This Record of Study contains the details of an optimization model developed for Shell Oil Co. This model will be used during the strategic design process of a supply chain for a new technology commercialization. Unlike traditional supply chain deterministic optimization, this model incorporates different levels of uncertainty at suppliers' nominal capacity. Because of the presence of uncertainty at the supply stage, the objective of this model is to define the best diversification and safety stock level allocated to each supplier, which minimize the total expected supply chain cost. We propose a Monte Carlo approach for scenario generation, a two-stage non-linear formulation and the Sample Average Approximation (SAA) procedure to solve the problem near optimality. We also propose a simple heuristic procedure to avoid the nonlinearity issue. The sampling and heuristic optimization procedures were implemented in a spreadsheet with a user's interface. The main result of this development is the analysis of the impact of diversification in strategic sourcing decisions, in the presence of stochastic supply disruptions.

<p>THE ADVANTAGE OF RFID TECHNOLOGY IMPLEMENTATION IN A MANUFACTURING FIRM. THE TECHNOLOGY IMPLEMENTATION STREAM LINES THE LOSS OF INFORMATION FLOW WHEN THE PRODUCT MOVES ALONG THE DIFFERENT CHAIN MEMBERS. THE COMMON SHARING OF THE ASSOCIATED BENEFIT BRINGS HIGHER PROCESS EFFICEINCY , WHEN THE PRODUCT MOVES ALONG THE UPSTREAM AND DOWNSTREAM SUPPLY CHAIN FOR THE SELECTED PRODUCT. THE IMPLEMENTATION IS A CUSTOMISED SOLUTION FOR THE MANUFACTURING UNIT FOR ITS PRODUCT, THIS THESIS WILL ENABLE THE IMPLEMENTATORS THE VALUABLE IMPLEMENTATION PROCEDURES THAT ONE HAS TO FOLLOW TO TAKE RIGHT BENEFIT FROM THIS TECHNOLOGY.</p>

Demand forecasting is an important step of a company’s supply chain management process, allowing companies to project their needs for different components that are used in the final product. This is even more important in emerging industries with job order (or project-based) products where historical demands do not exist and components may not be readily available or may involve a long lead time. Developing a demand forecasting model which accurately projects the needs of components for a company can decrease costs while decreasing overall lead times of final products. This demand forecast model takes into account projected component needs along with the likelihood of successfully winning a project bid. The model is extended to four different demand forecasting formulas incorporating different use of the winning probabilities. Historical results are then used to compare the methods and their advantages and disadvantages are discussed. / text

Implementing Build to Order (BTO) strategies instead of usual Build to Stock have the potential of sorting out some individual problems of the automotive industry (e.g. high stock of finished goods). BTO reconnects the customer to the Supply Chain by focusing on him/her and making him/her to the starting point of the production process. Consequently some objectives like stock reduction as well as an increase of market shares and profits are linked with BTO. However, some requirements and preconditions have to be fulfilled to realize BTO strategies. First of all flexibility across processes, products and volume have to be assured. Therefore actions and strategies like Direct Order Booking, integration of suppliers and 3rd party logistics, platforms and modular design could be adopted. Furthermore, it's necessary to take measures to reduce the Order to Delivery (OTD) time generally and the time of information flow, which currently accounts for more then 85% of the delay in the production and planning process, specially. Promoting IT along the whole Supply Chain, might be the key to success in this case. Finally it should be noted that BTO could not be the overall solution for the whole automotive industry. It will only be applicable if some circumstances are satisfied. Therefore the premium segment (customers going for individuality and prestige) as well as the European market (customers with relatively high willingness to wait) are the possible fields of implementing BTO in the near future. (author's abstract) / Series: Schriftenreihe des Instituts für Transportwirtschaft und Logistik - Supply Chain Management

