Tesi sul tema "Inventory in supply chain"

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management; and, (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.
Includes bibliographical references (p. 97).
by Jennifer Ann Felch.
M.S.

Supply chain management addresses the management of materials and

information across the entire chain from suppliers to producers,

distributors, retailers, and customers. In the past few decades, scholars

gave ample attention about the impact of inventory on Supply Chain

Management (SCM). Roughly speaking, research on supply chain management has

been mainly focused on three major issues. One is the behavior of

information flow; the second issue deals with inventory management; the

third issue is orientated to planning and operations management. In this

paper the second issue, namely inventory management will be discussed. The

author will follow the phases of classifying inventory; identify cost

factors; assess cost components; calculate EOQ; giving suggestion and

effect of inventory on supply chain will be discussed. The result is going

to become clear under the analysis of two alternatives by using MCDM

(Multiple Criteria Decision Making) method. The conclusion is when

optimizing the inventory management, both up stream and down stream

activities will run effectively.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Manufacturing Program at MIT, 2007.
Includes bibliographical references (p. 66-67).
Strategic inventory management has become a major focus for Honeywell Aerospace as the business unit challenged itself to meeting cost reduction goals while maintaining a high level of service to its customers. This challenge has become particularly important as customers have steered their purchase decisions from focusing only on capability and quality to including cost performance as well. To do so, Honeywell Aerospace's Planning and Asset Management group is undertaking a three-year effort to re-engineer its inventory planning systems with the goal of increasing planner productivity, improving supply chain responsiveness, and reducing overall inventory. This internship forms the building blocks of this strategy by leveraging existing software available in the industry and applying it to Honeywell's supply chain. Through two pilot programs with different supply chain designs, this internship analyzed the cost and benefit of transforming the company's inventory management strategy. In addition, this internship attempts to identify the challenges associated with such an enormous change, compare them with challenges with implementation in other industries in order to prepare management for full implementation across all product lines. These challenges range from leadership buy-in and information readiness to implementation feasibility both within Honeywell manufacturing and its suppliers.
by Billy S. Lo.
S.M.
M.B.A.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Manufacturing Program at MIT, 2008.
Includes bibliographical references (p. 79-80).
This paper introduces multiple methods to set and optimize inventory levels. These methods are then classified based on the complexity involved to implement them. As an organization develops a deeper understanding of inventory, it becomes more mature and can apply more complex methods. This sequencing of methods is defined as a three phase maturity model. First, a foundational level of maturity is defined, which quantifies inventory levels based on future demand and business requirements. Second, a transitional level of maturity defines safety stock positioning in a single-echelon supply chain. Finally, the maturity model concludes with an optimal level of maturity that is based on principles of multi-echelon inventory optimization: safety stock at multiple positions of a supply chain. The setting for this paper was the Aerospace industry. Honeywell Aerospace is in the middle of a 3-year effort to re-engineer Sales, Inventory and Operations Planning (SIOP) systems. At the same time, Honeywell Aerospace is standardizing on a uniform implementation of an ERP system. Through SIOP, standard inventory and planning practices aided by the uniform ERP backbone and a strategic inventory program executive management hopes to reduce what is seen as a disproportionate contribution of inventory to Honeywell International.
by Joseph Mauro.
S.M.
M.B.A.

