Toward digital twins for sawmill production planning and control: benefits, opportunities, and challenges

Figures & data

Figure 1. Overview of a forest product supply chain

A general diagram of a forest product supply chain, including forests, a sawmill, different other facilities, and customers.

Figure 2. Life cycles of products and processes

This figure presents the life cycles of a production facility and products, from conception to end of life. These life cycles are orthogonal and cross at the production phase.

Figure 3. Distribution of the number of published articles per publication dates from 1980 and before to 2020.

Figure 4. Pie chart of the nationalities of author institutions for the articles gathered during the literature review.

Pie chart of the nationalities of author institutions for the gathered articles. Nearly 50% of the authors are Canadian.

Figure 5. Keyword graph of the selected articles.

Graph of the articles keywords. Nodes represent keywords and links show the co-occurrence of two keywords in an article.

Table 1. Examples of articles studying common planning problems from the sawing industry.

Planning problem	References
Sawing operations	Haberl et al. (1991), Maness and Adams (1991), Reinders (1992), Sinclair and Erasmus (1992), Reinders (1993), Todoraki and Ronnqvist (2001), Donald, Maness, and Marinescu (2001),Maness and Norton (2002), Corro, Singer, and Donoso (2007), Caballero et al. (2009), Pradenas, Alvarez, and Ferland (2009), Zanjani, Ait-Kadi, and Nourelfath (2010), Kazemi Zanjani, Nourelfath, and Ait-Kadi (2010), Kazemi Zanjani, Nourelfath, and Aït-Kadi (2011), Kazemi Zanjani, Ait-Kadi, and Nourelfath (2013), Zanjani, Ait-Kadi, and Nourelfath (2013), Pradenas et al. (2013), Zanjani, Nourelfath, and Ait-Kadi (2013b), Arabi (2013), Marier et al. (2014), Alvarez and Vera (2014),Lindner, Vlok, and Wessels (2015), Lobos and Vera (2016), Palma and Vergara (2016),Huka and Gronalt (2017), Wery et al. (2018), Galvez, Borenstein, and da Silveira Farias (2018), Vanzetti et al. (2018), Vanzetti, Broz, Corsano, et al. (2019a), Broz et al. (2019), Vanzetti, Broz, Montagna, et al. (2019b), Alvarez et al. (2020), Pradenas, Bravo, and Linfati (2020)
Drying operations	Sinclair and Erasmus (1992), Donald, Maness, and Marinescu (2001), Corro, Singer, and Donoso (2007), Gaudreault et al. (2011), Cifuentes, Gatica, and Linfati (2017), Theresia, Widyadana, and Wahjudi (2019), Vanzetti, Corsano, and Montagna (2020), Pradenas, Bravo, and Linfati (2020), Huka, Rindler, and Gronalt (2020), Marier, Gaudreault, and Noguer (2021)
Finishing operations	Sinclair and Erasmus (1992), Donald, Maness, and Marinescu (2001), Maness and Norton (2002), Corro, Singer, and Donoso (2007), Marier, Gaudreault, and Robichaud (2014), Baesler and Palma (2014), Gaudreault et al. (2011), Pradenas, Bravo, and Linfati (2020)
Coordination mechanisms	Donald, Maness, and Marinescu (2001), Wessels et al. (2006), Frayret et al. (2007), Cid et al. (2007), Singer and Donoso (2008), Forget et al. (2009), Cid Yáñez et al. (2009), Beaudoin, Frayret, and LeBel (2010), Marinescu and Maness (2010), Gaudreault et al. (2010), Santa-Eulalia et al. (2011), Gaudreault et al. (2012), Jerbi et al. (2012), Alayet et al. (2013), Arabi (2013), Morneau-Pereira et al. (2014), Bajgiran, Zanjani, and Nourelfath (2014), Paradis et al. (2015), Dumetz et al., “Planning and Coordination”  (2017), Vanzetti, Broz, Corsano, et al. (2019a), Vanzetti, Broz, Montagna, et al. (2019b), Fuentealba et al. (2019), Pradenas, Bravo, and Linfati (2020)

Note: An article can be placed in several cells if it tackles or integrates several planning steps.

Table 2. Articles gathered during the literature review using metaheuristics.

