Simulation combinée des processus de production et des processus de pilotage : analyse comparative de stratégies de pilotage pour la production de bois d'oeuvre

Dans le cadre de ce travail de thèse, nous avons conçu une plateforme de simulation permettant l’évaluation comparative de stratégies de pilotage pour la production de bois d’œuvre dans les scieries nord-américaines. Dans notre contexte, une stratégie de pilotage est composée de plusieurs paramètres tels que le choix des politiques d’acceptation des commandes, permettant d’accepter ou de refuser une commande en fonction de règles mises en place, le choix des modèles et algorithmes de planification utilisés à chaque étape de la production de bois d’œuvre, le choix du modèle au niveau tactique, les mécanismes de coordination utilisés, permettant de mieux coordonner les opérations de plusieurs entités distinctes ou de plusieurs niveaux de planification ; on parle notamment d’échange d’informations circulant entre les niveaux de planification tactique et opérationnel ou encore entre les entités/modèles utilisés au niveau opérationnel pour planifier la production de bois d’œuvre. Lors de la planification des opérations, les industriels doivent mettre en place ces stratégies de pilotage. Aujourd’hui, il est extrêmement compliqué de savoir quelle stratégie de pilotage mettre en place en fonction de son propre contexte de marché et de ses paramètres de production. L’objectif général est donc est de permettre d’évaluer et comparer des stratégies de pilotage aux niveaux tactique et opérationnel pour la production de bois d’œuvre, tout en tenant compte du contexte de marché de l’entreprise ainsi que de ses paramètres de production. Pour atteindre cet objectif, nous l’avons divisé en quatre objectifs spécifiques qui ont donnés lieu à trois publications. Pour notre premier objectif spécifique, nous avons développé un modèle de simulation permettant de représenter la génération, l’acceptation et la vente d’une commande pour une entreprise de sciage. Un module de planification de la production a également été couplé et est responsable de la gestion des stocks et de la génération des plans de production. Pour notre deuxième objectif spécifique, nous avons utilisons ce modèle de simulation pour pouvoir évaluer l’impact de politiques d’acceptation des commandes (telles que Availableto-promise (ATP), Capable-to-promise (CTP) ou encore On-Stock) sur les performances de l’entreprise en termes de volume de commandes acceptées dans un environnement à flux de produits divergent avec co-production. Bien que ces politiques d’acceptation des commandes aient été largement étudiées dans un contexte manufacturier traditionnel, le choix d’une politique plutôt qu’une autre est loin d’être trivial dans un tel contexte de divergence de flux physique. Nous montrons dans cette première contribution que dans ce type de contexte, le choix d’une politique d’acceptation de commande plutôt qu’une autre dépend fortement du marché et impacte fortement les performances de l’entreprise, en termes de commandes acceptées et de stock moyen annuel. Cet objectif spécifique a entrainé l’écriture d’un premier article. Pour notre troisième objectif spécifique, nous avons évalué des mécanismes de coordination mis en place au niveau opérationnel entre les différentes activités du processus de transformation de bois d’œuvre, qui est un processus décentralisé. La précédente plateforme de simulation a donc été adaptée et des mécanismes de coordination déjà publiés tels que « Twophases planning », ou « bottleneck-first planning » y sont évalués en utilisant un horizon roulant dans un environnement où les commandes sont générées dynamiquement. Nous montrons que les mécanismes de coordination déjà publiés et testés dans un environnement statique performent mal dans un environnement dynamique. Nous proposons donc un autre mécanisme de coordination « hybride flux poussé / flux tiré » exploitant le concept de point de découplage. Ce mécanisme s’avère meilleur que les précédents en permettant un plus grand nombre de ventes, ainsi qu’une réduction des stock moyens. Cet objectif spécifique a entrainé l’écriture d’un deuxième article. Enfin, pour notre quatrième objectif spécifique, nous nous intéressons à la planification de la production aux niveaux tactique et opérationnel. Nous utilisons le modèle de simulation pour comparer et évaluer l’impact de différents types d’informations transmises du niveau tactique au niveau opérationnel. Le niveau de planification tactique est alors pris en compte pour établir une planification à plus long terme. Nous montrons que le choix du type d’informations à transmettre du niveau tactique au niveau opérationnel varie selon plusieurs facteurs, tels que : la politique d’acceptation des commandes (ATP, CTP) utilisée par l’entreprise, l’ampleur de la saisonnalité des prix de vente, ou le fait d’être ou non dans un marché en surcapacité. Cet objectif spécifique a entrainé l’écriture d’un troisième article.In this thesis, we designed a simulation platform to compare and evaluate production planning and order management strategies for lumber production in North American sawmills. In our context, a strategy is composed of several parameters such as the choice of order acceptance policies, allowing to accept or refuse an order based on implemented rules, the choice of planning models and algorithms used at each stage of timber production, the choice of model at the tactical level, the coordination mechanisms used, to better coordinate the operations of several distinct entities or of several planning levels; this includes the exchange of information between tactical and operational planning levels or between entities / models used at the operational level to plan timber production. Today, it is extremely difficult for a company to know which management strategy to put in place. The general objective is then to evaluate and compare tactical and operational planning strategies for timber production, taking into account the company's market context and its production parameters. To achieve this goal, we divided it into four specific objectives that resulted in three publications. In the first specific objective, we developed a simulation model to represent the generation, acceptance and sale of an order for a sawmill. We coupled a production planning module to this simulation model that is responsible for inventory management and the generation of production plans. In a second objective, we use this simulation model to be able to evaluate the impact of order acceptance policies such as Available-to-promise (ATP), Capable-to-promise (CTP) and Stock policies on the company’s performance in terms of volume of accepted orders in a product flow environment diverge with co-production. Although these order acceptance policies have been widely studied in a traditional manufacturing context, the choice of one policy over another is far from being trivial in such a context of divergence flow. We show that in this type of context, the choice of an order acceptance policy rather than another depends strongly on the market and impacts the performance of the company, in terms of accepted orders and average annual inventory. This specific objective leads to the first publication. In a third specific objective, we evaluated coordination mechanisms used at the operational level between the different activities of the timber processing process, which is a decentralized process. The previous simulation platform has been adapted and previously published coordination mechanisms such as "Two-phase planning" or "bottleneck-first planning" are evaluated using a rolling horizon in an environment where orders are generated dynamically. We show that coordination mechanisms already published and tested in a static environment perform poorly in a dynamic environment. We therefore propose another "hybrid push / pull" coordination mechanism exploiting the decoupling point concept. This mechanism is better than the previous ones by allowing a greater number of sales, as well as a reduction in average inventory. This specific objective leads to a second publication. Finally, in a fourth specific objective, we are interested in production planning at the tactical and operational levels. We use the simulation model to compare and evaluate different information transmitted from the tactical level to the operational level by simulating the production system, the planning process and the market behavior. The tactical planning level is then taken into account to establish longer-term production planning. We show that the choice of the type of information to be transmitted from the tactical level to the operational level varies according to several factors, such as: the order acceptance policy (ATP, CTP) used by the company, the extent of seasonality selling prices, or whether or not being in an overcapacity market. This specific objective leads to third publicatio