Information Technology infrastructures continue to be dynamic, evolving, and business critical investments for companies of all sizes. Even with moves to virtualize end user computing functions, the evolution of network architectures, mobile computing devices and corporate security requirements will continue to necessitate technology upgrades requiring, at their core, the rudimentary act of placing hardware at specific physical locations on a prescribed timeline. In distributed corporate environments, deploying a range of devices sourced from multiple suppliers into geographically dispersed locations can be a challenge in material management and logistics planning. This Multi-Source, Multi-Site style of deployment is a complex balance of competing timelines where failures to meet delivery targets can have costly impacts that cascade throughout the project. Perturbations in global supply chains, manufacturing schedules, and local shipping capacities drive fluctuations in a supplier's ability to consistently and predictably execute to delivery timelines so it is the task of a deployment Project Manager to interpret a variety supply chain signals and take action to minimize the negative impacts of supply chain challenges. In that effort, the deployment PM will benefit from a structured approach to defining how available supply chain data will be used to help manage expectations, monitor execution, and effect the overall deployment success. In this paper, I present an approach that breaks deployment planning into 3 primary deliverables; the Site Plan, the Data Plan, and the Monitoring Plan. Executing those three plans will drive a PM to understand the supply chain data available to them, translate that data into information useful and understandable by all stakeholders, and monitor the progress of the supply chain against a deployment schedule. In practical terms, those plans culminate in a data mining and data management methodology that can be supported with spreadsheet based dashboards that provide both a fixed Snapshot of the status of the deployment as well as a rolling Timeline of key material movements over the duration of the deployment. The data management approach described here is specifically designed to avoid complex macro development, database queries, or software purchases that may not be available to all Project Managers. Applying the Multi-Source, Multi-Site approach, a PM can gain useful and relevant information from various streams of supply chain data using straightforward spreadsheet manipulations. With a clearer picture of supply chain execution, a PM tasked with a Multi-Source, Multi-Site deployment can better leverage project change control methods to improve their chances of successfully meeting their schedule and cost targets. / text

This thesis proposes a novel synergy of the classical scenario and robust approaches used for strategic supply chain optimization under uncertainty. Two novel formulations, namely the naïve robust scenario formulation and the affinely adjustable robust scenario formulation, are developed, which can be reformulated into tractable deterministic optimization problems if the uncertainty is bounded by the infinity-norm. The two formulations are applied to a classical farm planning problem and an energy and bioproduct supply chain problem. The case study results demonstrate that, compared to the scenario formulation, the proposed formulations can achieve the optimal expected economic performance with smaller number of scenarios, and they can correctly indicate the feasibility of a problem. The results also show that the affinely adjustable robust scenario formulation can better address uncertainties than the naïve robust scenario formulation. Next, a strategic optimization problem for an industrial chemical supply chain from DuPont was studied. The supply chain involves one materials warehouse, five manufacturing plants, five regional product warehouses and five market locations. Each manufacturing plant produces up to 23 grades of final products from 55 grades of primary raw materials. The goal of the strategic optimization is to determine the capacities of the five plants to maximize the total profits of the supply chain system while satisfying uncertain customer demands at the different market locations. A mathematical model is developed to relate the material and product flows in the supply chain, based on which the classical scenario approach and the affinely adjustable robust scenario formulation were developed to address the uncertainty in the demands. The case study results show the advantages of the affinely robust scenario formulation over the scenario formulation. Using the affinely adjustable robust scenario formulation often results in problems with very large sizes, which cannot be solved by regular optimization solvers efficiently. In order to exploit the decomposable structure of the formulation, Dantzig-Wolfe decomposition is studied in the thesis. Two approaches to implement Dantzig-Wolfe decomposition are developed, and both approaches involve the solution of a sequence of linear programming (LP) and mixed-integer linear programming (MILP) subproblems. The computational study of the industrial chemical supply chain shows that a combination of the two Dantzig-Wolfe approaches can achieve an optimal or a near-optimal solution much more quickly than a state-of-the-art commercial LP/MILP solver, and the computational advantage increases with the increase of number of scenarios involved in the problem. / Thesis (Master, Chemical Engineering) -- Queen's University, 2014-03-24 20:39:42.761

