence, proper selection of the input process parameters becomes vital for having sustainable machining environment. In this paper, an integrated application of step-wise weight assessment ratio analysis (SWARA) and combined compromise solution (CoCoSo) methods is presented to identify the optimal parametric combinations of two green dry milling processes. In the first example, cutting speed, depth of cut, feed rate and nose radius are treated as the input parameters, while power factor, electric consumption and surface roughness are the responses. On the other hand, in the second example, cutting speed, feed rate, depth of cut and width of cut, and surface roughness, active cutting energy and material removal rate are respectively considered as the input parameters and responses. Instead of considering equal weights, SWARA method assigns relative subjective importance to the responses based on the preference set by the decision-makers, while CoCoSo ranks the experimental trials from the best to the worst. The derived optimal parametric settings are finally analyzed using the developed regression equations. It is observed that SWARA-CoCoSo method outperforms the other popular optimization techniques in identifying the best parametric intermixes for the green dry milling processes for having improved machining performance with minimal environmental effect. |
| first_indexed | 2024-12-18T11:06:49Z |
| format | Article |
| id | doaj.art-f84384382fd14ebdbecb8325d6d50426 |
| institution | Directory Open Access Journal |
| issn | 1110-1903 2536-9512 |
| language | English |
| last_indexed | 2024-12-18T11:06:49Z |
| publishDate | 2022-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Engineering and Applied Science |
| spelling | doaj.art-f84384382fd14ebdbecb8325d6d504262022-12-21T21:10:05ZengSpringerOpenJournal of Engineering and Applied Science1110-19032536-95122022-03-0169112110.1186/s44147-022-00087-3SWARA-CoCoSo method-based parametric optimization of green dry milling processesPartha Protim Das0Shankar Chakraborty1Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal UniversityDepartment of Production Engineering, Jadavpur UniversityAbstract Attaining green environment for various machining processes has now caught the attention of many manufacturing industries. The input parameters involved in those machining processes are mainly responsible for achieving the desired performance as they are directly related to the process outputs. Hence, proper selection of the input process parameters becomes vital for having sustainable machining environment. In this paper, an integrated application of step-wise weight assessment ratio analysis (SWARA) and combined compromise solution (CoCoSo) methods is presented to identify the optimal parametric combinations of two green dry milling processes. In the first example, cutting speed, depth of cut, feed rate and nose radius are treated as the input parameters, while power factor, electric consumption and surface roughness are the responses. On the other hand, in the second example, cutting speed, feed rate, depth of cut and width of cut, and surface roughness, active cutting energy and material removal rate are respectively considered as the input parameters and responses. Instead of considering equal weights, SWARA method assigns relative subjective importance to the responses based on the preference set by the decision-makers, while CoCoSo ranks the experimental trials from the best to the worst. The derived optimal parametric settings are finally analyzed using the developed regression equations. It is observed that SWARA-CoCoSo method outperforms the other popular optimization techniques in identifying the best parametric intermixes for the green dry milling processes for having improved machining performance with minimal environmental effect.https://doi.org/10.1186/s44147-022-00087-3Green dry millingSWARACoCoSoOptimizationMilling parameterResponse |
| spellingShingle | Partha Protim Das Shankar Chakraborty SWARA-CoCoSo method-based parametric optimization of green dry milling processes Journal of Engineering and Applied Science Green dry milling SWARA CoCoSo Optimization Milling parameter Response |
| title | SWARA-CoCoSo method-based parametric optimization of green dry milling processes |
| title_full | SWARA-CoCoSo method-based parametric optimization of green dry milling processes |
| title_fullStr | SWARA-CoCoSo method-based parametric optimization of green dry milling processes |
| title_full_unstemmed | SWARA-CoCoSo method-based parametric optimization of green dry milling processes |
| title_short | SWARA-CoCoSo method-based parametric optimization of green dry milling processes |
| title_sort | swara cocoso method based parametric optimization of green dry milling processes |
| topic | Green dry milling SWARA CoCoSo Optimization Milling parameter Response |
| url | https://doi.org/10.1186/s44147-022-00087-3 |
| work_keys_str_mv | AT parthaprotimdas swaracocosomethodbasedparametricoptimizationofgreendrymillingprocesses AT shankarchakraborty swaracocosomethodbasedparametricoptimizationofgreendrymillingprocesses |