L’environnement concurrentiel des affaires et la mondialisation oblige actuellement les entreprises à accorder une importance particulière à la performance de leur chaîne d’approvisionnement. Afin de se démarquer, les entreprises sont contraintes de prévoir et de gérer des paramètres de performance souvent contradictoires à savoir réduire le coût de leur chaîne d’approvisionnement et augmenter la qualité du service offert à leur clientèle. À cet égard, la planification intégrée de la chaîne logistique c’est-à-dire que les décisions relatives à la l’emplacement des usines, l’approvisionnement, la production, le stockage et la distribution s’avèrent majeures dans le gain d’efficience des entreprises et la réactivité d’une chaîne d’approvisionnement. La production et la planification de la distribution constituent deux opérations fondamentales dans la gestion de la chaîne logistique. Couramment, elles sont traitées de manière distincte du fait de leur complexité. Les coûts d’inventaire sont élevés dans cette approche dite aussi linéaire ou hiérarchique, eu égard à la nécessité de respecter les délais de traitement des commandes et d’assurer la satisfaction des clients. Cependant, il devient impératif de ne plus négliger les liens existants entre les décisions prises pour gérer la production et la distribution, afin de réaliser des économies de coûts dans la chaîne d’approvisionnement. Bien que l’intérêt pour la planification intégrée de chaîne d’approvisionnement soit grandissant, les modèles d’optimisation actuels laissent encore place à l’amélioration afin d’être plus réalistes. Dans cette recherche, nous étudions des problèmes logistiques riches et intégrés. La pertinence de notre apport réside dans l’ajout de variables opérationnelles telles que les fenêtres de temps de service ou la configuration de réseaux flexibles ainsi que de certaines caractéristiques environnementales, dans des modèles logistiques. Notre objectif est de mettre en évidence les valeurs d’intégration, en termes d’économies de coûts et de réduction de gaz à effet de serre. Premièrement, nous décrivons, modélisons et résolvons le problème qui se présent chez un partenaire industriel qui fabrique un seul produit. Dans ce système, la capacité de production et le niveau d’inventaire sont limités, les transferts inter-usines sont permis et les fenêtres de délais de livraison sont flexibles. En nous appuyant sur un vaste ensemble de données réelles collectées chez notre partenaire, nous comparons l’approche intégrée avec plusieurs scénarios de pratique courante. Nous utilisons une méthode exacte qui permet de résoudre chacun des scénarios et étudions les compromis entre les coûts et les niveaux de service dans une analyse de sensibilité détaillée. Les résultats obtenus démontrent ainsi comment l’application d’une approche synchronisée et holistique dans la prise de décision apporte de nombreuses opportunités bénéfiques pour les systèmes logistiques en général. Nous étendons par la suite notre étude aux systèmes de production multi-produits et multiéchelons. Cette nouvelle configuration du problème implique que les produits sont expédiés aux clients par l’intermédiaire d’un ensemble de centres de distribution dont le producteur peut contrôler l’emplacement. Dans cette analyse, la conception de notre réseau de transport est flexible puisqu’il peut varier au cours du temps. Plus le problème est riche et s’approche de la réalité, plus le problème devient difficile et compliqué à résoudre. Les meilleures solutions issues de l’approche intégrée sont obtenues au détriment d’une plus grande complexité d’implémentation et de l’allongement du temps d’exécution. Nous décrivons, modélisons et résolvons le problème en utilisant d’abord des approches de prise de décision intégrées puis des approches séquentielles afin de déterminer à quel le moment l’usage d’une approche plus complexe est avantageuse pour résoudre le problème. Les résultats confirment la pertinence de l’approche intégrée comparativement à l’approche séquentielle. Pour illustrer l’importance des économies réalisées grâce au caractère flexible de la conception de réseaux et des fenêtres de temps de livraison, nous décrivons, modélisons et résolvons un problème de localisation-tournées de vehicules intégré et flexible à deux échelons. Dans ce problème, le fournisseur livre la marchandise à ses clients grâce à un réseau d’approvisionnement à deux échelons, avec une pénalité pour chaque demande non réalisée dans la fenêtre de livraison prédéterminée. La problématique est ici traitée dans une configuration plus riche; la livraison est planifiée en tournées de véhicules. Le quatrième volet de cette thèse s’intéresse aux impacts environnementaux des décisions logistiques. En effet, le plus souvent, les recherches scientifiques sur l’optimisation des chaînes d’approvisionnement se concentrent uniquement sur les aspects économiques du développement durable et tendent à ignorer les deux autres dimensions. Nous abordons donc des problématiques d’optimisation connues sous de nouveaux angles. Nous étudions deux systèmes intégrés de production, d’inventaire, de localisation et de distribution dans lesquels une marchandise produite à une usine est livrée aux détaillants dans un horizon de temps fini. Une analyse de sensibilité élaborée nous permet d’améliorer nos connaissances sur les coûts et les émissions dans les chaînes d’approvisionnement intégrées, en plus d’améliorer notre compréhension des coûts associés à l’implantation de solutions respectueuses de l’environnement. Dans cette thèse, nous visons non seulement une meilleure compréhension de l’approche englobante de logistique intégrée mais nous développons également des outils opérationnels pour son application dans des cas complexes concrets. Nous proposons ainsi de nouveaux modèles d’affaires capables d’améliorer la performance de la chaine d’approvisionnement tout en développant des techniques d’implémentation mathématiques efficaces et efficientes. Mots Clés: Optimisation intégrée, Problème de dimensionnement dynamique de lots, Fenêtres de temps de livraison, Problèmes de localisation, Distribution.
Today’s challenging and competitive global business environment forces companies to place a premium upon the performance of their supply chains. The key to success lies in understanding and managing several contradicting performance metrics. Companies are compelled to keep their supply chain costs low and to maintain the service level high. In this regard, integrated planning of important supply chain decisions such as location, procurement, production, inventory, and distribution has proved to be valuable in gaining efficiency and responsiveness. Two fundamental operations in supply chain management are production and distribution planning. Traditionally, mainly due to the high complexity and difficulty of these operations, they have been treated separately. This hierarchical or sequential decision making approach imposes high inventory holding cost, as in the traditional approach inventory plays an important role in timely satisfying the demand. However, in the era of supply chain cost reduction, it is becoming increasingly apparent that the interrelations between different decisions, and especially production and distribution decisions, can no longer be neglected. Although the research interest in the integrated supply chain planning has been recently growing, there is still much room to further improve and make the existing models more realistic. Throughout this research, we investigate different rich integrated problems. The richness of the models stems from real-world features such as delivery time windows, flexible network designs, and incorporation of environmental concerns. Our purpose is to highlight the values of integration, in terms of cost savings and greenhouse gas emission reduction. First, we describe, model, and solve a plant-customer, single product setting in which production and inventory are capacitated and inter-plant transshipment is allowed. The problem is flexible in terms of delivery due dates to customers, as we define a delivery time window. Using a large real dataset inspired from an industrial partner, we compare the integrated approach with several current practice scenarios. We use an exact method to find the solution of each scenario and study the trade-offs between cost and service level in a detailed sensitivity analysis. Our results indicate how the use of a synchronized and holistic approach to decision making provides abundant opportunities for logistics systems in general. We further extend our study by considering a multi-product and multi-echelon setting. In this problem, products are shipped to customers through a set of distribution centers, and the producer has control over their locations. In this study our network design is flexible since it may change over time. As the problem gets richer and more realistic, it also becomes more complex and difficult to solve. Better solutions from the integrated approach are obtained at the expense of higher implementation complexity and execution time. We describe and model the problem, and solve it with both integrated and sequential decision making approaches to indicate when the use of a more complex approach is beneficial. Our work provides insights on the value of the integrated approach compared to the sequential one. To highlight how the two types of flexibility, from the network design and from the delivery time windows, lead to economic savings, we describe, model, and solve an integrated flexible two-echelon location routing problem. In this problem a supplier delivers a commodity to the customers through a two-echelon supply network. Here, we also consider a penalty for each demand that is not satisfied within the pre-specified time window. The problem is studied in a richer setting, as the distribution is conducted via vehicle routing. The fourth part of this thesis addresses the environmental impacts of logistic decisions. Traditionally, supply chain optimization has merely concentrated on costs or the economic aspects of sustainability, neglecting its environmental and social aspects. Aiming to compare the effect of operational decisions not only on costs but also on greenhouse gas emissions, we reassess some well-known logistic optimization problems under new objectives. We study two integrated systems dealing with production, inventory, and routing decisions, in which a commodity produced at the plant is shipped to the retailers over a finite time horizon. We provide elaborated sensitivity analyses allowing us to gain useful managerial implications on the costs and emissions in integrated supply chains, besides important insights on the cost of being environmentally friendly. In this thesis, we aim not only to better understand the integrated logistics as a whole but also to provide useful operational tools for its exploitation. We propose new business models capable of enhancing supply chain performance while at the same time developing mathematical and technical implementation for its effective and efficient use. Keywords: Integrated optimization; Dynamic lot-sizing; Delivery time window; Location analysis; Distribution

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 46-49).
Many businesses struggle to optimize the flow of inventory and finished goods through existing plants and facilities. The integration of inventory costs, organizational processes, and changing business dynamics make it difficult to determine the optimal flow. This thesis examines the flow of raw materials and finished goods through the supply chain of a multi-national oilfield services company. We study a centralized inventory approach, assessed through heuristics, against the existing decentralized approach. Sensitivity analysis with regard to service level, and mode of transport strengthened the analysis. We show that demand aggregation and lead time are important factors in determining the upper echelon for a company's internal distribution model. Potential safety stock reduction is 2%, which is mainly due to the improved coordination for materials flowing to the final echelon in the supply chain. However, pipeline inventory increases by 12% as a result of longer lead times.
by Patrick Scott and Boxi Xu.
M. Eng. in Supply Chain Management

