Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions
Abstract Significant attention has been given to low‐carbon smart manufacturing (SM) as a strategy for promoting sustainability and carbon‐free emissions in the manufacturing industry. The implementation of intelligent algorithms and procedures enables the attainment and enhancement of low‐carbon cl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-03-01
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| Series: | IET Collaborative Intelligent Manufacturing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cim2.12094 |
| _version_ | 1797238510741094400 |
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| author | Sudhanshu Joshi Manu Sharma |
| author_facet | Sudhanshu Joshi Manu Sharma |
| author_sort | Sudhanshu Joshi |
| collection | DOAJ |
| description | Abstract Significant attention has been given to low‐carbon smart manufacturing (SM) as a strategy for promoting sustainability and carbon‐free emissions in the manufacturing industry. The implementation of intelligent algorithms and procedures enables the attainment and enhancement of low‐carbon clever manufacturing processes. These algorithms facilitate real‐time monitoring and predictive maintenance, ensuring efficient and sustainable operations and data‐driven decision‐making, increasing resource utilisation, waste reduction, and energy efficiency. The research examines the utilisation of algorithms in the context of low‐carbon smart manufacturing, encompassing machine learning, optimisation algorithms, and predictive analytics. A comprehensive literature evaluation spanning from 2011 to 2023 is conducted to assess the significance of low‐carbon approaches in the context of smart manufacturing. An integrated approach is used using content analysis, network data analysis, bibliometric analysis, and cluster analysis. Based on the published literature the leading contributors to low‐carbon manufacturing research are India, China, United States, United Kingdom, Singapore, and Italy. The results have shown five main themes—Low‐carbon smart manufacturing and applications of Algorithms; Industry 4.0 technologies for low‐carbon manufacturing; low carbon and green manufacturing; Low‐carbon Manufacturing, and Product design and control; Lean Systems and Smart Manufacturing. The purpose of this study is to provide policymakers and researchers with a guide for the academic development of low‐carbon manufacturing by evaluating research efforts in light of identified research deficits. |
| first_indexed | 2024-04-24T17:36:48Z |
| format | Article |
| id | doaj.art-fce424ba88784ee988a9f039818d586e |
| institution | Directory Open Access Journal |
| issn | 2516-8398 |
| language | English |
| last_indexed | 2024-04-24T17:36:48Z |
| publishDate | 2024-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Collaborative Intelligent Manufacturing |
| spelling | doaj.art-fce424ba88784ee988a9f039818d586e2024-03-28T05:21:01ZengWileyIET Collaborative Intelligent Manufacturing2516-83982024-03-0161n/an/a10.1049/cim2.12094Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directionsSudhanshu Joshi0Manu Sharma1Australian Artificial Intelligence Institute (AAII) University of Technology Sydney Sydney New South Wales AustraliaAustralian Artificial Intelligence Institute (AAII) University of Technology Sydney Sydney New South Wales AustraliaAbstract Significant attention has been given to low‐carbon smart manufacturing (SM) as a strategy for promoting sustainability and carbon‐free emissions in the manufacturing industry. The implementation of intelligent algorithms and procedures enables the attainment and enhancement of low‐carbon clever manufacturing processes. These algorithms facilitate real‐time monitoring and predictive maintenance, ensuring efficient and sustainable operations and data‐driven decision‐making, increasing resource utilisation, waste reduction, and energy efficiency. The research examines the utilisation of algorithms in the context of low‐carbon smart manufacturing, encompassing machine learning, optimisation algorithms, and predictive analytics. A comprehensive literature evaluation spanning from 2011 to 2023 is conducted to assess the significance of low‐carbon approaches in the context of smart manufacturing. An integrated approach is used using content analysis, network data analysis, bibliometric analysis, and cluster analysis. Based on the published literature the leading contributors to low‐carbon manufacturing research are India, China, United States, United Kingdom, Singapore, and Italy. The results have shown five main themes—Low‐carbon smart manufacturing and applications of Algorithms; Industry 4.0 technologies for low‐carbon manufacturing; low carbon and green manufacturing; Low‐carbon Manufacturing, and Product design and control; Lean Systems and Smart Manufacturing. The purpose of this study is to provide policymakers and researchers with a guide for the academic development of low‐carbon manufacturing by evaluating research efforts in light of identified research deficits.https://doi.org/10.1049/cim2.12094data analysisdecision makingmanufacturing systemsmanufacturing industries |
| spellingShingle | Sudhanshu Joshi Manu Sharma Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions IET Collaborative Intelligent Manufacturing data analysis decision making manufacturing systems manufacturing industries |
| title | Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions |
| title_full | Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions |
| title_fullStr | Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions |
| title_full_unstemmed | Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions |
| title_short | Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions |
| title_sort | intelligent algorithms and methodologies for low carbon smart manufacturing review on past research recent developments and future research directions |
| topic | data analysis decision making manufacturing systems manufacturing industries |
| url | https://doi.org/10.1049/cim2.12094 |
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