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Personne :
Gaudreault, Jonathan

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Gaudreault

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Jonathan

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Université Laval. Département d'informatique et de génie logiciel

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ncf10571965

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Voici les éléments 1 - 10 sur 28
  • PublicationAccès libre
    Configuration and evaluation of an integrated demand management process using a space-filling design and Kriging metamodeling
    (Elsevier, 2018-01-09) Gaudreault, Jonathan; Carle, Marc-André; Ben Ali, Maha; D'Amours, Sophie
    Objective This research aims to develop a basic understanding of a demand management process integrating sales and operations planning (S&OP) and order promising in a Make-To-Stock environment and to compare different demand management policies with limited capacity. Contribution Typical researches about demand management processes analyze few system specifications or vary few potential factors one at a time. Yet, additional insights can be obtained by employing a space-filling design and Kriging metamodeling for analysis. Methodology We compare two configurations of the integrated demand management process. While the First-Come First-Served concept is used at the order promising level for the first configuration, the second configuration uses nested booking limits and gives advantage to profitable customers and attractive periods. Considering various order arrival sequences, we generate Kriging metamodels that best describe the nonlinear relationships between four environmental factors (demand intensity, demand forecast error, customer heterogeneity and coefficient of variation) and three performance measures (yearly profit margin, yearly sales and high-priority fill rate) for Canadian softwood lumber firms. Since our simulation experiments are time-consuming, we employ a Latin hypercube design to efficiently take into account different market situations. Results Our analysis reveals the potential to improve the performance of the demand management process if we know high-priority customers needs before fulfilling low-priority orders and if we use nested booking limits concept.
  • PublicationRestreint
    Simulating an integrated revenue management approach in a production system with product substitution
    (Institute of Electrical and Electronics Engineers, 2019-02-04) Gaudreault, Jonathan; Carle, Marc-André; Ben Ali, Maha; D'Amours, Sophie
    Most revenue management publications dealing with substitutable products in a manufacturing context have focused on pricing issues. They consider that substitution is a customer’s decision which occurs as a response to product price differences. In our study, substitution is considered as the firm’s policy. We focus on the extension of the revenue management to practical applications in manufacturing and we are motivated by the Canadian softwood lumber case where product substitution is a common demand fulfillment practice. We aim, first, to propose a generic consumption model integrating both capacity control and product substitution decisions and second, to evaluate, using a rolling horizon simulation, the performance of this integrated model in different settings compared to common demand fulfillment approaches. In addition to practical implications, our study contributes to the existing demand fulfillment literature since we simulate different consumption models integrated with a Sales and Operations Planning model.
  • PublicationAccès libre
    Toward digital twins for sawmill production planning and control : benefits, opportunities and challenges
    (Taylor and Francis, 2022-05-12) Morin, Michael; Chabanet, Sylvain; Gaudreault, Jonathan; El-Haouzi, Hind Bril; Thomas, Philippe; Chabanet, Sylvain; El-Haouzi, Hind Bril
    Sawmills are key elements of the forest product industry supply chain, and they play important economic, social, and environmental roles. Sawmill production planning and control are, however, challenging owing to severalfactors, including, but not limited to, the heterogeneity of the raw material. The emerging concept of digital twins introduced in the context of Industry 4.0 has generated high interest and has been studied in a variety of domains, including production planning and control. In this paper, we investigate the benefits digital twins would bring to the sawmill industry via a literature review on the wider subject of sawmill production planning and control. Opportunities facilitating their implementation, as well as ongoing challenges from both academic and industrial perspectives, are also studied.
  • PublicationRestreint
    Chaînes de création de valeur
    (Éditions MultiMondes, 2009-01-01) Martel, Alain; Frayret, Jean-Marc; Gaudreault, Jonathan; D'Amours, Sophie; LeBel, Luc
  • PublicationRestreint
    Motivations for multi behavior agents in supply chain planning
    (Édition Tec & doc-Lavoisier, 2008-01-01) Frayret, Jean-Marc; Gaudreault, Jonathan; Forget, Pascal; D'Amours, Sophie
