Abstract
In the supply chain management of the automotive industry, this paper investigates the use of demand forecasting, supply optimization, and price optimization. Optimizing the supply chain is essential for satisfying changing customer needs, cutting expenses, and increasing revenue. This study aims to improve the accuracy of demand prediction, optimize supplier relationships, and simplify pricing strategies through the use of ML-driven models. To solve the difficulties faced by automakers in a volatile market, the suggested framework combines historical data analysis, market trends, and inventory management strategies. The results help the automotive industry's supply chain systems become more flexible and resilient.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal for Research in Applied Science and Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
