
Inventory Optimization for Revised Production Schedules in the Manufacturing Industry
The need to intelligently cope with significant changes that happen between planning and execution coupled with the highly dynamic nature of markets in manufacturing industries necessitates systematic approaches to effectively manage material orders to remain efficient and competitive. This paper considers a realistic case in an automotive industry assembly line that experiences frequent demand revisions and affects multiple facets of supply chain operations. These include, but are not limited to, (de-)expedited material orders from suppliers, changes to master production schedules, line stoppages due to inadequate inventory, changes to transportation plans, and revisions to delivery commitments. In general, any demand revisions within the Enterprise Resource Planning (ERP) system can cause disruptions throughout the supply chain. In an automotive industry assembly line for example, thousands of parts are typically ordered from multiple suppliers, and with the rise in globalization and the need to source materials in a cost effective manner, these parts can have large lead times ranging from a few weeks to months. This further mandates the need for a systematic approach to manage material orders in response to a change in demand. In this paper, we consider this problem of managing material orders in response to demand revisions and propose a linear programming (LP) model to optimally revise material orders from suppliers with the objective of minimizing penalties for unmet demand, suppliers’ capacity, and expedited shipments. An illustrative example is used to test the usefulness of the model and to derive insights on the decisions from the model. In addition, a large-scale realistic industry-sized instance is also used to test model performance. Finally, key managerial implications pertaining to the use of this approach as a decision support system are also presented. Advisor - Professor Dr Anirudh Subramanyam
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Work Title | Inventory Optimization for Revised Production Schedules in the Manufacturing Industry |
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License | In Copyright (Rights Reserved) |
Work Type | Research Paper |
Publication Date | 2024 |
DOI | doi:10.26207/bj3d-3615 |
Deposited | March 25, 2024 |
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