Purpose: This study aims to find how the integration between marketing and operations can improve demand management in order to have efficient inventory level and avoid excess inventory. Method used: In order to have optimize inventory level and managing demand, integrating business process between marketing, supply planning and inventory management team was considered in this study. Qualitative data from nine interviews among three direct sales cosmetics companies was gathered. Findings: Empirical findings address excess inventory is caused by several issue in the company as poor management of demand forecasting, wide product portfolio, long lead time, the lack of sharing information between the company and its suppliers and ineffective strategy to avoid excess inventory within the company. Regarding to improve forecast accuracy and manage demand, findings indicate the role of marketing in obtaining knowledge about customer insight is not good enough. Practical Implication: It is critical that works and plans from each function be integrated to optimize inventory. In order to support optimize inventory strategy all pertinent departments must continue reviewing meeting with the aim to reach a consensus about the products planning for the both side of demand and operation align with overall strategic goals of the company. Contribution: Empirical data demonstrate the best way for effective implication of demand management occurs when marketing can provide demand information in time, as well as supply chain management can react flexibly to demand changes in time. Moreover, the lack of integration between marketing and supply chain management is a major barrier in optimizing inventory.

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 52-53).
While festivals bring a reason to cheer for everyone, businesses dealing with a spike in demand for perishables may have to live with the misery of lost sales and/or expired items. In the case of the dairy industry that deals with liquid milk, both raw material, and finished goods are perishable, which implies that merely stockpiling inventory of either item, without paying attention to potential inventory losses, cannot be an optimal strategy. In developing countries, the supplier base for perishables like milk, fruits, vegetables, flowers, etc. mostly comprise of small farmers instead of corporate/professional agencies, thus leading to supply variability. During special occasions like festivals, as individuals set aside more of the raw material for their own consumption, we encounter a reduction in supply. Around the same time, we notice a spike in customer demand, leading to a demand-supply mismatch. Companies dealing with perishables need an analytical approach to manage this.
In this thesis, we present a framework to address this problem of intermittent demand-supply mismatch using a 3-stage stochastic optimization model. We decide on the sourcing targets, the production plans based on supply realized, and finally, the dispatch plan based on orders received. As a case study, we analyze the operations and data from a private dairy company in eastern India, to understand the research problem and the applicability of the resulting model. We notice the impact of demand spikes and supply reduction in two areas: we increase supply targets in the periods preceding the demand spike; and we increase supply targets in periods when supply is expected to decrease, while demand is as usual. When there are multiple festival days within the time series, the compounding of impact depends on the sequencing of the events.
Finally, when we introduce the realistic constraint that the supply target needs to be constant throughout the time series, we see a degradation in the profitability, as we need to tradeoff between lost sales and wasted products. While the focus of this case study is the dairy industry, the conclusions from this research are broadly applicable to other industries dealing with perishables.
by Vishwanathan Parameshwaran lyer Nurani.
M. Eng. in Supply Chain Management
M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

This thesis studies inventory control with risk of major supply chain disruptions, specifically border closures and congestion. We first investigate an inventory system in which the probability distributions of order leadtimes are dependent on the state of an exogenous Markov process; we will model border disruptions via this exogenous process. We consider stationary, state-dependent basestock policies, which are known to be optimal for the system under study, and develop an expression for the long-run average cost of an arbitrary policy of this form. Restricting our attention to state-invariant basestock policies, we show how to calculate the optimal basestock (or order-up-to) level and long-run average cost. We provide a sufficient condition for the optimality of a state-invariant basestock policy and monotonicity results for the optimal state-invariant order-up-to level. We finally give the optimal state-invariant order-up-to level for a special class of supply states. Motivated by the possibility of port of entry closures in the event of a security incident, we specialize the previous model to a two-stage international supply chain. A domestic manufacturer orders a single product from a foreign supplier and the orders must cross an international border that is subject to closure. We first assume that border congestion is negligible. The manufacturer's optimal inventory policy and long-run average cost are analyzed. We present structural policy results and the results of a comprehensive numerical study that have important implications for business and for the cooperation between business and government in disruption management and contingency planning. Finally we extend the border closure model to include both border closures and the resulting congestion. We model the border processing system as a discrete-time, single-server queue with constant arrival rate and Markov-modulated service rate. A key task is the development of the leadtime distribution, which is more complex than in the previous model. We present the results of a comprehensive numerical study and provide managerial insights.

This dissertation considers the problems of coordinating different supply chain inventory systems with private information under deterministic settings. These systems studied are characterized by the following properties: (a) each facility in the system has self decision-making authority, (b) cost parameters of each facility are regarded as private information that no other facilities in the system have access to, and (c) partial information is shared among the facilities. Because of the above properties, the existing approaches for systems with global information may not be applicable. Thus, new approaches for coordinating supply chain inventory systems with private information are needed. This dissertation first studies two two-echelon distribution inventory systems. Heuristics for finding the replenishment policy of each facility are developed under global information environment. In turn, the heuristics are modified to solve the problems with private information. An important characteristic of the heuristics developed for the private information environment is that they provide the same solutions as their global information counterpart. Then, more complex multi-echelon serial and assembly supply chain inventory systems with private information are studied. The solution approach decomposes the problem into separate subproblems such that the private information is divided as required. Global optimality is sought with an iterative procedure in which the subproblems negotiate the material flows between facilities. At the core of the solution procedure is a node-model that represents a facility and its corresponding private information. Using the node-model as a building block, other supply chains can be formed by linking the node-models according to the product and information flows. By computational experiments, the effect of the private information on the performance of the supply chain is tested by comparing the proposed approach against existing heuristics that utilize global information. Experimental results show that the proposed approach provides comparable results as those of the existing heuristics with global information.

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1995, and Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1995.
Includes bibliographical references (leaves 61-66).
by Roderick D. Tranum.
M.S.

