Spare Parts Inventory System Research Articles

Batch Ordering Policy of Multi-location Spare Parts Inventory System with Emergency Lateral Transshipments

Abstract A batch ordering model for multi-location spare parts inventory system with emergency lateral transshipments is provided, and algorithms for calculating the probabilities of demand fulfillment by inventory point self, by transshipment, or backorder are also given. Based on these, a procedure is given to find the best ordering point for a constrained model that minimizes holding plus transshipment cost subject to a certain service level, assuming the ordering quantity is predetermined. The results were tested through simulation.

Two-echelon multi-item spare parts systems with emergency supply flexibility and waiting time constraints

We consider a two-echelon multi-item spare parts inventory system in which supply flexibility through both lateral transshipments and direct deliveries are used in response to stock-outs. We develop a simple heuristic to determine the stocking levels for each type of spare part at the central warehouse and local warehouses minimizing the expected total system cost subject to a target level for the average waiting time across items at each local warehouse. Numerical comparisons between the heuristic's objective function values and lower bounds obtained by applying Lagrangian relaxation techniques show that the heuristic performs well. A study to evaluate the relative merits of a two-echelon system as opposed to a single-echelon system is also presented. We find that the presence of lateral transhipment improves the performance of the single-echelon system considerably. A two-echelon system is only worth implementing when lateral transhipments are not possible.

Efficient heuristics for two-echelon spare parts inventory systems with an aggregate mean waiting time constraint per local warehouse

This paper presents solution procedures for determining close- to-optimal base stock policies in a multi-item two-echelon spare parts inventory system. The system consists of a central warehouse and multiple local warehouses, and there is a target for the aggregate mean waiting time per local warehouse. We develop four different heuristics and derive a lower bound on the optimal total cost. The effectiveness of each heuristic is assessed by the relative gap between the heuristic’s total cost and the lower bound. The results of the computational experiments show that a greedy procedure performs most satisfactorily. It is accurate as indicated by relatively small gaps, easy to implement, and the computational requirements are limited. Its computational efficiency can be increased by using Graves’ approximate evaluation method instead of an exact evaluation method, while the results remain accurate. That results in a feasible algorithm for real-life cases with many items and local warehouses.

An efficient heuristic optimization algorithm for a two-echelon ( R, Q) inventory system

This paper presents a two-echelon non-repairable spare parts inventory system that consists of one warehouse and m identical retailers and implements the reorder point, order quantity ( R, Q) inventory policy. We formulate the policy decision problem in order to minimize the total annual inventory investment subject to average annual ordering frequency and expected number of backorder constraints. In order to solve the problem, we decompose the system by echelon and location, derive expressions for the inventory policy parameters, and develop an iterative heuristic optimization algorithm. Experimentation showed that our optimization algorithm is an efficient and effective method for setting the policy parameters in large-scale inventory systems.

Object-Oriented Multi-Indenture Multi-Echelon Spare Parts Supply Chain Simulation Model

In supply chain networks, the flow of material occurs between various business entities such as suppliers, manufactures, distributors, and retailers, which can be considered as the various echelons (levels) in a multi-echelon supply chain network. Spare parts supply chain management deals with optimizing stocking, purchasing, repairing, and disposing activities of purchased parts and their components for maintaining a successful user-service level for a system involving repair and operating functions. A spare parts inventory system has products that will have relationships with other products. A multi-indenture structure defines the structure of the products that flow through the supply chain system. In this article, we present a standardized, object-oriented, data-driven, simulation framework for the evaluation of multi-echelon multi-indenture spare part supply chain networks.

Two-echelon spare parts inventory system subject to a service constraint

In this paper, we consider a spare parts inventory problem faced by a manufacturer of electronic machines with expensive parts that are located at various customer locations. The parts fail infrequently according to a Poisson process. To serve customers when a failure occurs, the manufacturer operates a central warehouse and many field depots that stock spare parts. The central warehouse acts as a repair facility and replenishes stock at the field depots. There is a centralized decision-maker who manages the inventory in both the central warehouse and the field depots. We develop a continuous review, base stock policy for this two-echelon, multi-item spare parts inventory system. We formulate a model to minimize the system-wide inventory cost subject to a response time constraint at each field depot. We present an efficient heuristic algorithm and study its computational effectiveness.

Dynamic inventory targets revisited

This paper is about periodic review inventory systems which are controlled by replenishing the inventory up to a target level which is set based on a demand forecast generated from past demands. It is shown that the replenishments will fluctuate more than final demand. Furthermore the effectiveness of a given safety stock is significantly reduced, indeed even with a very high target the maximum achievable service level can be quite limited. The paper is based on an actual spare parts inventory control system used in a domestic appliance company.