Reference	Metaheuristic	Problem characteristics
Pradenas, Peñailillo, and Ferland (2004)	Tabu search	Optimisation of monthly operation. The problem was modelled as an MIP model with quadratic constraints
Caballero et al. (2009)	Scatter Search Procedure for Multiobjective Optimisation (SSPMO)	Operational production planning, modelled as a multiobjective nonlinear integer model
Lindner, Visser, and Wessels (2013)	Probability-based incremental learning	Simultaneous optimisation of primary and secondary sawing operations
Pradenas et al. (2013)	Genetic algorithm or simulated annealing	Sawing operation planning over a few days horizon. Metaheuristics are used to generate sawing patterns and solve the subsequent integer programming problem
Baesler and Palma (2014)	Memetic algorithm	Scheduling of finishing operations (moulding) on a set of parallel machines
Lindner, Vlok, and Wessels (2015)	Population-based incremental learning algorithm	Optimising simultaneously machine settings at two points of the production line
Shahi and Pulkki (2015)	A commercial solver was used, which is based on scatter search and tabu search procedures	Inventory optimisation to minimise daily costs of three simulated agents representing a forest company, merchandising log yard, and sawmill
Huka, Rindler, and Gronalt (2020)	Tabu search	Scheduling of drying operations. The metaheuristic is used to improve upon the results of the first heuristic solution. The problem was modelled as a nonlinear MIP model

Table 3. Articles implementing specific optimisation methods to deal with uncertainty in the planning process.

Reference	Uncertainty	Solution method
Vila, Beauregard, and Martel (2009)	Demand	Stochastic programming
Zanjani, Ait-Kadi, and Nourelfath (2010)	Process yield	Robust optimisation
Kazemi Zanjani, Nourelfath, and Ait-Kadi (2010)	Raw material quality and demand	Stochastic programming
Kazemi Zanjani, Nourelfath, and Aït-Kadi (2011)	Raw material quality	Stochastic programming
Vahidian (2012)	Process yield and demand	Stochastic programming
Zanjani, Nourelfath, and Ait-Kadi (2013a)	Process yield, products demand	Robust optimisation, stochastic programming
Zanjani, Ait-Kadi, and Nourelfath (2013)	Process yield and demand	Stochastic programming
Kazemi Zanjani, Ait-Kadi, and Nourelfath (2013)	Processed yield	Stochastic programming
Zanjani, Nourelfath, and Ait-Kadi (2013b)	Process yield and demand	Stochastic programming
Varas et al. (2014)	Raw material supply and demand	Robust optimisation
Alvarez and Vera (2014)	Process yield	Robust optimisation
Palma and Vergara (2016)	Manager preferences among objectives	Robust optimisation
Lobos and Vera (2016)	Log supply	Stochastic programming
Alvarez et al. (2020)	Process yield	Robust optimisation

Table 4. List of articles collected during the literature review using multi-agent simulation technologies.

Reference	Main agents	Simulation objective
Frayret et al. (2007)	Source, Sawing, Drying, Finishing, Deliver and Warehouse agents	Design and test distributed planning strategies. This study focuses on the introduction of the FORAC agent simulation platform
Cid et al. (2007)	Sawing, Drying and Planning agents	Evaluate different planning strategies, especially in terms of push-pull decoupling points, under several scenarios
Forget, D'Amours, and Frayret (2008)	Planning and Customer agents	While focusing on a general agent architecture this article presents a use case in the lumber industry. The use case is used to assess the impact of the reception of a new demand plan by the planning agent
Lemieux et al. (2009)	Source, Sawing, Drying, Finishing, Deliver and Customer agents	Evaluate different tactical planning strategies under various market situations
Cid Yáñez et al. (2009)	Sawing, Drying and Finishing agents	Compare planning strategies in terms of push-pull decoupling points
Forget et al. (2009)	Source, Sawing, Drying, Finishing, Warehouse and Customer agents	Compare operational planning behaviours, such as agents coordination mechanisms
Gaudreault, Frayret, and Pesant (2009)	Sawing, Drying and Finishing agents	Coordinate operations on a short-term horizon
Gaudreault et al. (2010)	Sawing, Drying and Finishing agents	Evaluate coordination mechanisms
Beaudoin, Frayret, and LeBel (2010)	Mandated and Procured agents, representing forest companies. Each agent owns a mill, but only the mandated agent manages the harvest	Coordinate wood procurement planning among several companies, as well as procurement and production within a company
Santa-Eulalia et al. (2011)	Source, Sawing, Drying, Finishing and Deliver agents	Compare planning policies, in terms of horizon, control level and planning method
Vahid (2011)	Each existing economic player in the modelled supply chain (i.e. sawmills and log yards) is represented by an agent	Solve strategic problems, including the placement of new facilities to maximise the total profit of the supply chain
Gaudreault et al. (2012)	Sawing, Drying and Finishing agent	Evaluation of a coordination mechanism, based on an efficient search in a solution space
Shahi and Pulkki (2015)	Sawmill storage, Merchandising yard and Forest management unit agents	Optimise an inventory policy to help tactical and operational decision-making

Figure 6. Outline of the components essential to a sawmill DT.

A DT block containing historic data as well as predictive and decision support models, exchanging data and information with the physical sawmill.

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Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.