The assumption that all items are of good quality is technologically unattainable in most supply chain applications. Moreover, inventory theories are often built upon the assumption that the rates of demand, screening, deterioration and defectiveness are constant and known, even though this is rarely the case in practice. In addition, the classical formulation of a two-warehouse inventory model is often based on the Last-In-First-Out (LIFO) or First-In-First-Out (FIFO) dispatching policy. The LIFO policy relies upon inventory stored in a rented warehouse (RW), with an ample capacity, being consumed first, before depleting inventory of an owned warehouse (OW) that has a limited capacity. Consumption works the other way around for the FIFO policy. This PhD research aims to advance the current state of knowledge in the field of inventory mathematical modelling and management by means of providing theoretically valid and empirically viable generalised inventory frameworks to assist inventory managers towards the determination of optimum order/production quantities that minimise the total system cost. The aim is reflected on the following six objectives: 1) to explore the implications of the inspection process in inventory decision-making and link such process with the management of perishable inventories; 2) to derive a general, step-by-step solution procedure for continuous intra-cycle periodic review applications; 3) to demonstrate how the terms “deterioration”, “perishability” and “obsolescence” may collectively apply to an item; 4) to develop a new dispatching policy that is associated with simultaneous consumption fractions from an owned warehouse (OW) and a rented warehouse (RW). The policy developed is entitled “Allocation-In-Fraction-Out (AIFO)”; 5) to relax the inherent determinism related to the maximum fulfilment of the capacity of OW to maximising net revenue; and 6) to assess the impact of learning on the operational and financial performance of an inventory system with a two-level storage. Four general Economic Order Quantity (EOQ) models for items with imperfect quality are presented. The first model underlies an inventory system with a singlelevel storage (OW) and the other three models relate to an inventory system with a two-level storage (OW and RW). The three models with a two-level storage underlie, respectively, the LIFO, FIFO and AIFO dispatching policies. Unlike LIFO and FIFO, AIFO implies simultaneous consumption fractions associated with RW and OW. That said, the goods at both warehouses are depleted by the end of the same cycle. This necessitates the introduction of a key performance indicator to trade-off the costs associated with AIFO, LIFO and FIFO. Each lot that is delivered to the sorting facility undergoes a 100 per cent screening and the percentage of defective items per lot reduces according to a learning curve. The mathematical formulation reflects a diverse range of time-varying forms. The behaviour of time-varying demand, screening and deterioration rates, defectiveness, and value of information (VOI) are tested. Special cases that demonstrate application of the theoretical models in different settings lead to the generation of interesting managerial insights. For perishable products, we demonstrate that LIFO and FIFO may not be the right dispatching policies. Further, relaxing the inherent determinism of the maximum capacity associated with OW, not only produces better results and implies comprehensive learning,but may also suggest outsourcing the inventory holding through vendor managed inventory.

Vendor Managed Inventory (VMI) is a business practice in which vendors monitor their customers&rsquo
inventories, and decide when and how much inventory should be replenished. VMI has attracted a lot of attention due to its benefits. In this study, we analyze the benefits of VMI in a supply chain consisting of a single retailer and a single capacitated supplier under stochastic demand. We propose a VMI setting and compare the vendor managed system with the traditional system to quantify the benefits of VMI. In our proposed VMI system, the retailer shares the inventory level information with the supplier, which is not available in traditional system
and the supplier is responsible to keep the retailer&rsquo
s inventory level between the specified minimum and maximum values, called (z,Z) levels, set by a contract. We examine the benefits of such a VMI system for each member and for the overall chain
and analyze the effects of system parameters on these benefits. The performance of VMI in coordinating the overall chain is examined under different system parameters.

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged student-submitted from PDF version of thesis.
Includes bibliographical references (pages 59-63).
Excess inventory is prevalent in both the armed forces and defense companies; it takes up space and resources that could be used elsewhere. This thesis proposes a method to reduce the excess inventory and associated costs, while maintaining instant part availability, despite design changes which alter the number of parts required. A single period model extension was created based on K-means clustering of the parts according to lead-time and cost. These groupings provided the backbone of the cost functions created in the thesis. A predictive demand function was also created so that the design change's alterations to demand would be captured. The cost function was optimized using the predicted demand, to find an optimal order quantity that met the demand requirements and was the lowest cost option. Together these single period model function extensions allowed for a 31 percent decrease in excess inventory and 34 percent decrease in total cost. Due to the nature of this report the companies' names have been removed, and the data naming conventions were altered so as to protect the nature of the parts.
by Danaka M. Porter.
M. Eng. in Supply Chain Management

Manufacturing outsourcing in the U.S. has never been stronger than it is today. Increased outsourcing has led to significant changes in the design of the retail distribution network. While the traditional distribution network had the manufacturing plants supplying goods to the retail stores directly, the off-shore manufacturing has increased the network's demand for transportation and warehousing to deliver the goods. Thus, most companies have a complex distribution network with several import and regional distribution centers (RDC). In this thesis, we study an integrated facility location and inventory allocation problem for designing a distribution network with multiple national (import) distribution centers (NDC) and retailers. The key decisions are where to locate the RDCs and how much inventory to hold at the different locations such that the total network cost is minimized under a pre-defined operational rule for the distribution of goods. In particular, the inventory cost analysis is based on the continuous review batch ordering policy and the base-stock policy. Both Type-I (probability of stock-outs) and Type-II (fill-rate) service level measures are used in the analysis. Two different models are presented in this thesis for solving the integrated facility location-inventory allocation problem. The first model, continuous approximation (CA), assumes the distribution network to be located in a continuous region and replaces the discrete store locations with a store density function. The second model is a discrete representation of the problem as a mixed integer programming problem. Both the models take a nonlinear form and solution techniques are developed using the theory of nonlinear programming and linear reformulation of nonlinear problems. The goal of the first part of the thesis is to model the problem using a modified CA approach and an iterative solution scheme is presented to solve it. The main contribution of this work lies in developing a refined CA modeling technique when the discrete data cannot be modeled by a continuous function. In addition, the numerical analysis suggests that the total network cost is significantly lower in the case of the integrated model as compared with the non-integrated model. It is also shown that the regular CA approach leads to a solution which is inferior to the solution obtained by the modified CA approach. Our analysis shows that the type of service measure used affects the network design. In the second part of the thesis, the problem is modeled as a nonlinear mixed integer program and a linear reformulation solution technique is proposed to obtain a lower bound on the original problem. Computational results are presented for small problem instances. We conclude this part of the thesis by presenting an integrated model when a base stock inventory policy is used. A drop-decomposition heuristic is proposed to solve this problem.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 91-92).
The motivation for multi-echelon supply chain management at Nike is to more cost-effectively accommodate customer-facing lead time reduction in the rapid-response replenishment business model. Multi-echelon inventory management, as opposed to a traditional finished-goods only philosophy, provides two clear benefits to a make-to-stock supply chain: first, it increases flexibility through staging calculated work-in-process inventory buffers at critical supply chain links and allowing postponed identification of finished goods; second, inventories held as work-in- process are typically carried at lower cost than finished goods. This thesis details the completion of a project intended to improve Nike's ability to determine optimal inventory levels by balancing cost and service level tradeoffs in a multi-echelon-enabled environment. The goal is to develop an inventory modeling methodology for Nike's supply chain data architecture specifically to evaluate the hypothesis that multi-echelon inventory management will present only limited opportunity for cost reduction in offshore, long lead time make-to-stock supply chains. To directly asses the hypothesis, Llamasoft's Supply Chain Guru optimization software will be deployed to create an inventory optimization model for a specific family of apparel products sold as part of Nike's replenishment offering in North America. The modeling results confirm the hypothesis that multi-echelon inventory management offers little value to the current offshore supply chain. Sensitivity and scenario analysis is utilized to identify significant inventory drivers, areas for substantial improvement, and profitable opportunities for multi-echelon inventory management.
by Robert Giacomantonio.
S.M.
M.B.A.