MMMS — A Microcomputer Based System for Maintenance Management

The growing awareness of the critical importance of proper maintenance both at national and sectoral levels has led to the development of the concept of maintenance management systems. This paper outlines the main features of a microcomputer based maintenance management system, called MMMS. The system was developed using dBASE lII and completely menu driven. The main features of the system include the generation of preventive maintenance schedules and work orders for both preventive and breakdown activities, maintenance of all preventive and breakdown activities and generation of practical management reports. It also tracks labor time, cost, and efficiency of various maintenance operations. The system has integrated both the personnel and the spare parts inventory systems with the maintenance system.

Determination of reorder points for spare parts in a two-echelon inventory system: The case of non identical maintenance facilities

This paper deals with the determination of reorder points in a two-echelon spare parts inventory system. The system consists of a central warehouse that supplies several maintenance facilities. Each maintenance facility faces random demand. Inventory carrying cost is the same in both echelons, but the consequences of stockout vary among the maintenance facilities. An inventory management policy is proposed that determines the reorder point for each facility, so that predetermined requirements concerning relationships between the resulting service levels are met. The inventory system described in this paper is typical to class A (in a Pareto or ABC analysis) of spare parts inventories, i.e., military. Limited quantities of spare parts are stocked in an inventory system serving several maintenance facilities. The same type of equipment is maintained by each facility. However, due to readiness requirements of the organizational units served by each facility, the required service levels of the centers are not all the same.

Order-statistic calculation, costs, and service in an (s, Q) inventory system

A retailer or distributor of finished goods, or the manager of a spare-parts inventory system, must generally forecast the major portion of demand. A specific customer-service level p (fraction of replenishment intervals with no stockout) implies two challenges: achieve the service within a small interval plus or minus, and do so with a minimum-cost investment in inventory. The pth fractile of lead-time demand (LTD) is the reorder point (ROP) for this service measure, and is often approximated by that fractile of a normal distribution. With this procedure, it is easy to set safety stocks for an (s, Q) inventory system. However, Bookbinder and Lordahl [2] and others have identified cases where the normal approximation yields excessive costs and/or lower service than desired. This article employs an order-statistic approach. Using available LTD data, the ROP is simply estimated from one or two of the larger values in the sample. This approach is sufficiently automatic and intuitive for routine implementation in industry, yet is distribution free. The order-statistic method requires only a small amount of LTD data, and makes no assumptions on the form of the underlying LTD distribution, nor even its parameters μ and ρ. We compare the order-statistic approach and the normal approximation, first in terms of customer service and then using a model of expected annual cost. Based upon characteristics of the available LTD data, we suggest a procedure to aid a practitioner in choosine between the normal and order-statistic method. © 1994 John Wiley & Sons, Inc.

A microcomputer expert system for advising on stocks in spare parts inventory systems

This paper describes the development and application of a logistic expert system for advising on the stocks of spare parts in inventory systems. The expert system designed, called SPARTA, is efficient and simple microcomputer application software and uses a standard programming environment and PC Plus as AI tool. SPARTA is a rule-based expert system consisting of a knowledge base and an inference engine. It combines causal knowledge and surface knowledge which allows a condensed design of the knowledge base. SPARTA's domain of expertise is restricted to the items for which the exponential distribution of times between failures can be assumed. SPARTA's output includes: (1) the list of recommended stocks, (2) the effectiveness of investment in spares, and (3) suggestions concerning further investment in spare parts.

A new adaptive algorithm for determination of stocks in spare parts inventory systems

A new adaptive algorithm for determination of stocks in spare parts inventory systems

Optimal stocking policies for low usage items in multi‐echelon inventory systems

AbstractMulti‐echelon logistic systems are essential parts of the service support function of high technology firms. The combination of technological developments and competitive pressures has led to the development of services systems with a unique set of characteristics. These characteristics include (1) low demand probabilities: (2) high cost items; (3) complex echelon structures; (4) existence of pooling mechanisms among stocking locations at the same echelon level; (5) high priority for service, which is often expressed in terms of response time service levels for product groups of items: (6) scrapping of failed parts; and (7) recycling of issued stock due to diagnostic use. This article develops a comprehensive model of a stochastic, multi‐echelon inventory system that takes account of the above characteristics. Solutions to the constrained optimization problem are found using a branch and bound procedure. The results of applying this procedure to a spare parts inventory system for a computer manufacturer have led to a number of important policy conclusions.

Aspects of an inventory control study

A case study for the design of a spare parts inventory control system is described. The main emphasis is given to the problems of applying and tailoring forecasting and inventory control theory to suit the needs of a particular problem. In the main, well established methods were used and these are not described in detail. New developments arising in the course of the study have been described elsewhere.