George Tagaras

A SURVEY OF RECENT DEVELOPMENTS IN THE DESIGN OF ADAPTIVE CONTROL CHARTS

This survey presents, in a comprehensive way, the substantial recent developments in the statistical and economic design of adaptive or dynamic charts that allow some of their parameters to change during production. After discussing several different me..

Effects of Pooling on the Optimization and Service Levels of Two-Location Inventory Systems

Abstract The study of inventory distribution systems with two locations and random demand is the subject of this paper. It is shown that under certain conditions a policy of complete pooling between the locations minimizes the expected costs for the system. A solution procedure is proposed for the derivation of the optimal parameters determining the ordering and lateral transshipmentrules. Relationships between the measures of service level before and after pooling are derived, and it is concluded that pooling always improves the service levels at both locations. Minimization of total costssubject to service level constraints is also studied. Numerical examples serve to illustrate the analytical results. Handled by the Editor-In-Chief.

A Periodic Review Inventory System with Emergency Replenishments

This paper proposes and analyzes a periodic review inventory system with two replenishment modes. Regular orders are placed periodically following a base stock policy on inventory position, and arrive at the stocking location after a deterministic lead time. The location also has the option of placing emergency orders, characterized by a shorter lead time but higher acquisition cost, in case of imminent stockouts. Thus, at some appropriate time in the replenishment cycle, the necessity and size of an emergency order is determined according to a base stock policy on net stock. The timing of the emergency order is such that this order arrives and can be used to satisfy the demand in the time period just before the arrival of a regular order, when the likelihood of a stockout is highest. An approximate cost model is developed which can easily be optimized with respect to the order-up-to parameters. This model is used as the basis for a heuristic algorithm, which leads to solutions that are very close to the exact optimal solutions determined through simulation. It is shown that the proposed system offers substantial cost savings relative to a system without the emergency replenishment option.

Impact of uncertainty in the quality of returns on the profitability of a single-period refurbishing operation

This paper investigates how the profitability of reuse activities is affected by uncertainty regarding the quality of returned products. Specifically, we examine a reverse supply chain consisting of two collection sites and a refurbishing site, which faces stochastic demand for refurbished products in a single-period setting. The quality of returns (refurbishing yield) becomes known only after the transportation of the products to the refurbishing site. We prove that the expected profit function has a unique optimal solution (procurement and production quantities) and we derive the conditions under which it is optimal to use only one of the collection sites. The analysis is supported by numerical results which provide insights regarding the effect of the uncertain yields at the two collection sites and their correlation on optimal decisions and system profitability.

On the attractiveness of sorting before disassembly in remanufacturing

We examine the attractiveness of simple sorting procedures characterized by limited accuracy just before disassembly and remanufacturing of used products. That type of quick sorting is often made possible through the installation of simple electronic devices in new products, which record basic usage data and provide information about the remanufacturability of the product without the need for its disassembly. We study a two-level reverse supply chain with remanufacturing and we concentrate on the single-period setting. There is uncertainty about the remanufacturability of used products and we derive the conditions under which quick sorting is economically justifiable. We show that the economic attractiveness of sorting depends on the costs of transportation, disposal, disassembly, the cost and accuracy of the sorting procedure and the expected quality of the returned items.

Inventory control of spare parts using a Bayesian approach: A case study

This paper presents a case study of applying a Bayesian approach to forecast demand and subsequently determine the appropriate parameter S of an (S-1,S) inventory system for controlling spare parts of electronic equipment. First, the problem and the current policy are described. Then, the basic elements of the Bayesian approach are introduced and the procedure for calculating the appropriate parameter S is illustrated. Finally, we present the results of applying the Bayesian approach in an innovative way to determine the stock levels of three types of circuit packs at several locations. According to the proposed method, a lower base stock than the one currently used is sufficient to achieve the desired service level.

Drivers and obstacles of product recovery activities in the Greek industry

Purpose – The purpose of this study is to assess the current state of affairs in the product recovery domain as perceived by Greek industry. The extent of involvement of original equipment manufacturers in product recovery activities (PRA), the direct profitability of PRA and the most important specific drivers and barriers to the implementation of PRA are the main issues that are explored. The paper also investigates whether these issues are affected by two factors: level of PRA and profitability of existing PRA.Design/methodology/approach – A questionnaire‐based survey was conducted and 312 valid responses were received. Statistical analysis of the responses was carried out via non‐parametric χ2‐tests for homogeneity, Mann‐Whitney U‐tests and Friedman two‐way analysis of variance.Findings – The results suggest that PRA are not very much developed by manufacturing companies in Greece. The companies engage in PRA mainly because they want to provide service to their customers; they are hesitant to embark o...

Optimal preventive maintenance for equipment with two quality states and general failure time distributions

We present an economic model for the optimization of preventive maintenance in a production process with two quality states. The equipment starts its operation in the in-control state but it may shift to the out-of-control state before failure or scheduled preventive maintenance. The time of shift and the time of failure are generally distributed random variables. The two states are characterized by different failure rates and revenues. We first derive the structure of the optimal maintenance policy, which is defined by two critical values of the equipment age that determine when to perform preventive maintenance depending on the actual (observable) state of the process. We then provide properties of the optimal solution and show how to determine the optimal values of the two critical maintenance times accurately and efficiently. The proposed model and, in particular, the behavior of the optimal solution as the model parameters and the shift and failure time distributions change are illustrated through numerical examples.

Comparing the Effectiveness of Various Bayesian X Control Charts

In an attempt to improve the procedures for statistical process control many researchers have developed and proposed a variety of adaptive control charts in the last decade. The common characteristic of those charts is that one or more of the chart parameters (sampling interval, sample size,control limits) is allowed to change during operation, taking into account current sample information. Due to their flexibility, adaptive charts are more effective than their static counterparts but they are also more complex in terms of implementation. The purpose of this paper is to evaluate the economic performance of various adaptive control schemes to derive conclusions about their relative effectiveness. The analysis concentrates on Bayesian control charts used for monitoring the process mean in finite production runs. We present dynamic programming formulations and properties of the optimal solutions, which we then use to solve a number of numerical examples. The results from our comparative numerical study indicate that the chart parameter having the most positive impact on the economic performance by being adaptive is the sampling interval. It is therefore sufficient in most cases to use control charts with adaptive sampling intervals rather than other types of partially adaptive charts or the more complicated fully adaptive control charts.

Dynamic control charts for finite production runs

Abstract A dynamic programming model is developed for the optimization of statistical process control for finite production runs. The case of one-sided control charts for variables is examined first. A dynamic chart allows all three parameters, namely the sampling interval, sample size and control limit location, to change during production, as sample information becomes available and the state of the process is updated using Bayesian methods. The economic performance of the optimal dynamic chart is compared to that of the optimal static control chart through a number of numerical examples. It is concluded that substantial improvements may result from the adoption of dynamic charts. The benefits of direct observability of assignable causes are also estimated. Then, a generalized theoretical formulation is provided for two-sided dynamic control charts. The increased size of the state and decision spaces leads to a discussion of practical implementation issues. An example of computing transition probabilities between states of different stages is given. The major conclusion of this research is that significant cost savings may be realized through the application of dynamic control charts and even greater benefits may be reaped by investing in process understanding and improvements.