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Supply Chain Management with Application of Lean Six Sigma and Artificial Intelligence: An Integrated Empirical Investigation


Affiliations
1 Professor & Head, Department of Supply Chain & Logistics Management, Indian Institute of Social Welfare & Business Management, Management House, College Square West, Kolkata, West Bengal,, India
2 C.E.O (Realware), C.S.O. (S. C. Trading & Co.), Department of Supply Chain & Logistics Management, Indian Institute of Social Welfare and Business Management, Kolkata, West Bengal, India
3 Vice President (Materials), CESC Limited, Materials Division, Kolkata, West Bengal, India
     

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The objective of this study is to establish a new business model for a business unit implementing the technology and methodology mentioned in 2.0 (visualised). It further encompassed the comparison with the benchmark snapshot between the quarter 01.10.2020 – 31.12.2020 and 01.1.2021 – 03.03.2021). The improvements due to the integration of lean six sigma along with artificial intelligence in conventional supply chain management system were quantified in terms of increase in percentage of profit, reduction in distributor attrition, failure of supply, excess or blocked inventory, and furthermore, reduction in operating losses and project completion tenure. Finally, the study identified areas of improvement with respect to the services rendered with supply chain, and suggested corrective actions for the same. The results derived in this study are explicit, conceptually stimulating and may provide guidance to managers engaged in supply chain management activities. The results showed that conventional supply chain management system is difficult to build, due to the complexities and uncertainties that exist across organizational boundaries. Hence, it is not surprising, therefore, that most alliances among partners fail to generate expected outcomes, especially in context to leveraging the potential of lean six sigma and Artificial Intelligence based SCM. It is hoped that our results provide a framework that may act as a blueprint for the manufacturing sector to assess and improve conventional supply chain management system with lean six sigma and AI-powered supply chain management, as well as increased organizational and financial performance.

Keywords

Supply Chain Management, Lean Six Sigma, Artificial Intelligence, Industrial Internet of Things, DMIAC, Client Relationship Management System, Operational Process
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  • Supply Chain Management with Application of Lean Six Sigma and Artificial Intelligence: An Integrated Empirical Investigation

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Authors

Sarbani Mitra
Professor & Head, Department of Supply Chain & Logistics Management, Indian Institute of Social Welfare & Business Management, Management House, College Square West, Kolkata, West Bengal,, India
Bishakh Chanda
C.E.O (Realware), C.S.O. (S. C. Trading & Co.), Department of Supply Chain & Logistics Management, Indian Institute of Social Welfare and Business Management, Kolkata, West Bengal, India
Partha Bhattacharya
Vice President (Materials), CESC Limited, Materials Division, Kolkata, West Bengal, India

Abstract


The objective of this study is to establish a new business model for a business unit implementing the technology and methodology mentioned in 2.0 (visualised). It further encompassed the comparison with the benchmark snapshot between the quarter 01.10.2020 – 31.12.2020 and 01.1.2021 – 03.03.2021). The improvements due to the integration of lean six sigma along with artificial intelligence in conventional supply chain management system were quantified in terms of increase in percentage of profit, reduction in distributor attrition, failure of supply, excess or blocked inventory, and furthermore, reduction in operating losses and project completion tenure. Finally, the study identified areas of improvement with respect to the services rendered with supply chain, and suggested corrective actions for the same. The results derived in this study are explicit, conceptually stimulating and may provide guidance to managers engaged in supply chain management activities. The results showed that conventional supply chain management system is difficult to build, due to the complexities and uncertainties that exist across organizational boundaries. Hence, it is not surprising, therefore, that most alliances among partners fail to generate expected outcomes, especially in context to leveraging the potential of lean six sigma and Artificial Intelligence based SCM. It is hoped that our results provide a framework that may act as a blueprint for the manufacturing sector to assess and improve conventional supply chain management system with lean six sigma and AI-powered supply chain management, as well as increased organizational and financial performance.

Keywords


Supply Chain Management, Lean Six Sigma, Artificial Intelligence, Industrial Internet of Things, DMIAC, Client Relationship Management System, Operational Process

References