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A Scalable Hybrid Model for the Parameterization of Material Requirements Planning under Uncertainty

Warfman, Niels (2024) A Scalable Hybrid Model for the Parameterization of Material Requirements Planning under Uncertainty. Research Project, Industrial Engineering and Management.


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Material Requirements Planning (MRP) is a core element in manufacturing management, capable of managing complex production systems and extensive Bill of Materials (BOM) structures. A significant challenge within MRP is determining the optimal planning parameters for systems characterized by uncertainty. This research deploys a scalable hybrid model to identify these optimal planning parameters amidst uncertain conditions, to minimize overall costs. The proposed model simulates a make-to-order production environment that has demand and lead time uncertainty. This scalable model is defined by the input it receives from BOM and routing information. Stochastic behaviour is applied to processing times, replenishment lead times, customer-required lead time and customer order size. Then a genetic algorithm is utilized to find the planning parameters to minimize the sum of inventory and backorder costs. The hybrid model is subjected to different scenarios regarding BOM size and complexity. The results indicate that the hybrid model successfully identifies optimal plan- ning parameters across a range of BOM sizes. Demonstrating adaptability to diverse demand pattern scenarios accompanied by uncertain lead times underscores the model’s broad applicability. This adaptability highlights the method’s potential for generic use in optimizing manufacturing planning parameters.

Item Type: Thesis (Research Project)
Supervisor name: Hubl, A.
Degree programme: Industrial Engineering and Management
Thesis type: Research Project
Language: English
Date Deposited: 22 Apr 2024 07:14
Last Modified: 22 Apr 2024 07:14

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