COMPETITION IN REMANUFACTURING

We present a two‐period model of remanufacturing in the face of competition. In our model, an original equipment manufacturer (OEM) competes with a local remanufacturer (L) under many reverse logistics configurations for the returned items. After establishing the Nash Equilibrium in the second period sub‐game, we use numerical experiments for comparative statics. OEM wants to increase L'S remanufacturing cost. Surprisingly, while L competes in the sales market, she has incentives to reduce oem's remanufacturing cost. A social planner who wants to increase remanufacturing can give incentives to the OEM to increase the fraction available for remanufacturing, or reduce his remanufacturing costs.     

MIXED ASSEMBLY AND DISASSEMBLY OPERATIONS FOR REMANUFACTURING

In this paper we consider the problem of designing a mixed assembly‐disassembly line for remanufacturing. That is, parts from the disassembly and repair of used products can be used to build “new” products. This is a problem common to many OEM remanufacturers, such as Xerox or Kodak. We study two main configurations, under the assumption that the disassembly sequence is exactly the reverse of the assembly sequence. Under a parallel configuration, there exist two separate dedicated lines, one for assembly and one for disassembly, which are decoupled by buffers—from both disassembly operations, which have preference, as well as parts from an outside, perfectly reliable supplier. Under a mixed configuration, the same station is used for both disassembly and assembly of a specific part. The problem is studied using GI/G/c networks, as well as simulation. Due to a loss of pooling, we conclude that the parallel configuration outperforms the mixed line only when the variability of both arrivals and processing time are significantly higher for disassembly and remanufacturing than for assembly. Via a simulation, we explore the impact of having advanced yield information for the remanufacturing parts. We find that advanced yield information generally improves flow times; however, there are some instances where it lengthens flow times.     

PLANNING AND SCHEDULING THE REPAIR SHOPS OF THE DEUTSCHE LUFTHANSA AG: A HIERARCHICAL APPROACH

To plan and schedule the repair shops for recoverable parts at Deutsche Lufthansa AC, we designed a hierarchical model consisting of two levels. The top level calculates the optimal number of parts in the system to guarantee a certain service level while minimizing the capital tied up in parts. Given this provision, the lower level schedules the repair of parts so that the service level is actually maintained. Using queuing theory, the solution gives special attention to the different hierarchical dependencies. Lufthansa has implemented the model for its repair shops of electronic parts. Their experience with the model is discussed briefly.     

A COMPARISON OF PRODUCTION SCHEDULING POLICIES ON COSTS,SERVICE LEVEL,AND SCHEDULE CHANGES

We consider a single product, single level, stochastic master production scheduling (Mps ) model where decisions are made under rolling planning horizons. Outcomes of interest are cost, service level, and schedule stability. The subject of this research is the Mps control system: the method used in determining the amount of stock planned for production in each time period. Typically, Mps control systems utilize a single buffer stock. Here, two Mps dual-buffer stock systems are developed and tested by simulation. We extend the data envelopment analysis (dea ) methodology to aid in the evaluation of the simulation results, where Dea serves to increase the scope of the experimental design. Results indicate that the dual-buffer control systems outperform existing policies.     

COMPONENT COMMONALITY: MODELS WITH PRODUCT‐SPECIFIC SERVICE CONSTRAINTS*

Common components are used extensively for reasons including product postponement and expediting new product development. We consider a two‐stage assemble‐to‐order system with two products having uniformly distributed demand, one common component, and product‐specific components. We develop optimization models in which the cost‐minimizing inventory of the components must be determined and allocated to products in order to meet product‐specific service level constraints. We compare two different commonality models based on whether or not the products are prioritized. A distinctive feature of our study is the use of product‐specific service levels. We compare our results with models using aggregate service levels.     

ROBUSTNESS OF VARIOUS PRODUCTION CONTROL POLICIES IN SEMICONDUCTOR MANUFACTURING

This paper compares several different production control policies in terms of their robustness to random disturbances such as machine failures, demand fluctuations, and system parameter changes. Simulation models based on VLSI wafer fabrication facilities are utilized to test the performance of the policies. Three different criteria, namely, the average total WIP, the average backlog, and a cost function combining these measures, are used to evaluate performance. Among the policies tested, the Two‐Boundary Control policy outperforms the others.     

MANAGING A FLOW LINE WITH SINGLE‐KANBAN,DUAL‐KANBAN OR CONWIP

To control the production of different parts on a single flow line, managers can choose between the Single‐kanban, Dual‐kanban, and Conwip. This paper therefore compares the three different systems. The results show that Conwip consistently produces the shortest mean customer wait time and lowest total work‐in‐process. Our results also contradict the finding of a previous study, which showed that Dual‐kanban performed better than Single‐kanban. The different findings can, however, be attributed to the use of a material transfer policy, which favors the Dual‐kanban modeled in the previous study. Our study shows that transferring replenished containers immediately to downstream stations, increasing the number of cards, and reducing the withdrawal cycle reduce the mean customer wait time significantly.     

DETERMINISTIC TIME‐VARYING DEMAND LOT‐SIZING MODELS WITH LEARNING AND FORGETTING IN SETUPS AND PRODUCTION

We study the deterministic time‐varying demand lot‐sizing problem in which learning and forgetting in setups and production are considered simultaneously. It is an extension of Chiu's work. We propose a near‐optimal forward dynamic programming algorithm and suggest the use of a good heuristic method in a situation in which the computational effort is extremely intolerable. Several important observations obtained from a two‐phase experiment verify the goodness of the proposed algorithm and the chosen heuristic method.     

A STUDY OF THE UTILIZATION OF CAPACITY CONSTRAINED RESOURCES IN DRUM‐BUFFER‐ROPE SYSTEMS*

Goldratt, the originator of the Theory of Constraints (TOC), maintains that only the system's primary resource constraint(s) should be scheduled at 100% of capacity. All other resources should have excess capacity. This paper presents the results of a simulation experiment that studies how changes in the capacity utilization of a systems two most heavily utilized resources affect the performance of a drum‐buffer‐rope (DBR)scheduling system. The research demonstrates that 100% utilization of the primary constraint is not optimal. It also shows that DBR responds well to relatively low levels of increased capacity at the operations second most heavily utilized resource. This research also highlights several other issues related to capacity utilization that need further investigation.