    In today’ industrial context competitiveness is closely associated to supply chain performance. Coordiantion between production partners is essential in supply chains to deliver products on time to final clients. As perturbations occur all the time, production centers have to react quickly correct deviances and create new plans, while coordinating changes with partners. Agent-based technology provides a natural approach to model supply chain networks and describe specialized planning agents. To coordinate and optimize their production plan, agents ue specify the heuristic parameters a priori, at the time of their design and prior to their use. The solution proposed here is to give agents the opportunity to change these parameters, modifying their planning behaviors following the environmental conditions met. Using simulation, agents can identify optimal team behaviors for the supply chain in different situations. This paper explains the methodology followed to experiment multi-behavior agents and presents results from an application to the lumber supply chain.
  • PublicationRestreint
    Coordination mechanism design in supply chains using multi-behaviour agents
    (Olney Inderscience Enterprises, 2010-07-19) Frayret, Jean-Marc; Gaudreault, Jonathan; Forget, Pascal; D'Amours, Sophie
    In today's industrial context, competitiveness is closely associated with supply chain performance. The ongoing development of integrated supply chains has increased the importance of supply chain management. This paper focuses on the design of coordination mechanisms that determine how partners interact to coordinate their production planning. We present a simulation tool to aid in the design of coordination mechanisms using multi-behaviour agents in an agent-based planning system where agents act as partners. The implementation of this solution is realised through the FORAC agent-based planning platform, which is dedicated to supply chain production planning and simulation for the lumber industry.
  • PublicationAccès libre
    Vine copula-based data generation for machine learning with an application to industrial processes
    (2022-12-02) Sexton, Jean-Thomas; Morin, Michael; Gaudreault, Jonathan
    Synthetic data generation of industrial processes exhibiting non-stationarity and complex, non-linear dependencies between their inputs and outputs is a challenging task. We argue that vine copula models are particularly well suited for this problem and present a method combining limited available data and expert knowledge in order to generate synthetic data by conditionally sampling from a C-Vine, a type of vine copula. We demonstrate our approach by generating synthetic data for a high-speed, sophisticated lumber finishing machine called a wood planer.
  • PublicationAccès libre
    Quality of sawmilling output predictions according to the size of the lot - The size matters!
    (2021-05-07) Morin, Michael; Gaudreault, Jonathan; Vallerand, Steve; Martineau, Vincent
    Lors de l'évaluation de modèles d'apprentissage automatique supervisé, on considère généralement le rendement de prédiction moyen obtenu sur les tests individuels comme mesure de choix. Toutefois, lorsque le modèle est destiné à prédire quels produits du bois seront obtenus lors du sciage de certains billots, c'est généralement la performance pour un lot complet qui importe. Dans cet article, nous montrons l'impact de cette nuance en termes d'évaluation du modèle. En fait, la qualité d'une prédiction (globale) s'améliore considérablement lorsque l'on augmente la taille des lots, ce qui offre un solide soutien à l'utilisation de ces modèles en pratique.
  • PublicationRestreint
    Intégration d'outils APS dans une simulation multi-agent : une application à l'industrie du bois d'œuvre
    (Tec & Doc, 2008-01-01) Frayret, Jean-Marc; Gaudreault, Jonathan; Lemieux, Sébastien; D'Amours, Sophie
    Ces travaux proposent l’intégration d’un système avancé de planification pour l’industrie du sciage de bois résineux dans une simulation multi-agent. L’objectif visé est de permettre la simulation de différences conditions du marché afin de d’évaluer et de comparer l’impact économique de stratégies de pilotage ou de gestion de la demande dans un réseau de création de valeur. Dans cet article, un simulateur à base d’agents est présenté de même qu’un agent simulant le comportement des clients. Un cas d’étude (Virtual Lumber Case) est présenté afin d’illustrer le potentiel d’utilisation du simulateur. Ce cas représente une entreprise canadienne de production de bois d’œuvre, de taille moyenne. Le développement du cas VLC constitue un maillon clé dans le développement de cette recherche; il facilite la création de scénarios de simulation et l’étude de différentes stratégies propres à l’industrie des produits forestiers.
  • PublicationAccès libre
    Neural network architectures and feature extraction for lumber production prediction
    (Canadian Artificial Intelligence Association, 2021-06-08) Martineau, Vincent; Morin, Michael; Gaudreault, Jonathan; Thomas, Philippe; El-Haouzid, Hind Bril; Antonie, Luiza; Moradian Zadeh, Pooya
    We tackle the problem of predicting the lumber products resulting from the break down of the logs at a given sawmill. Although previous studies have shown that supervised learning is well suited for that prediction problem, to our knowledge, there exists only one approach using the 3D log scans as inputs and it is based on the iterative closest-point algorithm. In this paper, we evaluate the combination of neural network architectures (multilayer perceptron, residual network and PointNet) and log representation as input (industry know-how-based features, 2D projections, and 3D point clouds) in the context of lumber production prediction. Our study not only shows that it is possible to predict the output of a sawmill using neural networks, but also that there is value in combining industry know-how-based features and 3D point clouds in various network architectures.