Analysing service level agreements with multiple customers.

Within numerous production and distribution environments, maintenance of effective customer service is central to securing competitive benefits. Globalised industries are becoming more commonplace as well, further increasing the competitive pressure. Companies, as a result, are forced to expand product availability and deliver to the demand on schedule. As part of a supply chain, service levels are an important measure of performance in operations management and are widely used to evaluate and manage supplier performance. This thesis examines the SLA for the supplier under two types of contracts to guarantee the agreed customer service level. Specifically, this dissertation will shed light on the two most important (SLA) measurements for inventory systems: fill rate and ready rate. Both SLA measurements are commonly used as performance measures in SLAs between customers and suppliers. Throughout this thesis, we examine performance-based contracts in which the supplier has either: a single customer with a large demand, or multiple customers with a smaller demand. Our experiments were designed so that the demand distribution for the single customer case was similar to the aggregated demand distribution in the multiple customer case. The thesis primarily focused on four main questions, with each question being examined in its own chapter. The first research problem is addressed in Chapter 3. Earlier studies of finite horizon fill rate only consider the situation in which there is a single customer in the supply chain. In Chapter 3, we develop a model to analyse the fill rate distributions for a supplier that has multiple customers, each with its own SLA. In particular, we examine the impacts of performance review period length and the correlation between customer demands on the average fill rate and the probability of overreaching the target fill rate when a supplier has multiple customers. Under the multiple customer contracts, two service policies for demand fulfilment. In the first policy, First-Come-First-Served (FCFS), demand is filled with no prioritization (e.g., in the case of two customers, there is a 50% chance that the first customer is served first). In the second policy, Prioritized Lowest Fill Rate (PLFR), customers are prioritized so that the customer with the highest negative deviation from its target fill rate in the current performance review period is served first. The results and findings in Chapter 3 provide insights that can assist suppliers in the design and negotiation of SLAs. The second research problem is addressed in Chapter 4. Previous studies on the finite horizon fill rate are limited and assume a zero lead time for the supplier. We create a model to examine the impact of different supplier lead times on the finite horizon fill rate, considering either single customer or multiple customers. As lead time exists in reallife supply chains, we explore the effect of various lead times on the fill rate distribution and required base stock over finite horizons with a variety of review period lengths. The results revealed that to fix the long-run fill rate, as the lead time increases, more stock is required; however, the probability of exceeding the target fill rate (the probability of success) increases as the lead time increases. The results indicate that the increase in the probability of success as the lead time increases is higher when the review period is shorter. For the third research problem Chapter 5 presents further results related to the fill rate, an important measure of supply chain performance, specifically ensuring that a customer’s service need is met with maximum reliability. These results mainly concentrate on variability, an aspect that is largely ignored in the literature on fill rate. Related results concerning consistency and asymptotic normality extend the range of application of the fill rate in evaluating reliability and determining the optimal stock level of a supply chain. Chapter 6 explores the fourth research problem which considers the ready rate, a widely used performance measure in SLAs. The ready rate considered in this study is defined as the long-run fraction of periods in which all customer demand is filled immediately from on-hand stock. Previous studies of SLAs have been solely concerned with one supplier serving one customer, whereas in practice, a supplier usually deals with more than one customer. In multiple customer cases, the supplier has an SLA with each customer, and a penalty is incurred whenever the agreement is violated. In this chapter, we create a model to examine the impacts of various factors such as the base-stock level, the type of penalty (lump-sum and linear penalty), and the review period duration on the supplier’s cost function when the supplier deals with multiple customers. The results show that dealing with more customers is preferable for a supplier (assuming the overall demand is the same) and that under a lump-sum penalty contract, a longer performance review is beneficial. Finally, Chapter 7 closes with a brief review, discussion on the models constructed and suggests areas for future studies