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 73-75).
When a disruption brings down one of company's manufacturing facilities, it can have a ripple effect on the entire supply chain and threaten the company's ability to compete. In this thesis, we develop an effective disruption mitigation strategy by using both process flexibility and strategic inventory. The model is focused on a manufacturer with multiple plants producing multiple products, where strategic inventory can be held for any product. We propose a new metric of supply chain robustness, defined as the maximum time that no customer demand is lost regardless of which plant is disrupted. Using this metric, we analyze K-chain flexibility designs in which each plant is capable of producing exactly K products. It is demonstrated that a 2-chain design, which is known to be effective for matching supply with demand when there is no disruption, is not robust when there is both disruption and demand uncertainty. However, it is shown that a 3-chain design is significantly more robust and achieves the same robustness as full flexibility under high uncertainty level. We then extend the model to an assembly system and find that investment in process flexibility designs changes the optimal inventory placements. In particular, when the degree of flexibility is high, more inventory is allocated to standard components, i.e. components used by multiple products, but when the degree of flexibility is low, more inventory is allocated to non-standard components.
by He Wang.
S.M.in Transportation

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2006.
Includes bibliographical references (p. 68-69).
Dell is a well-known consumer electronics manufacturer that has experienced astounding rates of revenue growth since its inception in 1984. Regarded as a supply chain innovator, Dell has attained success through industry-revolutionizing ideas such as vendor-managed inventory, pull manufacturing, and direct sales. Today, continuance of revenue growth for Dell requires not only rapid innovation, but also rapid geographic and product expansion. Until a few years ago, Dell only had one facility in the United States. All of Dell's US-based systems and processes were constructed to optimize this single factory. Since 1999, Dell has added a number of new facilities in the US - factories and merge centers - for the sake of proximity to customers as well as additional capacity. Also, Dell recently began practicing more product leveling than in the past, producing multiple types of systems at the same factory. Finally, Dell's US supply base has migrated to Asia, as have those of most in the industry. This confluence of complexities has led to a significant increase in instances of material imbalances, whereby any given part has not been distributed to the various sites in accordance with their proportion of actual demand, often resulting in costly expedites from site to site or delayed shipments to customers.
(cont.) Part of the solution to this problem is what Dell has termed "Dynamic Replenishment". As Dell's US supply has shifted from America-based to Asia-based over the past five years, the effective lead time for most ocean-shipped parts has increased from days to several weeks. As a result, the site-level forecast for routing of an ocean shipment is more frequently incorrect by the time it reaches the US, and material imbalances occur. In order to reduce these imbalances, Dynamic Replenishment processes aim to proactively re-route material (if needed, based on campus inventories and forecasts) upon arrival at the US port. This thesis will focus on the tools, information, processes, and organizational roles that are required to ensure proper routing of material at the latest possible juncture in Dell's ocean-network supply chain. Treatment will also be given to the idea that the material balancing problem is one of many that result from Dell's rapid supply chain growth, and some related issues will be examined from this broader perspective. (A note on scope: The content of this thesis is related only to Dell's US-based operations. All history, facts, and comments should be taken in this regard.)
by Amy M. Reyner.
S.M.
M.B.A.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006.
Includes bibliographical references (p. 199-213).
This thesis investigates the impact of lack of information and decentralization of decision-making on the performance of inventory, supply chain, and transportation systems. In the first part of the thesis, we study two extensions of a classic single-item, single-period inventory control problem: the "newsvendor problem." We first analyze the newsvendor problem when the demand distribution is only partially specified by some moments and shape parameters. We determine order quantities that are robust, in the sense that they minimize the newsvendor's maximum regret about not acting optimally, and we compute the maximum value of additional information. The minimax regret approach is scalable to solve large practical problems, such as those arising in network revenue management, since it combines an efficient solution procedure with very modest data requirements. We then analyze the newsvendor problem when the inventory decision-making is decentralized. In supply chains, inventory decisions often result from complex negotiations among supply partners and might therefore lead to a loss of efficiency (in terms of profit loss).
(cont.) We quantify the loss of efficiency of decentralized supply chains that use price-only contracts under the following configurations: series, assembly, competitive procurement, and competitive distribution. In the second part of the thesis, we characterize the dynamic nature of traffic equilibria in a transportation network. Using the theory of kinematic waves, we derive an analytical model for traffic delays capturing the first-order traffic dynamics and the impact of shock waves. We then incorporate the travel-time model within a dynamic user equilibrium setting and illustrate how the model applies to solve a large network assignment problem.
by Guillaume Roels.
Ph.D.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 53-55).
In supply chain management, it is commonly held that reducing lead times and minimum order quantities (MOQs) from suppliers can drive down the customer's inventory levels substantially. Customers providing a consumption forecast along with a commitment to a supplier to cover some portion of raw material, work-in-process, and finished goods in exchange for reduced lead times and lower MOQs can support that goal; however, there does not exist a general method for identifying and optimizing the terms of these agreements. Existing literature describes techniques that involve vendor-managed inventory and other lead time reduction strategies, but none exists where the customer manages the ordering and replenishment policies from a vendor stock. In this thesis, we investigate a method for a company to reduce lead times and inventory level while maintaining or improving their customer service level. To do so, we introduce a new process for the business where a customer identifies the optimal subset of parts with their corresponding lead time and stocking policy trade-offs to drive inventory reductions relative to the existing state. We describe the benefits for both supplier and customer and specifically focus on the investigation of the opportunity for the customer and the appropriate segmentation of suppliers and parts for consideration in a pilot leading to full implantation. We expect this new approach to substantially reduce the inventory at the customer while improving the suppliers' ability to optimize their own manufacturing planning and setup schedules.
by Randall Markham.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

