4,804 research outputs found

    Estimating obsolescence risk from demand data - a case study

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    In this paper obsolescence of service parts is analyzed in a practical environment. Basedon the analysis, we propose a method that can be used to estimate the risk of obsolescenceof service parts. The method distinguishes groups of service parts. For these groups, therisk of obsolescence is estimated using the behavior of similar groups of service parts inthe past. The method uses demand data as main information source, and can therefore beapplied without the use of an expert's opinion. We will give numerical values for the risk ofobsolescence obtained with the method, and the e®ects of these values on inventory controlwill be examined.inventory;forecasting;obsolescence;spare parts

    Modeling Overstock

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    Two main problems have been emerging in supply chain management: the increasing pressure to reduce working capital and the growing variety of products. Most of the popular indicators have been developed based on a controlled environment. A new indicator is now proposed, based on the uncertainty of the demand, the flexibility of the supply chains, the evolution of the products lifecycle and the fulfillment of a required service level. The model to support the indicator will be developed within the real options approach.overstock, stock management, real options

    Efficient inventory control for imperfect quality items

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    In this paper, we present a general EOQ model for items that are subject to inspection for imperfect quality. Each lot that is delivered to the sorting facility undertakes a 100 per cent screening and the percentage of defective items per lot reduces according to a learning curve. The generality of the model is viewed as important both from an academic and practitioner perspective. The mathematical formulation considers arbitrary functions of time that allow the decision maker to assess the consequences of a diverse range of strategies by employing a single inventory model. A rigorous methodology is utilised to show that the solution is a unique and global optimal and a general step-by-step solution procedure is presented for continuous intra-cycle periodic review applications. The value of the temperature history and flow time through the supply chain is also used to determine an efficient policy. Furthermore, coordination mechanisms that may affect the supplier and the retailer are explored to improve inventory control at both echelons. The paper provides illustrative examples that demonstrate the application of the theoretical model in different settings and lead to the generation of interesting managerial insights

    An Evaluation of End of Maintenance Dates and Lifetime Buy Estimations for Electronic Systems Facing Obsolescence

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    The business of supporting legacy electronic systems is challenging due to mismatches between the system support life and the procurement lives of the systems' constituent components. Legacy electronic systems are threatened with Diminishing Manufacturing Sources and Material Shortages (DMSMS)-type obsolescence, and the extent of their system support lives based on existing replenishable and non-replenishable resources may be unknown. This thesis describes the development of the End of Repair/End of Maintenance (EOR/EOM) model, which is a stochastic discrete-event simulation that follows the life history of a population of parts and cards and operates from time-to-failure distributions that are either user-defined, or synthesized from observed failures to date. The model determines the support life (and support costs) of the system based on existing inventories of spare parts and cards, and optionally harvesting parts from existing cards to further extend the life of the system. The model includes: part inventory segregation, modeling of part inventory degradation and periodic inventory inspections, and design refresh planning. A case study using a real legacy system comprised of 117,000 instances of 70 unique cards and 4.5 million unique parts is presented. The case study was used to evaluate the system support life (and support costs) through a series of different scenarios: obsolete parts with no failure history and never failing, obsolete parts with no failure history but immediately incurring their first failures with and without the use of part harvesting. The case study also includes analyses for recording subsequent EOM and EOR dates, sensitivity analyses for selected design refreshes that maximize system sustainment, and design refresh planning to ensure system sustainment to an end of support date. Lifetime buys refer to buying enough parts from the original manufacturer prior to the part's discontinuance in order to support all forecasted future part needs throughout the system's required support life. This thesis describes the development of the Lifetime Buy (LTB) model, a reverse-application of the EOR/EOM model, that follows the life history of an electronic system and determines the number of spares required to ensure system sustainment. The LTB model can generate optimum lifetime buy quantities of parts that minimizes the total life-cycle cost associated with the estimated lifetime buy quantity

    Inventory drivers in a pharmaceutical supply chain

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    In recent years, inventory reduction has been a key objective of pharmaceutical companies, especially within cost optimization initiatives. Pharmaceutical supply chains are characterized by volatile and unpredictable demands –especially in emergent markets-, high service levels, and complex, perishable finished-good portfolios, which makes keeping reasonable amounts of stock a true challenge. However, a one-way strategy towards zero-inventory is in reality inapplicable, due to the strategic nature and importance of the products being commercialised. Therefore, pharmaceutical supply chains are in need of new inventory strategies in order to remain competitive. Finished-goods inventory management in the pharmaceutical industry is closely related to the manufacturing systems and supply chain configurations that companies adopt. The factors considered in inventory management policies, however, do not always cover the full supply chain spectrum in which companies operate. This paper works under the pre-assumption that, in fact, there is a complex relationship between the inventory configurations that companies adopt and the factors behind them. The intention of this paper is to understand the factors driving high finished-goods inventory levels in pharmaceutical supply chains and assist supply chain managers in determining which of them can be influenced in order to reduce inventories to an optimal degree. Reasons for reducing inventory levels are found in high inventory holding and scrap related costs; in addition to lost sales for not being able to serve the customers with the adequate shelf life requirements. The thesis conducts a single case study research in a multi-national pharmaceutical company, which is used to examine typical inventory configurations and the factors affecting these configurations. This paper presents a framework that can assist supply chain managers in determining the most important inventory drivers in pharmaceutical supply chains. The findings in this study suggest that while external and downstream supply chain factors are recognized as being critical to pursue inventory optimization initiatives, pharmaceutical companies are oriented towards optimizing production processes and meeting regulatory requirements while still complying with high service levels, being internal factors the ones prevailing when making inventory management decisions. Furthermore, this paper investigates, through predictive modelling techniques, how various intrinsic and extrinsic factors influence the inventory configurations of the case study company. The study shows that inventory configurations are relatively unstable over time, especially in configurations that present high safety stock levels; and that production features and product characteristics are important explanatory factors behind high inventory levels. Regulatory requirements also play an important role in explaining the high strategic inventory levels that pharmaceutical companies hold

