Approches intégrées de gestion de la demande dans l'industrie de bois d'œuvre

Authors: Ben Ali, Maha
Advisor: D'Amours, SophieGaudreault, Jonathan
Abstract: This thesis addresses the need of softwood lumber firms operating in a supply-constrained environment and facing heterogeneous and seasonal market, to synchronize between the different business units of supply chain and to maximize profits. The objective is to develop and to evaluate new integrated demand management approaches for limited capacity contexts in a way to maximize profits and enhance the service level offered to high-priority customers. Our case study, inspired from softwood lumber manufacturers located in Eastern Canada, considers heterogeneous customers, divergent production processes and several mills considered as an MTS environment since operations and sales plans are driven by forecasts. In this thesis, we first define a multilevel decision framework in order to support mediumterm, short-term and real-time sales decisions. We propose a demand management process integrating sales and operations planning (S&OP) and revenue management (RM) concepts : we present a new mathematical formulation integrating an S&OP network model in the softwood lumber industry and an order promising model using nested booking limits. This formulation offers the possibility of changing decisions of how confirmed orders have to be fulfilled as late as possible, which we called order reassignment. Considering current demand management practices and existing IT-systems, we developed a simulationoptimization platform in order to evaluate the demand management process performance the benefits of integrating S&OP and RM concepts in various scenarios. Simulation results provide evidence of the value of integrating RM and S&OP and show that we can offer better service level to high-priority customers and higher profit margin compared to common demand management practices. The simulation-optimization platform is used, in a second step, to investigate how an integrated demand management process, that can be configured differently, can perform facing various order arrival sequences and market disturbances. For this purpose, we use relatively novel techniques – a space-filling design and Kriging metamodeling – in supply chain settings to address the impact of decision and environmental factors on the performance of the integrated demand management process. The simulation results affirm the use of nested booking limits can be a powerful tool to maximize revenues facing different environmental conditions. We also show how order arrival sequence can play a relevant role, especially with a high customer heterogeneity. In addition, as motivated by an industrial problem, we discuss the potential implications of the analysis presented for firms operating in supplyconstrained environments, such as Canadian softwood firms. As a third step, we investigate the benefits of integrating revenue management and product substitution in a manufacturing context. We particularly examine the situation when a higher quality substitute is provided at the original product’s price, which is called an upgrade. Upgrading is a common demand fulfillment practice in the Canadian softwood lumber industry. Thus, we generalize the order promising model using nested booking limits and we add a product dimension to enable product substitution. Then, we conduct a rolling horizon simulation in order to compare different demand fulfillment approaches. The simulation results demonstrate that integrating RM and upgrading achieves better performance than common demand fulfillment approaches in a limited capacity context. The value of upgrading is more significant when integrated with RM concepts since the use of nested booking limits prevents from doing unprofitable upgrades. Thus, inventories are preserved for future profitable orders.
Document Type: Thèse de doctorat
Issue Date: 2018
Open Access Date: 15 October 2019
Permalink: http://hdl.handle.net/20.500.11794/36893
Grantor: Université Laval
Collection:Thèses et mémoires

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