Electric Vehicle Supply Chain Volatility: AI-Based Risk Forecasting and Inventory Optimization in SAP-Driven Systems

Authors

  • Zubair Shafiullah Khan Independent Researcher, USA Author

Keywords:

electric vehicles, supply chain volatility, semiconductor shortage, AI forecasting, SAP MRP, inventory optimization, predictive analytics, risk modeling, reinforcement learning, demand variability

Abstract

The supply chain for electric vehicle production sector has experienced some disruptions caused by such factors as semiconductor shortage and restrictions on materials available for batteries. Currently, all the models used for planning in terms of deterministic models integrated in enterprise information systems, such as the SAP Material Requirement Planning system. Therefore, it is hard for organizations to deal with demand uncertainty and supplier risks. The solution of this challenge calls for incorporating the AI-powered prediction models taking into account the non-linear relationships between such factors as demand, supply shock, and supplier's multi-level dependencies. This research aims at developing AI-based risk prediction and inventory optimization model integrated into SAP MRP.

Downloads

Download data is not yet available.

Downloads

Published

20-03-2023

How to Cite

[1]
Z. S. Khan, “Electric Vehicle Supply Chain Volatility: AI-Based Risk Forecasting and Inventory Optimization in SAP-Driven Systems”, Art. Intel. Mach. Learn. Auto. Sys., vol. 7, pp. 75–108, Mar. 2023, Accessed: Jul. 29, 2026. [Online]. Available: https://amlas.net/index.php/publication/article/view/55

Similar Articles

1-10 of 50

You may also start an advanced similarity search for this article.