ON THE USE OF BUFFER INVENTORIES TO MINIMIZE COSTS WITH AN UNRELIABLE MACHINE

In this paper, we discuss the problem of quality control with an unreliable machine which produces defects at a rate of Λ₀, per unit when in-control and a rate of Lambda; ₁, when out-of-control (where Λ₁ Λ ₀). Every h time periods, we sample n units, count the number of defects, and (using a process based on a Shewart c-chart) test the hypothesis that the machine is in control by comparing the total number of defects to an upper control limit (UCL). More important, we introduce the concept that a buffer inventory which immediately follows the unreliable machine may reduce expected total costs. This buffer serves to delay the movement of items from the unreliable machine to the next stage of the production process. In this way, we can isolate and repair most defective items before they are embedded in a product downstream or sold to customers where repair is more costly. To search for the optimal control policy, we find bounds for n, h, and UCL; given values for these variables, we show how the optimal buffer size can be determined directly. Numerical results illustrate the magnitude of potential savings.     

Detecting Threats in Star Graphs

In this paper, we consider the problem of searching a network for intruders. We propose a strategy for capturing the intruder in the popular interconnection topology, the star network. According to the proposed strategy, a team of collaborative software agents are responsible for capturing a hostile intruder (e.g. a virus). These agents asynchronously move along the network links and the intruder has the capability of escaping arbitrarily fast.     

Economic control and inspection policies for high-speed unreliable production systems

In this paper, we consider a high-speed production process, which produces defects at a known rate while in control. When the process goes out of control, it produces defects at a higher rate. In this study, we revisit the role of the distribution of the process in-control time when managing such systems. Specifically, we focus on two management schemes, a control policy and an inspection policy. In the control policy, when the number of defects produced reaches a threshold, the process is stopped and inspected. In contrast, in the inspection policy, the process is stopped and inspected periodically. We derive the operating characteristics of the system and devise schemes for finding the optimal policy parameters for each policy. We also investigate the behavior of the optimal policy parameters, compare the performances of the control and inspection policies and identify the environments in which each of these policies out performs the other one using a numerical experiment.     

Production Lot-Sizing Under Learning Effects: An Efficient Solution Technique

In this paper, we consider a production-inventory model which assumes that learning occurs as a function of the number of units produced. We analyze two cases: the first case allows for no forgetting between production runs and the second case (a generalization of the first case) allows for some given degree of forgetting between production runs. In the first case, we show that learning only has an impact on initial lot-sizes for large order quantities and that steady state lot-sizes will approach the traditional EOQ amount. In addition, we show that succeeding lot-sizes are always nonincreasing. Applying these results to the second case when forgetting occurs, we develop efficient heuristic algorithms with complexity O(N logN) to determine order quantities. Results from our algorithms are compared to optimal solutions; these comparisons indicate that our algorithms usually provide solutions within one percent of the optimal cost.     

Two-Parameter Approximations For Multi-Echelon Repairable Inventory Models With Batch Ordering Policy

In this paper we present a model for multi-echelon repairable systems with batch ordering policy at the bases. Such an ordering policy is desirable when demand rates and/or the set up cost for ordering are relatively high. Operating characteristics of such a system are analyzed. A two-parameter approximation scheme for the distribution of the number of orders outstanding and consequently backorders is developed, and its performance evaluated. It is found that, under a variety of scenarios including both finite and infinite servers at the repair facility, the approximation scheme is very effective in providing a relatively simple means to determine the stocking levels at both the depot and the bases to minimize the cost of inventory holding and backorders. For the special case when the batch size is one, we confirm the effectiveness of the use of the negative binomial distribution as an approximation for the distribution of orders outstanding, as suggested by recent studies, under a much more general setting.     

IIE Transactions Special Issue on Planning and Coordination of Supply Chains with Outsourcing

Introduction

IIE Transactions Special Issue on Planning and Coordination of Supply Chains with Outsourcing     

ORDER EXPEDITION IN MULTI-ECHELON PRODUCTION/DISTRIBUTION SYSTEMS

In this paper we study a multi-echelon production/distribution system where the retail centers are allowed to replenish their inventory through a normal resupply channel or an expedited resupply channel by incurring an additional cost. An approximation scheme to find the operating characteristics of such systems is developed. The results of a numerical study indicate that significant cost savings can be achieved by using the policy suggested in this paper.     

Analysis of maintenance policies for M machines with deteriorating performance

In this paper, we consider the maintenance scheduling of a group of M identical machines, the performance of which deteriorates with usage. Examples of such situations are frequently found in the heavy machine tooling, petro-chemical and semi-conductor industries among others. Assuming a limited maintenance resource and that the maintenance times are i.i.d., we propose a dynamic maintenance policy which utilities the information about the number of operating machines and their ages. We analyze the system for the special cases of constant and exponentially distributed maintenance times. We investigate the impact of maintenance time variability on system performance and evaluate the performance of various maintenance policies within the proposed policy class when the expected profit rate is maximized.     

An improved ordering policy for continuous review inventory systems with arbitrary inter-demand time distributions

In this paper, we revisit the optimality of (s,S) policies in continuous review inventory models where demand forms a renewal process. We explain why when orders are placed at demand epochs, (s,S) policies are not optimal in general, and propose a simple but practical ordering policy by introducing a delay in order placement as a policy parameter. Under our proposed policy, the operating characteristics of such systems can be evaluated using the existing results in the literature. In order to demonstrate the effectiveness of our policy, we restrict our analysis to a special class of inventory systems where demand follows a counting process, fixed ordering costs are negligible and leadtimes are constant. We derive expressions for the operating characteristics of such systems under our policy and present insights on the behavior of the policy parameters which minimize the average total cost rate under our policy. Using these results, we develop an efficient heuristic for computing the policy parameters. Finally, we investigate the effectiveness of our policy in comparison to policies which place orders only at demand epochs. The results of our numerical experiment indicate that our policy can result in a significant savings.