The Global Supply Chain Forum (Stanford Global Supply Chain Forum Web Resource, http://www.stanford.edu/groups/scforum) defines supply chain management (SCM) as “Supply chain management is the integration of key business processes from end user through original suppliers that provides products, services and information that add value for customer and other stakeholders.” The rapid development of the Internet has dramatically changed the traditional definitions of manufacturer, suppliers and customers. Newer approaches to supply chain management attempt to organize the supply chain as a network of cooperating intelligent agents, each performing one or more supply chain functions and each coordinating actions with one another. This research is aimed at creating a viable model of a single manufacturer single supplier collaborative supply chain system using a Vendor Managed Inventory (VMI) system. The research further uses known inventory performance parameters to performance benchmark the VMI system with traditional push-pull systems, develop a collaborative forecasting spreadsheet solution and a best alternative ordering policy amongst EOQ, Monthly, JIT and VMI policies under known lead time and a variety of demand distribution functions.
Master of Science

Supply chain agility has been receiving a lot of attention in recent literature as a way for organizations to become more responsive to change and improve customer service levels. However, agility is typically dealt with qualitatively, and organizations are usually unsure of the steps to take to improve their agility and the customer service level to target. This research studies supply chain agility based on a case study of Intel Corporation, a large semiconductor manufacturer. Here, agility is defined as the ability to satisfy customer demands by reacting effectively to changes in market stimuli. Reacting effectively does not mean reacting to every change in supply or demand. Doing so means increasing supply chain variability unnecessarily, which is amplified by the bullwhip effect. The essence of supply chain agility is determining the degree to which variability should be managed through artificial means such as safety stock, and appropriate triggers for changing production levels and inventory targets. The purpose of this research is to examine factors that influence supply chain agility and identify a cost-effective plan for achieving it. The first phase addresses the problem of identifying target inventory and customer service levels based on regression analysis of historical data and financial analysis of inventory holding costs and stock-out costs. The impact of three factors (forecast error, order lead-time, and demand variability) on the relationship between inventory and customer service level is also examined. The second phase of the research evaluates strategies for production and inventory control with the goal of finding the appropriate trade-off between minimizing cost (of holding inventory and stock-outs) and minimizing variability. Control policies based on the Exponentially Weighted Moving Average (EWMA) control chart with control limits on demand forecasts are proposed to detect when tighter control of processes is necessary. A Monte Carlo supply chain simulation is used to evaluate the performance of these policies under various levels of forecast error and demand variability. Results indicate that several control chart-based policies outperform Intel's current planning policy in terms of cost without significantly increasing variability. The selection of the appropriate policy must be based on the decision-makers' desire to minimize cost compared to the desire to minimize variability, as each policy results in a trade-off between these two objectives.
Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering and Management Systems

We live in an era where markets are more dynamic and the product life cycle is shorter, an era where concepts such as smart manufacturing and mass customization form part of daily life in industries and where consumption rates of products and services are rising. All these result in more dynamic, global, complex and fragile supply chains. Disruptions are negative impacts on business continuity in companies and when a supply chain is disrupted there is only one way to tackle the challenges originated and is the ability to be resilient. Based on a systematic literature review, this thesis lay out a framework to position Vendor Managed Inventory digital solutions in order to provide full visibility in the supply chains, and enhance agility and flexibility skill sets in the organizations to be resilient after massive disruptions such as the COVID-19. The conclusions of this work provide a positive outlook of the capabilities of VMI solutions to create more resilient supply chains.
Vi lever i en era där marknader är mer dynamiska och produkters livscykel kortare. En era där koncept som smart tillverkning och mass-anpassning är en del av dagliga livet i industrier och där konsumtionsnivåer av produkter och tjänster ökar. Allt detta resulterar i mer dynamiska, globala, komplexa och känsliga försörjningskedjor. Störningar påverkar kontinuiteten i verksamheten negativt hos företag och när en försörjningskedja påverkas av störningar finns det bara ett sätt att hantera utmaningarna som uppstår och det är genom förmågan att vara motståndskraftig. Baserad på systematisk litteratursökning, lägger denna avhandling fram ramverk för att positionera Vendor Managed Inventory digitala lösningar för att förse full synlighet i distributionskedjan och förbättra rörlighetens och flexibilitetens förmågor i organisationerna för att bli mera uthållig efter massiva störningar som COVID-19. Slutsatserna av detta arbete ger en positiv syn på möjligheterna för VMI-lösningar för att skapa mer motståndskraftiga försörjningskedjor.

In this study, carbon dioxide emissions resulting from transportation are assessed, carbon emission reduction opportunities in the current service supply chain design of Cisco Systems, Inc. are explored. Among these opportunities, changing transport mode from a high-carbon transport mode to a low-carbon transport mode is found to be the most promising option and is scrutinized. The effect of transportation mode change on carbon emission and expected total cost are scrutinized by developing a mathematical model that minimizes expected total cost subject to aggregate fill rate constraint. Furthermore, a second model that minimizes the expected total cost under aggregate expected fill rate and carbon emission constraints is developed. In this model transportation mode choice decisions are integrated into inventory decisions. Since it is difficult to make transportation mode selection for each individual item, the items are clustered and transportation mode selection is made for each cluster. Therefore we propose two clustering methods that are k-means clustering and an adopted ABC analysis. In addition, a greedy algorithm based on second model is developed. Since currently there are no regulations on carbon emissions, in order to examine possible regulation scenarios computational studies are carried out. In these studies, efficient solutions are generated and the most preferred solutions that have less carbon emission and lower total cost among all efficient solutions are examined.

Vendor Managed Inventory (VMI), Consignment Inventory (CI) and a combination of both (C&VMI) are supply-chain sourcing agreements between a vendor and customer. VMI allows the vendor to initiate orders on behalf of the customer. In CI, the customer pays for the goods supplied by the vendor only upon use. The vendor under C&VMI decides customer-replenishments, and owns the goods replenished until they are deployed by the customer. Our thesis studies these agreements in three essays.

The first essay considers a vendor V that manufactures a particular product at a unique location. That item is sold to a single retailer, the customer C. Three cases are treated in detail: Independent decision making (no agreement between the parties); VMI, whereby the supplier V initiates orders on behalf of C; and Central decision making (both Vendor and Customer are controlled by the same corporate entity).

