Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutions
The industrial landscape is experiencing a dynamic transformation propelled by technological advancements and innovative methodologies. The progression from Industry 1.0 to Industry 4.0 signifies a journey of industrial transformation characterized by technological advancements and shifts in operati...
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Elsevier
2025-03-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024020875 |
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| author | Muthunandhini R. Palanivel K. |
| author_facet | Muthunandhini R. Palanivel K. |
| author_sort | Muthunandhini R. |
| collection | DOAJ |
| description | The industrial landscape is experiencing a dynamic transformation propelled by technological advancements and innovative methodologies. The progression from Industry 1.0 to Industry 4.0 signifies a journey of industrial transformation characterized by technological advancements and shifts in operational paradigms. This transition has significantly impacted various industries, influencing their evolution across successive revolutions. Among these industries, the textile industry, medical industry, iron and steel industry, and agriculture industry have played a pivotal role in all industrial revolutions. This study offers a comprehensive framework for selecting one of these industries for future development, examining their roles in shaping the industrial landscape of the future through the Superiority and Inferiority Ranking Multi-Criteria Decision-Making approach. The objective is to establish a Triple Vague framework on T- Spherical fuzzy sets for industry selection in the Industrial Revolution decision-making process. A comparative analysis was conducted with the proposed Decision-Making framework against other methods such as Technique for Order of Preference by Similarity to Ideal Solution, the Grey Relational Analysis method, and the Preference Ranking Organization Method for Enrichment Evaluation. The results indicate that the proposed structure highlights its effectiveness in addressing issues like hesitation, vagueness, and other undesirable characteristics. This underscores its significance in providing decision-makers with valuable insights for a thorough assessment and selection of optimal alternatives. Finally, the proposed Ranking approach yields two complete rankings, aiding in the effective selection of an industry for development. This innovative approach justifies the selection process in the era of industrial improvement for benefit of the society. |
| format | Article |
| id | doaj-art-653aa67f35fe40d3ab9bccc4ed04a30d |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-653aa67f35fe40d3ab9bccc4ed04a30d2025-01-05T04:28:35ZengElsevierResults in Engineering2590-12302025-03-0125103844Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutionsMuthunandhini R.0Palanivel K.1Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, IndiaCorresponding author.; Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, IndiaThe industrial landscape is experiencing a dynamic transformation propelled by technological advancements and innovative methodologies. The progression from Industry 1.0 to Industry 4.0 signifies a journey of industrial transformation characterized by technological advancements and shifts in operational paradigms. This transition has significantly impacted various industries, influencing their evolution across successive revolutions. Among these industries, the textile industry, medical industry, iron and steel industry, and agriculture industry have played a pivotal role in all industrial revolutions. This study offers a comprehensive framework for selecting one of these industries for future development, examining their roles in shaping the industrial landscape of the future through the Superiority and Inferiority Ranking Multi-Criteria Decision-Making approach. The objective is to establish a Triple Vague framework on T- Spherical fuzzy sets for industry selection in the Industrial Revolution decision-making process. A comparative analysis was conducted with the proposed Decision-Making framework against other methods such as Technique for Order of Preference by Similarity to Ideal Solution, the Grey Relational Analysis method, and the Preference Ranking Organization Method for Enrichment Evaluation. The results indicate that the proposed structure highlights its effectiveness in addressing issues like hesitation, vagueness, and other undesirable characteristics. This underscores its significance in providing decision-makers with valuable insights for a thorough assessment and selection of optimal alternatives. Finally, the proposed Ranking approach yields two complete rankings, aiding in the effective selection of an industry for development. This innovative approach justifies the selection process in the era of industrial improvement for benefit of the society.http://www.sciencedirect.com/science/article/pii/S2590123024020875Multi-criteria decision makingT-spherical fuzzy setsDecision makingTechnique for order preference by similarity to ideal solutionGrey relational analysisPreference ranking organization method for enrichment evaluation |
| spellingShingle | Muthunandhini R. Palanivel K. Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutions Results in Engineering Multi-criteria decision making T-spherical fuzzy sets Decision making Technique for order preference by similarity to ideal solution Grey relational analysis Preference ranking organization method for enrichment evaluation |
| title | Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutions |
| title_full | Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutions |
| title_fullStr | Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutions |
| title_full_unstemmed | Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutions |
| title_short | Optimizing industrial growth: A spherical fuzzy MCDM framework for industrial revolutions |
| title_sort | optimizing industrial growth a spherical fuzzy mcdm framework for industrial revolutions |
| topic | Multi-criteria decision making T-spherical fuzzy sets Decision making Technique for order preference by similarity to ideal solution Grey relational analysis Preference ranking organization method for enrichment evaluation |
| url | http://www.sciencedirect.com/science/article/pii/S2590123024020875 |
| work_keys_str_mv | AT muthunandhinir optimizingindustrialgrowthasphericalfuzzymcdmframeworkforindustrialrevolutions AT palanivelk optimizingindustrialgrowthasphericalfuzzymcdmframeworkforindustrialrevolutions |