This paper aims to justify the importance of machine learning (ML) for the digital Supply chain (SC) in real-time.
Authors
Sachin Yadav, Assistant Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.
Surya Prakash Singh, Department of Management Studies, Indian Institute of Technology Delhi, Delhi, India
Summary
This paper aims to justify the importance of machine learning (ML) for the digital Supply chain (SC) in real-time. Disruption in SC is strongly affected by the COVID-19 pandemic. Worldwide, continuous lockdowns and shutdown of manufacturing plants have increased the stress on supply, resulting in disturbance amongst the demands and supplies, which increased the overall cost.
Tracing the material and transparency in SC are current challenges for manufacturing organizations. Therefore, Blockchain (BC) can be seen as a solution to SC’s transparency, traceability, trust, security, etc. But whenever we talk about real-time records, information without integration of ML with BC-integrated SC is incomplete. ML develops the real-time authenticity factor model that incorporates Women’s empowerment.
This mathematical model is easily integrated with the digital SC procurement problem to estimate real-time procurement costs. This developed ML-based authenticity factor will be a new milestone for optimizing the SC cost in the digital era. This proposed research develops the authenticity factor through machine learning. This model will reduce the errors from SC and make the system more resilient.
Published in: 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
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