    Inventory management strategy for the supply chain of a medical device company

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    Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 97-98).In the medical device industry, many companies rely on a high inventory strategy in order to meet their customers' urgent requirements, sometimes leading to excessive inventory. This problem is compounded when it involves a long supply chain with several stages of activities and with long delivery and processing lead times. It is further exacerbated when high inventory leads to the frequent expiry of items with short shelf lives, which is typical of surgical items that have to be sterilized. Good supply chain strategies can potentially lead to a significant reduction of the supply chain cost. Through the use of relevant mathematical formulae and Strategic Inventory Placement optimization method, this paper examines the extent of the usefulness of a few possible strategies, such as kitting architecture change and continuous review system, for a family of medical emergency surgical kits across the whole supply chain for a medical device company. The result shows that reducing production lead time and review period, as well as adopting certain kitting architecture changes can reduce inventory value by more than 60% and operating cost by more than 20%. In addition, the paper shows that the Strategic Inventory Placement method can further reduce the total inventory value and operating cost by increasing the inventory of finished products and reducing the inventory of components in the supply chain.by Poi Chung Tjhin and Rachita Pandey.M.Eng.in Logistic

    Estimating obsolescence risk from demand data - a case study

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    In this paper obsolescence of service parts is analyzed in a practical environment. Based on the analysis, we propose a method that can be used to estimate the risk of obsolescence of service parts. The method distinguishes groups of service parts. For these groups, the risk of obsolescence is estimated using the behavior of similar groups of service parts in the past. The method uses demand data as main information source, and can therefore be applied without the use of an expert's opinion. We will give numerical values for the risk of obsolescence obtained with the method, and the e®ects of these values on inventory control will be examined

    CONCURRENT MULTI-PART MULTI-EVENT DESIGN REFRESH PLANNING MODELS INCORPORATING SOLUTION REQUIREMENTS AND PART-UNIQUE TEMPORAL CONSTRAINTS

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    Technology obsolescence, also known as DMSMS (Diminishing Manufacturing Sources and Material Shortages), is a significant problem for systems whose operational life is much longer than the procurement lifetimes of their constitute components. The most severely affected systems are sustainment-dominated, which means their long-term sustainment (life-cycle) costs significantly exceed the procurement cost for the system. Unlike high-volume commercial products, these sustainment-dominated systems may require design refreshes to simply remain manufacturable and supportable. A strategic method for reducing the life-cycle cost impact of DMSMS is called refresh planning. The goal of refresh planning is to determine when design refreshes should occur (or what the frequency of refreshes should be) and how to manage the system components that are obsolete or soon to be obsolete at the design refreshes. Existing strategic management approaches focus on methods for determining design refresh dates. While creating a set of feasible design refresh plans is achievable using existing design refresh planning methodologies, the generated refresh plans may not satisfy the needs of the designers (sustainers and customers) because they do not conform to the constraints imposed on the system. This dissertation develops a new refresh planning model that satisfies refresh structure requirements (i.e., requirements that constrain the form of the refresh plan to be periodic) and develops and presents the definition, generalization, synthesis and application of part-unique temporal constraints in the design refresh planning process for systems impacted by DMSMS-type obsolescence. Periodic refresh plans are required by applications that are refresh deployment constrained such as ships and submarines (e.g., only a finite number of dry docks are available to refresh systems). The new refresh planning model developed in this dissertation requires 50% less data and runs 50% faster than the existing state-of-the-art discrete event simulation solutions for problems where a periodic refresh solution is required

    Multi-Source Backlogged Probabilistic Inventory Model for Crisp and Fuzzy Environment

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    This paper proposed a multi-item multi-source probabilistic periodic review inventory model under a varying holding cost constraint with zero lead time when: (1) the stock level decreases at a uniform rate over the cycle. (2) some costs are varying. (3) the demand is a random variable that follows some continuous distributions as (two-parameter exponential, Kumerswamy, Gamma, Beta, Rayleigh, Erlang distributions).The objective function under a constraint is imposed here in crisp and fuzzy environment. The objective is to find the optimal maximum inventory level for a given review time that minimize the expected annual total cost. Furthermore, a comparison between given distributions is made to find the optimal distribution that achieves the model under considerations. Finally, a numerical example is applied
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