Values of some cost parameters may vary between the three cases, and each case may cause a different actor to be responsible for particular expenses. Under a constant demand rate, optimal solutions are obtained analytically for the customer's order quantity, the vendor's production quantity, hence the parties' individual and total costs in the three cases. Inequalities are obtained to delineate those situations in which VMI is beneficial.

The problem setting in the second essay is the same with that of Essay 1, but the sourcing agreements investigated are now CI and C&VMI. In CI, as in the usual independent-sourcing approach, the customer has authority over the timing and quantity of replenishments. CI seems to favour the customer because, in addition, he pays for the goods only upon use. Under a C&VMI agreement, the vendor still owns the goods at the customer's premises, but at least can determine how much to store there.

The second essay thus contrasts the cases CI and C&VMI, and compares each of them to a no-agreement case. General conditions under which those cases create benefits for the vendor, the customer and the whole chain are determined.

Essay 3 investigates VMI and C&VMI separately for a vendor and multiple customers who face time-varying, but deterministic demand for a single product. In any of those agreements, the vendor seeks the best set of customers to achieve economies of scale. MIP models are developed to find that set of customers, and to determine the vendor's optimal production, transportation, and customer-replenishment quantities. The model for VMI is solved using a heuristic that produces two sub-models, and uses hierarchical solution approach for production, customer-replenishment and transportation decisions. C&VMI model is solved using Lagrangian relaxation. Various numerical examples are used to test the solution approaches used.

In the mean time, the customers can guarantee to be no worse off under VMI or C&VMI than the no-agreement case by setting the right levels of maximum inventory. A model to determine those levels and a solution algorithm are also proposed in Essay 3.

The first two essays can help a vendor or customer in a supply chain to determine the least costly sourcing option, which depends on the relative values of various cost parameters. A vendor with multiple customers can make use of the results in the third essay, which reveal the best possible economies of scale under VMI or C&VMI. Those customers can guarantee to be no worse of than traditional sourcing when they set the proposed levels of maximum inventory.

Sustainability concerns are increasingly shaping customers' behavior as well as companies' strategy. In this context, optimizing the supply chain with sustainability considerations is becoming a critical issue. However, work with quantitative models is still scarce. Our research contributes by revisiting classical inventory models taking sustainability concerns into account. We believe that reducing all aspects of sustainable development to a single objective is not desirable. We thus reformulate single and multi-echelon economic order quantity models as multi-objective problems. These models are then used to study several options such as buyer-supplier coordination or green technology investment. We also consider that firms are becoming increasingly proactive with respect to sustainability. We thus propose to apply multiple criteria decision aid techniques instead of considering sustainability as a constraint. In this sense, the firm may provide preference information about economic, environmental and social tradeoffs and quickly identify a satisfactory solution.

Thesis (Ph.D.)--Indiana University, Kelley School of Business, 2006.
"Title from dissertation home page (viewed July 5, 2007)." Source: Dissertation Abstracts International, Volume: 67-08, Section: A, page: 3067. Adviser: F. R. Jacobs.

We study risk pooling via unidirectional lateral transshipments between two locations under local decision-making. Unidirectional transshipments can be applicable when cost structures and/or capabilities differ between locations, and it is also a common practice in dual channel supply chains with online and offline sales channels. We show that such a system cannot be coordinated only with varying transshipment prices. The transshipment receiver orders more and the transshipment giver orders less than the respective optimal centralised order quantities. In order to remove this discrepancy, we suggest horizontal coordinationmechanisms by introducing a leftover subsidy for the location providing the transshipments or a shortage subsidy for the location receiving transshipments as well as a combination of shortage and leftover subsidy. Further, we evaluate the impact of network structure by comparing the equilibrium order quantities and profits under the uni- and bidirectional systems as well as a system without transshipments. Since demand correlation is a critical aspect in risk pooling we provide a detailed numerical study to discuss its impact on our findings.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 83-84).
Perishability presents a challenging problem in inventory management for the fresh produce industry since it can lead to higher inventory costs and lower service levels. If a supply chain has multiple echelons, that further complicates the issue since companies have an added risk of not having the right amount of product at the right location at the right time. We conduct our research on Chiquita's Fresh Express supply chain. We analyze the impact of perishability on total relevant costs. Our research focuses on determining the optimal inventory policy for the system considering inventory holding costs, shrinkage costs, lost sales costs, forecast accuracy and service levels. We test the sensitivity of the system with respect to forecast errors and the transportation lead time. We developed a discrete-event simulation model using Arena software to conduct the research. Our research demonstrates that by lowering the current target on-hand inventory levels at the distribution center and retail stores, inventory holding costs and shrinkage costs are reduced significantly. Under the optimal inventory policy, the system can save 31% in costs, improve the item fill rate at the distribution center, reduce the total shrinkage volume, and maintain high service levels of more than 95% at the retail stores. Our sensitivity analysis shows that the system is very sensitive to the forecast errors. Additionally, we recommend keeping the transportation lead time as low as possible to maximize the products' lifetime at the retail stores. Reducing the forecast errors or the transportation lead time would reduce the total relevant cost of the system while improving the item fill rates across the supply chain.
by Yogeshwar D. Suryawanshi and Thomas Hsien.
M.Eng.in Logistics

