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A comparative study of price-driven production control methods using a sawmill simulator

Louis Duhem, Maha Ben Ali, Michael Morin and Jonathan Gaudreault

Paper (2024)

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Abstract

In today's dynamic markets, decision-making relies heavily on simulation models to evaluate different production control methods. Although price-driven production control methods have proven their effectiveness in exploiting price volatility, certain industries are still reluctant to adopt these methods in their operational decision-making. This research demonstrates the relevance of price-driven methods for the wood products industry. A sawmill simulator is used to illustrate this. Since the simulation of the sawmill production process is time-consuming, we propose a probabilistic sampling-based method to rationalize the dataset size. A comparative study shows that exploiting historical and recent price data increases sawmill revenues.

Uncontrolled Keywords

industries; planing; decision making; production control; machine learning; probabilistic logic; delays

Subjects: 1600 Industrial engineering > 1600 Industrial engineering
1600 Industrial engineering > 1606 Operations management
Department: Department of Mathematics and Industrial Engineering
PolyPublie URL: https://publications.polymtl.ca/59311/
Conference Title: 2024 Winter Simulation Conference
Conference Location: Orlando, Florida, USA
Conference Date(s): 2024-12-15 - 2024-12-18
Publisher: IEEE
DOI: 10.1109/wsc63780.2024.10838824
Official URL: https://doi.org/10.1109/wsc63780.2024.10838824
Date Deposited: 24 Sep 2024 16:18
Last Modified: 11 Feb 2025 12:22
Cite in APA 7: Duhem, L., Ben Ali, M., Morin, M., & Gaudreault, J. (2024, December). A comparative study of price-driven production control methods using a sawmill simulator [Paper]. 2024 Winter Simulation Conference, Orlando, Florida, USA. https://doi.org/10.1109/wsc63780.2024.10838824

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