The Experts below are selected from a list of 5865 Experts worldwide ranked by ideXlab platform
Haitao Liao - One of the best experts on this subject based on the ideXlab platform.
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Joint Production and Spare Part Inventory Control Strategy Driven by Condition Based Maintenance
IEEE Transactions on Reliability, 2010Co-Authors: Mitchell Rausch, Haitao LiaoAbstract:Throughput of a manufacturing process depends on the effectiveness of equipment maintenance, and the availability of Spare(service) Parts. This paper addresses a joint production and Spare Part inventory control strategy driven by condition based maintenance(CBM) for a piece of manufacturing equipment. Specifically, a critical unit is continuously monitored for performance degradation during operation. The amount of degradation is utilized to initiate replacement actions in conjunction with Spare Part inventory control under both production lot size, and due date constraints. A degradation limit maintenance policy is combined with a base stock Spare Part inventory control policy to manage the manufacturing process. The objectives are to minimize the Spare Part inventory, and the expected total operating cost. Constrained least squares approximation, and simulation-based optimization are utilized, in a heuristic two-step approach, to determine the optimal base-stock level of Spare Parts, along with the preventive maintenance threshold. The resulting joint decision ascertains the allowed stockout probability for Spare Parts, while incurring the minimal operating cost for the required production within a fixed production duration. A case study of an automotive engine manufacturing process is provided to demonstrate the proposed decision-making methodology in practical use.
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Spare Part inventory control driven by condition based maintenance
2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS), 2010Co-Authors: Haitao Liao, Mitchell RauschAbstract:The ability to predict and prevent equipment failures is essential for managing a manufacturing process. Once failure symptoms are detected, timely maintenance needs to be performed with the support of required Spare Parts. However, the availability of Spare Parts often becomes the bottleneck of process throughput, and sometimes expensive emergency orders of Spare Parts have to be placed to meet a production due date. This paper addresses a joint production and Spare Part inventory control strategy driven by condition based maintenance (CBM) for a piece of manufacturing equipment with a critical unit. Specifically, the amount of degradation of the unit is monitored continuously during operation and used to drive replacement actions and Spare Part inventory control under both production lot size and due date constraints. A degradation limit maintenance policy and a base-stock Spare Part inventory control policy are integrated to manage the manufacturing process. The objective is to ascertain the service level for Spare Parts while minimizing the total operating cost. To determine the optimal base-stock level of Spare Parts and maintenance threshold, a two-stage approach using constrained least square approximation and simulation-based optimization techniques is developed. An automotive engine manufacturing process is provided to demonstrate the use of the proposed decision making strategy.
Andrei Sleptchenko - One of the best experts on this subject based on the ideXlab platform.
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A clustering-based repair shop design for repairable Spare Part supply systems
Computers & Industrial Engineering, 2018Co-Authors: Hasan Hüseyin Turan, Andrei Sleptchenko, Shaligram Pokharel, Tarek Y. ElmekkawyAbstract:Abstract In this study, we address the design problem of a single repair shop in a repairable multi-item Spare Part supply system. We propose a sequential solution heuristic to solve the joint problem of resource pooling, inventory allocation, and capacity level designation of the repair shop with stochastic failure and repair time of repairables. The pooling strategies to obtain repair shop clusters/cells are handled by a K-median algorithm by taking into account the repair time and the holding cost of each repairable Spare Part. We find that the decomposition of the repair shop in sub-systems by clustering reduces the complexity of the problem and enables the use of queue-theoretical approximations to optimize the inventory and capacity levels. The effectiveness of the proposed approach is analyzed with several numerical experiments. The repair shop designs suggested by the approach provide around 10% and 30% cost reductions on an average when compared to fully flexible and totally dedicated designs, respectively. We also explore the impact of several input parameters and different clustering rules on the performance of the methodology and provide managerial insights.
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joint optimization of redundancy level and Spare Part inventories
Reliability Engineering & System Safety, 2016Co-Authors: Andrei Sleptchenko, Matthijs C Van Der HeijdenAbstract:We consider a “k-out-of-N” system with different standby modes. Each of the N components consists of multiple Part types. Upon failure, a component can be repaired within a certain time by switching the failed Part by a Spare, if available. We develop both an exact and a fast approximate analysis to compute the system availability. Next, we jointly optimize the component redundancy level with the inventories of the various Spare Parts. We find that our approximations are very accurate and suitable for large systems. We apply our model to a case study at a public organization in Qatar, and find that we can improve the availability-to-cost ratio by reducing the redundancy level and increasing the Spare Part inventories. In general, high redundancy levels appear to be useful only when components are relatively cheap and Part replacement times are high.
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using repair priorities to reduce stock investment in Spare Part networks
European Journal of Operational Research, 2005Co-Authors: Van Der Mc Matthieu Heijden, Andrei Sleptchenko, Van Aart A HartenAbstract:In this paper, we examine the impact of repair priorities in Spare Part networks. Several heuristics for assigning priorities to items as well as optimising stock levels are developed, extending the well-known VARI-METRIC method. We model repair shops by multi-class, multi-server priority queues. A proper priority setting may lead to a significant reduction in the inventory investment required to attain a target system availability (usually 10–20%). The saving opportunities are Particularly high if the utilisation of the repair shops is high and if the item types sharing the same repair shop have clearly different characteristics (price, repair time). For example, we find an investment reduction of 73% for a system with single server repair shops with an utilisation of 0.90 that handle five different item types.
