33,360 research outputs found

    The value of coordination in a two echelon supply chain: Sharing information, policies and parameters.

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    We study a coordination scheme in a two echelon supply chain. It involves sharing details of replenishment rules, lead-times, demand patterns and tuning the replenishment rules to exploit the supply chain's cost structure. We examine four different coordination strategies; naïve operation, local optimisation, global optimisation and altruistic behaviour on behalf of the retailer. We assume the retailer and the manufacturer use the Order-Up-To policy to determine replenishment orders and end consumers demand is a stationary i.i.d. random variable. We derive the variance of the retailer's order rate and inventory levels and the variance of the manufacturer's order rate and inventory levels. We initially assume that costs in the supply chain are directly proportional to these variances (and later the standard deviations) and investigate the options available to the supply chain members for minimising costs. Our results show that if the retailer takes responsibility for supply chain cost reduction and acts altruistically by dampening his order variability, then the performance enhancement is robust to both the actual costs in the supply chain and to a naïve or uncooperative manufacturer. Superior performance is achievable if firms coordinate their actions and if they find ways to re-allocate the supply chain gain.Bullwhip; Global optimisation; Inventory variance; Local optimisation; Supply chains; Studies; Coordination; Supply chain; IT; Replenishment rule; Rules; Demand; Patterns; Cost; Structure; Strategy; Retailer; Policy; Order; Variance; Inventory; Costs; Options; Variability; Performance; Performance enhancement; Firms;

    Exploring the bullwhip effect by means of spreadsheet simulation.

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    One of the main supply chain deficiencies is the bullwhip effect: demand fluctuations increase as one moves up the supply chain from retailer to manufacturer. The Beer Distribution Game is widely known for illustrating these supply chain dynamics in class. In this paper we present a spreadsheet application, exploring the two key causes of the bullwhip effect: demand forecasting and the type of ordering policy. We restrict our attention to a single product two-echelon system and illustrate how tuning the parameters of the replenishment policy induces or reduces the bullwhip effect. We also demonstrate how bullwhip reduction (dampening the order variability) may have an adverse impact on inventory holdings and/or customer service. As such, the spreadsheets can be used as an educational tool to gain a clear insight into the use of inventory control policies and forecasting in relation to the bullwhip effect and customer service.Bullwhip effect; Replenishment rules; Forecasting techniques; Spreadsheet simulation; Beer distribution game;

    Optimizing inventory levels using financial, lifecycle and forecast variance data

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    Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2007.Includes bibliographical references (leaves 47-48).Significant inventory write-offs have recently plagued ATI Technologies, a world leader in graphics and media processors. ATI's product-centric culture has long deterred attention from supply chain efficiency. Given that manufacturing lead time exceeds customer order lead time for its semiconductors, ATI relies heavily on their demand forecasting team to instigate supply chain activities. The PC business unit forecasting team translates market information into product-line forecast and also sets finished goods inventory levels intended to offset demand uncertainty. Today's inventory decisions are made in response to customer escalations, often ignoring financial implications. To add necessary rigor when setting these inventory levels, this thesis presents a model using wafer and unit cost, profit margin, product lifecycle stage and historical forecast error to categorize products into inventory risk levels. The resultant risk levels become a critical input to monthly demand-supply meetings with marketing, operations and senior executives - the outcome of which are wafer orders and assembly and test plans at the world's largest contract foundries and subcontractors. Finally, the 2006 acquisition of ATI by Advanced Micro Devices (AMD) offers unforeseen flexibility, scale and challenges to the outsourced semiconductor supply chain.by Irene S. Hwang.S.M.M.B.A

    A Hybrid Fuzzy Approach to Bullwhip Effect in Supply Chain Networks

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    COMPETITIVE ANALYSIS OF U.S. FOOD PROCESSING PLANTS

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    This paper presents a model-based approach for competitive analysis of manufacturing plants in the U. S. food processing industry. As part of this approach, plant competitiveness is measured using Operational Competitiveness Ratings Analysis (OCRA) -- a new non-parametric method of computing relative inefficiency. Drivers of competitiveness are identified in terms of policies related to plant structure and infrastructure. Policies related to plant structure are those decisions that are related with "bricks and mortar" and have long term implications, such as decisions related to plant size and capacity. Policies related to plant infrastructure are decisions related to how the " bricks and mortar" are used. These policies are typically under the direct control of the operations managers and have a short-term orientation, such as decisions related to equipment, quality, inventory, workforce and confusion-engendering activities (e.g. new product introductions and product variety). The empirical analysis is based on detailed cross-sectional data on 20 processed food manufacturing plants. With respect to plant structure, the results suggest that small sized food processing plants are competitive, and both capacity underutilization and overutilization are detrimental to plant competitiveness. Among the significant results with respect to plant infrastructure, equipment maintenance, quality management programs, packaging supplies inventory, workforce training and product variety are positively associated with plant competitiveness. The results also suggest that introduction of new products disrupts plant operations, at least in the short run, and is negatively associated with plant competitiveness.Agribusiness,

    Risk-Smoothing Across Time and the Demand for Inventories: A Mean-Variance Approach

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    The standard production smoothing model of inventory demand cannot represent the added incentives for smoothing risks or explain the impact of market shocks that independently affect expectations and uncertainty. Those limitations are overcome by modeling inventory demand as a problem in deterministic optimal control, with the risk-averse firm maximizing utility that is a separable function of the mean and variance of returns and the firm controlling on two decision variables, production and inventory investment. Support for the mean-variance approach comes from regressions using Survey of Professional Forecasters data to show how changes in the mean forecasts of the GDP price deflator and changes in the disagreement among deflator forecasts can explain changes in aggregate inventory investment over time. Further support comes from the ability of the model to explain the excess volatility of industry output over sales—a fact at odds with the production smoothing theory.

    Computing Replenishment Cycle Policy under Non-stationary Stochastic Lead Time

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    Inventory dynamics and the bullwhip effect : studies in supply chain performance

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