Since the 1990s, facing increasing competition and mass customization, many companies including Dell have chosen to adopt the assemble-to-order (ATO) model in order to increase products offering and reduce the life cycles of products. Inventory management is a key challenge for ATO systems, in particular determination of inventory replenishment levels without full demand information, component allocations based on available component inventories, and realizations of product demands. ATO systems are usually modeled as a two-stage stochastic integer program. However, such programs are typically hard to solve, especially for stochastic integer nonlinear programs used for the joint optimization. In this thesis, we describe two ATO models proposed by Ackay and Xu (2004) and by Huang (2014). Both models include a nonlinear term in the right hand side of the inventory availability constraints. We discuss the techniques used to linearize the original problem and to estimate the impact of the linearization. In addition, we investigate another key element of ATO systems called component commonality used to reduce inventory costs. An extensive literature review regarding component commonality is provided. / Thesis / Master of Science (MSc)

Lowering the degree of component commonality may yield a higher type-II service level for a periodic review assemble-to-order system that aims to maximize reward. This is achieved via separating inventories of all the shared components for different products. We investigate the optimal bill-of-materials structure for two-product assemble-to-order systems with arbitrary number of components. The inventory of a shared component can be separated or common between different products. We show that an optimal bill-of-materials can be characterized between the following two extremal configurations: either two products share all common components, or they do not share any common component. / Thesis / Doctor of Philosophy (PhD)

Les systèmes assemble-to-order (ATO) peuvent être considérés comme une affectation de ressources multiples qui induit planification de production, satisfaction des contraintes et affectation des stocks. Les systèmes ATO représentent une stratégie de logistique populaire utilisée en gestion de fabrication. En raison de la complexité croissante des systèmes de fabrication d'aujourd'hui, le défi pour les systèmes ATO est de gérer efficacement les stocks de composants et de trouver les décisions optimales de production et d'affectation.Nous étudions un système ATO avec un produit unique qui est assemblé à partir de plusieurs composants. Le système doit répondre à une demande non seulement du produit assemblé, mais aussi des composants individuels. Nous considérons le cas avec seulement des lost sales puis le cas mixte lost sales et backorders avec des temps de production suivant des lois de type exponentiel et une demande sous forme de loi de Poisson. Nous formulons le problème comme un Processus de décision markovien (MDP), et nous considérons deux critères d'optimalité qui sont le coût actualisé et le coût moyen par période. Nous caractérisons la structure de la politique optimale et étudions l'impact des différents paramètres du système sur cette politique. Nous présentons également plusieurs heuristiques pour le cas lost sales et le cas mixte lost sales et backorders. Ces heuristiques fournissent des méthodes simples, mais efficaces pour contrôler la production et l’affectation des stocks du système ATO / Assemble-to-order (ATO) systems can be regarded as a multiple resource allocation that induces production planning, requirements fulfilling and inventory assignment. ATO is a popular strategy used in manufacturing management. Due to the increasing complexity of today’s manufacturing systems, the challenge for ATO systems is to efficiently manage component inventories and make optimal production and allocation decisions. We study an ATO system with a single product which is assembled from multiple components. The system faces demand not only from the assembled product but also from the individual components. We consider the pure lost sales case and the mixed lost sales and backorders case with exponential production times and Poisson demand. We formulate the problem as a Markov decision process (MDP), and consider it under two optimality criteria: discounted cost and average cost per period. We characterize the structure of the optimal policy and investigate the impact of different system parameters on the optimal policy. We also present several static heuristic policies for the pure lost sales and the mixed lost sales and backorders cases. These static heuristics provide simple, yet effective approaches for controlling production and inventory allocation of ATO system