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Raw material heterogeneity, complex transformation processes, and divergent product flows make sawmilling operations difficult to manage. Most north-American lumber sawmills apply a make-tostock production strategy, some accepting/refusing orders according to available-to-promise (ATP) quantities, while a few uses more advanced approaches. This article introduces a simulation framework allowing comparing and evaluating different production planning strategies as well as order management strategies. A basic ERP system is also integrated into the framework (inventory management, lumber production planning algorithms, ATP and CTP calculation, etc). The user can configure the production planning and order management process, and evaluate how they will perform in various market contexts using the discrete event simulation model.

No abstract

Sawmilling activities in softwood mills (i.e., wood-sawing, drying, and finishing) cannot be efficiently planned at the operational level in a centralized manner because of the complexity of the production process. Sawmills plan their activities in a decentralized manner (although they try to coordinate them). Thus, specific mathematical models have been developed over the years to support planning for each activity. In the literature, these planning models are usually evaluated and tested independently, or connected using heuristics and evaluated for a fixed demand–planning horizon, assuming a known demand for the entire planning period. In this study, we simulate the use of planning models for decentralized sawmill production, but in a context where new orders arrive randomly and replanning is carried out periodically using a rolling horizon. We also simulated and evaluated different coordination mechanisms at the operational level, highlighting that previously published coordination mechanisms for decentralized planning of sawmilling operations may lead to a low order-fill rate when used in such a dynamic environment. We then propose a more advanced push–pull coordination mechanism based on the concept of decoupling point, revealing that this new mechanism may be more appropriate regarding the market characteristics considered in the study, while leading to a sales increase and reduced inventory. Actual numbers vary depending on specific market conditions.

Various optimization tools have been used in industry to facilitate production planning at different levels of aggregation. Choosing the interoperability mechanisms of these systems, such as the planning frequencies, the information passed between them and the interpretation that other systems must make of them, has always been a challenge. This work focusses on production planning at the tactical and operational levels in North American sawmills, a commodity industry characterized by volatile prices and a divergent production process with coproduction. In this context, tactical planning produces aggregated plans, and information from these plans can be used as targets and / or constraints at the operational level (e.g. quantities to be produced / kept in stock per product and per period, sales targets, etc.). A simulation of this production system was therefore developed, encompassing the planning process and the market dynamic, to compare and evaluate the impact of different coordination approaches on business economic performance. Results showed that the type of information which should be shared from the tactical level to the operational level varies according to several factors, including the company's order acceptance policy, prices seasonality, and the presence or absence of overcapacity on the market.