Eugene Levner - One of the best experts on this subject based on the ideXlab platform.
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a network approach to modeling the multi echelon Spare Part inventory system with backorders and interval valued demand
International Journal of Production Economics, 2011Co-Authors: Eugene Levner, Yael Perlman, T C E Cheng, Ilya LevnerAbstract:A multi-echelon inventory system implies the existence of a hierarchy of stocking locations, and the dependence and interaction between them. We consider a multi-echelon, Spare-Part inventory management problem with outsourcing and backordering. The problem is characterized by deterministic repair time/cost, and supply and demand that lie within prescribed intervals and that vary over time. The objective is to minimize the total inventory and transportation costs. We develop a network model for problem analysis and present a network flow algorithm for solving the problem. We prove that the Wagner-Whitin property, known for the lot-sizing problem, can be extended to the Spare-Part inventory management problem under study.
Mitchell Rausch - One of the best experts on this subject based on the ideXlab platform.
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Joint Production and Spare Part Inventory Control Strategy Driven by Condition Based Maintenance
IEEE Transactions on Reliability, 2010Co-Authors: Mitchell Rausch, Haitao LiaoAbstract:Throughput of a manufacturing process depends on the effectiveness of equipment maintenance, and the availability of Spare(service) Parts. This paper addresses a joint production and Spare Part inventory control strategy driven by condition based maintenance(CBM) for a piece of manufacturing equipment. Specifically, a critical unit is continuously monitored for performance degradation during operation. The amount of degradation is utilized to initiate replacement actions in conjunction with Spare Part inventory control under both production lot size, and due date constraints. A degradation limit maintenance policy is combined with a base stock Spare Part inventory control policy to manage the manufacturing process. The objectives are to minimize the Spare Part inventory, and the expected total operating cost. Constrained least squares approximation, and simulation-based optimization are utilized, in a heuristic two-step approach, to determine the optimal base-stock level of Spare Parts, along with the preventive maintenance threshold. The resulting joint decision ascertains the allowed stockout probability for Spare Parts, while incurring the minimal operating cost for the required production within a fixed production duration. A case study of an automotive engine manufacturing process is provided to demonstrate the proposed decision-making methodology in practical use.
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Spare Part inventory control driven by condition based maintenance
2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS), 2010Co-Authors: Haitao Liao, Mitchell RauschAbstract:The ability to predict and prevent equipment failures is essential for managing a manufacturing process. Once failure symptoms are detected, timely maintenance needs to be performed with the support of required Spare Parts. However, the availability of Spare Parts often becomes the bottleneck of process throughput, and sometimes expensive emergency orders of Spare Parts have to be placed to meet a production due date. This paper addresses a joint production and Spare Part inventory control strategy driven by condition based maintenance (CBM) for a piece of manufacturing equipment with a critical unit. Specifically, the amount of degradation of the unit is monitored continuously during operation and used to drive replacement actions and Spare Part inventory control under both production lot size and due date constraints. A degradation limit maintenance policy and a base-stock Spare Part inventory control policy are integrated to manage the manufacturing process. The objective is to ascertain the service level for Spare Parts while minimizing the total operating cost. To determine the optimal base-stock level of Spare Parts and maintenance threshold, a two-stage approach using constrained least square approximation and simulation-based optimization techniques is developed. An automotive engine manufacturing process is provided to demonstrate the use of the proposed decision making strategy.
Van Der Mc Matthieu Heijden - One of the best experts on this subject based on the ideXlab platform.
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inventory reduction in Spare Part networks by selective throughput time reduction
International Journal of Production Economics, 2013Co-Authors: Van Der Mc Matthieu Heijden, E Elisa M Alvarez, Jmj Marco SchuttenAbstract:We consider combined inventory control and throughput time reduction in multi-echelon, multi-indenture Spare Part networks for system upkeep of capital goods. We construct a model in which standard throughput times (TPTs) for repair and transportation can be reduced at additional costs. We first estimate the marginal impact of TPT reduction on the system availability. Next, we develop an optimization heuristic for the cost trade-off between TPT reduction and Spare Part inventories. In a case study at Thales Netherlands with limited options for TPT reduction, we find a net saving of 5.6% on Spare Part inventories. In an extensive numerical experiment, we find a 20% cost reduction on average compared to standard Spare Part inventory optimization. TPT reductions downstream in the Spare Part supply chain appear to be the most effective.
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using repair priorities to reduce stock investment in Spare Part networks
European Journal of Operational Research, 2005Co-Authors: Van Der Mc Matthieu Heijden, Andrei Sleptchenko, Van Aart A HartenAbstract:In this paper, we examine the impact of repair priorities in Spare Part networks. Several heuristics for assigning priorities to items as well as optimising stock levels are developed, extending the well-known VARI-METRIC method. We model repair shops by multi-class, multi-server priority queues. A proper priority setting may lead to a significant reduction in the inventory investment required to attain a target system availability (usually 10–20%). The saving opportunities are Particularly high if the utilisation of the repair shops is high and if the item types sharing the same repair shop have clearly different characteristics (price, repair time). For example, we find an investment reduction of 73% for a system with single server repair shops with an utilisation of 0.90 that handle five different item types.