From Tradition to Technology

Author:

Kennedy George Williams1,Ikpe Samuel Amos2,Nassa Vinay Kumar3ORCID,Prajapati Tamanna4,Dhabliya Dharmesh5ORCID,Dari Sukhvinder Singh6ORCID

Affiliation:

1. School of Vocational and Technical Education, Akwa Ibom State College of Education, Nigeria

2. Department of Technical Education, Akwa Ibom State College of Education, Nigeria

3. Department of Information Communication Technology (ICT), Tecnia Institute of Advanced Studies, India

4. Shri D.N. Institute of Computer Applications, Sardar Patel University, Gujarat, India

5. Department of Information Technology, Vishwakarma Institute of Information Technology, Pune, India

6. Symbiosis Law School, Symbiosis International University, Pune, India

Abstract

The combination of AI and ML is driving supply chain digitalization. This chapter discusses supply chain management (SCM) in the digital age, including AI, ML, and classical techniques, SCM aspects and components, and supply chain network strategies. The chapter also covers AI and ML applications in supply chain optimisation, resilient supply chain network (SCN) methods, warehouse automation and robotics, transportation and route optimisation, and supply chain risk management. AI and ML enable supply chain stakeholders to use massive data streams for predictive analytics. AI-driven demand forecasting, inventory optimisation, and predictive maintenance reduce hazards and streamline resource allocation, improving cost-effectiveness. In a world of rapid change and innovation, organisations must use AI and ML as the supply chain ecosystem evolves.

Publisher

IGI Global

Reference50 articles.

1. Managing Artificial Intelligence.;N.Berente;Management Information Systems Quarterly,2021

2. Boopathi, S., Pandey, B. K., & Pandey, D. (2023). Advances in Artificial Intelligence for Image Processing: Techniques, Applications, and Optimization. In Handbook of Research on Thrust Technologies’ Effect on Image Processing (pp. 73-95). IGI Global.

3. Bringsjord, S., Govindarajulu, N. S., & Sundar, N. (2020). Stanford Encyclopedia of Philosophy. Retrieved from The Stanford Encyclopedia of Philosophy: https://plato.stanford.edu/entries/artificial-intelligence/#HistAI

4. Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlstrom, P., & Trench, M. (2017). Artificial Intelligence: The Next Digital Frontier? McKinsey Global Institute. Retrieved on August 19, 2023 from https://www.mckinsey.com/~/media/mckinsey/industries/advanced%20electronics/our %20insights/how%20artificial%20intelligence%20can%20deliver%20real%20value%20to%20companies/mgi-artificial-intelligence-discussion-paper.ashx

5. Caballero, S., & Rice, J.B. (2018). Artificial Intelligence/Machine Learning + Supply Chain Planning. MIT’s Center for Transportation and Logistics.

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