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 69).
Inventory is the largest asset on Nike's balance sheet-$3.9 Billion on May 3 1 st, 2014-and a key indicator of supply chain health. With new markets, products, and channels being added to Nike's sales portfolio each year, the environment in which Nike's supply chain must operate is becoming increasingly complex. Nike has responded to this complexity by splintering their supply chain into smaller segments, tailoring each segment to specific market and consumer needs. As a result of these market developments and Nike's organizational response, the task of understanding and predicting inventory movements has become increasingly challenging for Nike's business planning teams. This project creates an analytical method by which Nike can combine historical supply chain performance with sales forecasts to accurately predict future changes to company inventory levels. To achieve this goal and facilitate simple and flexible inventory predictions, a model was developed around the key segmentation dimensions that define Nike's supply chain. Use of this model enables Nike's senior management team to accurately predict movements in inventory due to product mix changes in the baseline sales forecasts. Additionally, the model provides Nike with a mechanism to evaluate sensitivity to forecast errors and the inventory costs associated with key strategic decisions to grow or shrink segments of their business. Preliminary results from the model over the time period FY15 - FY18 show a 2% increase in baseline inventory by the end of FY18 due both to growth in Apparel relative to Footwear and to growth in Direct-to-Consumer relative to Wholesale. This upward pressure on inventory leaves Nike in a precarious spot with Wall Street analysts who associate inventory growth relative to sales with poor marketplace performance. By carefully segmenting inventory, applying segment specific forecasts, and analyzing aggregated results through the use of the model, Nike can more accurately predict and explain movements in inventory to shareholders.
by Ryan Jacobs.
M.B.A.
S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 69-71).
This thesis details research performed during a six-month engagement with Verizon Wireless (VzW) in the latter half of 2012. The key outcomes are a forecasting model and decision-support framework to improve management of VzW's reverse supply chain inventory. The forecasting model relies on a reliability engineering formulation and incorporates a learning component to allow incremental forecast improvement throughout the device lifecycle. The decision-support model relies on Monte Carlo simulations to quantify the uncertainty and risk associated with different inventory management policies. These tools provide VzW stakeholders with a full-lifecycle perspective so that inventory planners can avoid costly end-of-life underages and overages. Prior to this effort, inventory planners at VzW relied on a three month returns forecast despite the fact that customers can return devices more than three years after launch. The decision-support model replaces existing heuristics to improve inventory management. Model efficacy is demonstrated through case studies. For a variety of representative SKUs, the returns forecast model is found to predict cumulative lifecycle returns within 10% using data available six months from launch. Had inventory been managed according to the policies recommended by the decision support model instead of policies from existing heuristics, VzW could have avoided an end-of-life stockout of more than 20,000 devices for a particular SKU.
by Brian J. Petersen.
M.B.A.
S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Cataloged from PDF version of thesis.
Includes bibliographical references (page 67).
As AstraZeneca's product portfolio becomes increasingly complex, its supply chains must evolve in parallel. These supply chains operate in an environment of ever-present external risks such as factory fires, geopolitical disruptions and natural disasters. Such risks might manifest as disruptions which could jeopardize the health of those who depend upon AstraZeneca's life-saving medicines. Accordingly, there is a need to improve proactive planning and reactive risk decisions to maintain service levels in such an environment. This thesis presents an approach which enhances both risk planning decisions and reaction to disruptive events. The approach consists of a third party software solution to provide better supply chain visibility, increased risk awareness, and faster disruptive event notification, as well as a stochastic nonlinear optimization model to support inventory reductions. Both approaches improve risk planning decisions, while the software approach also supports reactive decision-making as disruptive events unfold. For a single brand, this thesis model shows that current risk mitigation inventory sizes across its supply chain can be reduced by over 50% while maintaining the target service level. The cost savings estimated for a reduction of this magnitude are at least $20M for one brand alone. Simultaneously, the software uncovers previously unknown sub-tier suppliers and highlights tier one dependencies. Adoption of this thesis' recommendations can improve risk planning and decisionmaking within AstraZeneca's supply chains while greatly reducing mitigation inventory costs.
by Kenneth E. Hampshire.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering

博士
中原大學
工業工程研究所
95
Due to recent worldwide environmental and green products consciousness, a systematic analytical process to evaluate various alternative courses of action with the objective of developing an efficient way to employ scarce resources is critical. The pressures from WEEE (Waste Electrical and Electronic Equipment), RoHS (Restriction of Hazardous Substance) and European Union have played an important part in enhancing the greening of products. After December 31, 2006, each person of WEEE main members has to recovery at least 4 kilograms recycling quantities every year. Therefore, each enterprise must achieve the recovery system in order to conform to the WEEE instruction. Increasing environmental consciousness, limited of natural resources to manufacture new products, recovery quotas to avoid disposal, manufacturers assigned to be responsible for used products, and materials value of components included in returned products are incentives for product recovery. Reuse of products and materials is not a new phenomenon. Waste paper recycling, metal scrap brokers, and deposit systems for soft drink bottles are the examples that have been around for a long time. In these cases recovery of the used products is economically more attractive than disposal. In this study we discuss the newly procured and reusable items that have imperfect quality. The model assumes that a fixed proportion of the used products are collected from customers and later recovered for reuse. The recovered products are regarded as perfectly new ones. The object is to obtain the economic order quantity (EOQ) for procurement and the optimal inventory level of recoverable items to start the recovery process simultaneously. The formulation treats the two inventories as interdependent parts of a total system, and jointly determines the optimal lot sizes for the recovery and the procurement process. A mathematical model and program are developed to derive the minimal cost, and finally numerical example and sensitivity analysis are given to analyze the key factors in the system.

碩士
中原大學
工業工程研究所
91
Abstract The goal of supply chain management (SCM) is to pursue the minimization of the total operational costs, which consist mainly of the transportation and inventory costs. This research aims to derive an approximate optimized transportation and inventory costs by using a systematic process of allocating goods. In current electronic commerce (EC) environment of, customer satisfaction is achieved through rapid distribution of the supply chain management logistics. In order to satisfy customer’s stock requirements to avoid shortages, supply chain should have appropriate inventory management operation system and transportation system. The existence of inventory is due the consideration of customer service, seasonal products, market speculation, increasing quality standard, supplement of deviation of forecast, variation in supply and demand, differences between production system and distribution system, and the use of some ordering systems. Primarily, inventory management is to ensure smooth enterprise operations, and to reduce inventory cost and to provide satisfactory customer services. Transportation is one of the essential elements in basic activities of the supply chain. The transportation system serves to deliver raw material from the supplier to the manufacturer in business logistics, and to distribute finished goods from the manufacturer to the customer. The aim of the transportation operations is to deliver the right quantity of material to the right place at the right time. There is a conflicting objective of the transportation and the inventory costs, the decrease of one will increase of the other. A trade-off makes the considerations of supply chain operation difficult. This research investigates the factors that influence the transportation and inventory costs in the supply chain. Through inventory classification, the allocation of warehousing, and the use of available facilities, the transportation and inventory costs can be reduced. The result of this research can contribute to effective supply chain management. Keywords：supply chain、logistics、transportation and inventory costs

碩士
國立成功大學
交通管理學系碩博士班
100
In this research, we consider the supply chain inventory configuration and demand forecast recognizing customer stochasticity. We first forecast customer demand from historical data and formulate the problem as a two-stage stochastic linear program model. The resulting two-stage stochastic linear program model is solved by the Monte Carlo Bounding Techniques with both Common Random Number (CRN) and Independent Random Number (IRN) methods to determine the optimal distribution strategy. To gain insight into the problem and to intuitively understand the behavior of the proposed solution scheme, we empirically apply this framework on a three-tier supply chain to evaluate the practicability of the proposed framework. Numerical results together with the salient conclusions are presented and discussed.