The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach
<i>Background:</i> Our day-to-day commodities truly depend on the industrial sector, which is expanding at a rapid rate along with the growing population. The production of goods needs to be accurate and rapid. Thus, for the present research, we have incorporated machine-learning (ML) te...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Logistics |
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| Online Access: | https://www.mdpi.com/2305-6290/6/4/76 |
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| author | Alisha Lakra Shubhkirti Gupta Ravi Ranjan Sushanta Tripathy Deepak Singhal |
| author_facet | Alisha Lakra Shubhkirti Gupta Ravi Ranjan Sushanta Tripathy Deepak Singhal |
| author_sort | Alisha Lakra |
| collection | DOAJ |
| description | <i>Background:</i> Our day-to-day commodities truly depend on the industrial sector, which is expanding at a rapid rate along with the growing population. The production of goods needs to be accurate and rapid. Thus, for the present research, we have incorporated machine-learning (ML) technology in the manufacturing sector (MS). <i>Methods:</i> Through an inclusive study, we identify 11 factors within the research background that could be seen as holding significance for machine learning in the manufacturing sector. An interpretive structural modeling (ISM) method is used, and inputs from experts are applied to establish the relationships. <i>Results:</i> The findings from the ISM model show the ‘order fulfillment factor as the long-term focus and the ‘market demand’ factor as the short-term focus. The results indicate the critical factors that impact the development of machine learning in the manufacturing sector. <i>Conclusions:</i> Our research contributes to the manufacturing sector which aims to incorporate machine learning. Using the ISM model, industries can directly point out their oddities and improve on them for better performance. |
| format | Article |
| id | doaj-art-e90dabba00934024a96631be48e3dabc |
| institution | DOAJ |
| issn | 2305-6290 |
| language | English |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Logistics |
| spelling | doaj-art-e90dabba00934024a96631be48e3dabc2025-08-20T02:50:59ZengMDPI AGLogistics2305-62902022-10-01647610.3390/logistics6040076The Significance of Machine Learning in the Manufacturing Sector: An ISM ApproachAlisha Lakra0Shubhkirti Gupta1Ravi Ranjan2Sushanta Tripathy3Deepak Singhal4School of Mechanical Engineering, KIIT Deemed to be University, Bhubaneswar 751024, Orissa, IndiaDepartment of Information Technology, KIIT Deemed to be University, Bhubaneswar 751024, Orissa, IndiaSchool of Electronics Engineering, KIIT Deemed to be University, Bhubaneswar 751024, Orissa, IndiaSchool of Mechanical Engineering, KIIT Deemed to be University, Bhubaneswar 751024, Orissa, IndiaSchool of Mechanical Engineering, KIIT Deemed to be University, Bhubaneswar 751024, Orissa, India<i>Background:</i> Our day-to-day commodities truly depend on the industrial sector, which is expanding at a rapid rate along with the growing population. The production of goods needs to be accurate and rapid. Thus, for the present research, we have incorporated machine-learning (ML) technology in the manufacturing sector (MS). <i>Methods:</i> Through an inclusive study, we identify 11 factors within the research background that could be seen as holding significance for machine learning in the manufacturing sector. An interpretive structural modeling (ISM) method is used, and inputs from experts are applied to establish the relationships. <i>Results:</i> The findings from the ISM model show the ‘order fulfillment factor as the long-term focus and the ‘market demand’ factor as the short-term focus. The results indicate the critical factors that impact the development of machine learning in the manufacturing sector. <i>Conclusions:</i> Our research contributes to the manufacturing sector which aims to incorporate machine learning. Using the ISM model, industries can directly point out their oddities and improve on them for better performance.https://www.mdpi.com/2305-6290/6/4/76machine learningIndustry 4.0manufacturing industrysmart manufacturinginterpretive structural modeling (ISM) |
| spellingShingle | Alisha Lakra Shubhkirti Gupta Ravi Ranjan Sushanta Tripathy Deepak Singhal The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach Logistics machine learning Industry 4.0 manufacturing industry smart manufacturing interpretive structural modeling (ISM) |
| title | The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach |
| title_full | The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach |
| title_fullStr | The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach |
| title_full_unstemmed | The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach |
| title_short | The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach |
| title_sort | significance of machine learning in the manufacturing sector an ism approach |
| topic | machine learning Industry 4.0 manufacturing industry smart manufacturing interpretive structural modeling (ISM) |
| url | https://www.mdpi.com/2305-6290/6/4/76 |
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