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Den växande e-livsmedelshandelns Supply Chains har studerats genom hållbarhetsglasögon där syftet var att ”[…] ge en fördjupad förståelse över hur svenska elivsmedelsaktörerarbetar med frågor rörande Sustainable Supply Chain Management”. Syftet fullgjordes genom en kvalitativ studie av tre organisationer, i vilka totalt 9 beslutsfattare intervjuades enligt ett semi-strukturerat intervjuförfarande. De data som samlades rörande e-livsmedelsaktörernas arbete med SSCM har i sin tur analyserats med hänvisning till en i förväg fastställd teoretisk referensram. Vår studie avslöjar att två av de svenska e-livsmedelsaktörerna är exemplariska och framstående med att införliva hållbarhet i sin Supply Chain. De engagerar sig aktivt i de initiativ för Sustainable Supply Chain Management som i litteraturen identifierades som nödvändiga för en verkligt hållbar Supply Chain. De har en allomfattande och övergripande strategi för att minimera den sociala risken, reducera resursutnyttjande och förorenande biprodukter i hela Supply Chain samt för att förbättra organisatoriskt inbäddade ohållbara vanor. Det tredje företaget saknar emellertid kapacitet och marknadsinflytande att engagera sig i SSCM. Studien åskådliggör även att en klimatneutral e-livsmedelsdistribution osannolikt förverkligas inom en snar framtid, såvida inte marknaden interveneras och företagen tvingas internalisera kostnaderna för utsläpp.

This thesis presents an optimization model which helps retailers to reduce product costs by taking advantage of parts commonality in manufacturing and production areas, when selling similar units with uncertainty in demands. The concept of component commonality can be often found in the assemble-to-order system, which is the foremost concept used by prominent manufacturing companies in the global market. The method developed uses genetic algorithm (GA) to solve real world optimization problems that contain integer values for parts and finished items, and uncertain information. Numerical examples are solved using generated stochastic scenarios to show the impact of uncertainty on solutions. This impact is verified using two important criteria, Expected Value of Perfect Information (EVPI) and Value of Stochastic Solution (VSS). The obtained solutions present significant monetary benefits for the manufacturer illustrating the importance of the model presented here for retailers.

Effective Medicine Control is the essence of pharmaceutical service delivery and of financial management in Platinum Health Pharmacies. Platinum Health Pharmacies implement medicine control measures to enhance and optimise service delivery. As Platinum Health Pharmacies deliver a pharmaceutical service as business associates of Anglo Platinum, it serves the same workforce. The requirement of the pharmaceutical service delivery for Anglo Platinum is timely, appropriate and available medicine. Therefore, Platinum Health Pharmacies need to adhere to set criteria, those of ?Good Pharmacy Practice in South Africa? as applied to the control, procurement and prescribing of medication. The ordering and receiving of necessary medication forms a significant part of the criteria, as this is the source of medication to pharmacies. The subsequent management of medication as inventory and control over recall, storage, excess and disposal of expired medication serves the same purpose. Effective dispensing and distribution methods are therefore mandated to ensure timeously availability of correct medication. Finally, the success of effective medicine control is defined by the accuracy of the stock take ascertaining the results of managerial methods of medication. Platinum Health Pharmacies recorded an overall adherence level of 85 percent to the abovementioned criteria. This is a good indication of a strong, reliable and experienced pharmaceutical workforce that delivers an outstanding pharmaceutical service and is capable of maintaining effective medicine control. Although few shortcomings were identified, it is nevertheless recommended that Platinum Health Pharmacies plan the improvement of their risk management plans, and identify quality improvement projects in areas of medicine procurement. The implementation of key performance indicators, relevant to stock control, is also recommended. These, put into effect will assure optimisation of effective medicine control for Platinum Health Pharmacies, maintaining the benefits of cost containment and cost effective pharmaceutical service delivery. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2011.