Optimal Spare Parts Research Articles

Joint optimization of maintenance, buffer, and spare parts for a production system

Maintenance research catches growing attention for its increasing importance in reality. Spare parts and intermediate buffer are two important factors related to maintenance activity, and both of them may greatly influence the system cost. Although some researchers have considered maintenance and buffer inventory, or maintenance and spare parts inventory together, the joint optimization of the three has not been considered before. This paper is focused on the interaction between maintenance, buffer inventory, and spare parts inventory, to achieve the minimization of the long-term expected cost rate for a production system. The investigated production system of the paper consists of two serial machines, an intermediate buffer, and a spare part inventory. The practical example for this type of system can be an automated work center or an automobile general assembly. The cost model that represents the long-term expected cost rate is developed by mathematical analysis. Four control variables corresponding to decisions made on maintenance, buffer, and spare parts are included. Then by using the genetic algorithm method, the cost model is optimized. The proposed method is applied to different simulation cases to show its efficiency and necessity. Additionally, the related optimization results indicate that the joint optimization can effectively alleviate the influence caused by the change of buffer accumulation speed.

Evaluating the Impact of Spare Parts Pooling Strategy on the Maintenance of Unreliable Repairable Systems

In today's industries, optimal spare parts provisioning plays a critical role towards sustaining the asset's operational capabilities. In this context, spare parts pooling is increasingly mentioned as a plausible approach for optimizing spare parts management, more so for repairable systems. In this sense, several frameworks are proposed in literature, though largely analytical, thus limiting their capabilities with respect to modeling complex repairable systems. Moreover, the nature of interactions often account for aspects such as system reliability, imperfect component reconditioning, repair capacity and spare parts inventory that is multi-echelon in nature. To realistically model such complexities, simulation approaches are often explored. This paper presents a discrete event simulation modeling study. The simulation model mimics the impact of several aspects on unreliable repairable systems. The aspects include the repair capacity, component reconditioning process, and multi-echelon spare part provisioning strategy. Moreover, the influence of spare parts quality aspects is evaluated and demonstrated in the case study of critical system for a thermal power plant.

Joint Optimization of Condition-based Preventive Maintenance and Spare Parts Provisioning Policy for Equipment Maintenance

Joint Optimization of Condition-based Preventive Maintenance and Spare Parts Provisioning Policy for Equipment Maintenance

Joint optimization of spare parts ordering and maintenance policies for multiple identical items subject to silent failures

In this paper the joint maintenance and spare parts ordering problem for more than one identical operating items is studied. The operating items may suffer two types of silent failures: a minor failure, which results in item malfunctioning, and a major failure, which renders the item completely out-of-function. Inspections are periodically held to detect any failures and the inspected items are preventively maintained, repaired or replaced according to their condition. Two ordering policies are investigated to supply the necessary spare parts: a periodic review and a continuous review policy. The expected total maintenance and inventory cost per time unit is derived and the proposed models are optimized for real case data. In addition, the sensitivity of the proposed models is studied through numerical examples and the effect of some key problem characteristics on the optimal decisions is discussed.

Information System Construction of Spare Parts Supply Based on Supply Chain

Equipment spare parts in equipment maintenance play an important role in the management, maintenance and repair of damaged equipment. Information system of spare parts supply is constructed based on supply chain. The generic configuration of supply chain is introduced, based on which the information system of spare parts supply is established. The proposed information system includes three levels. The lowest level is spare parts supply entity level which mainly includes all sorts of entities involved in spare parts supply activities. The middle level is spare parts data collecting level which including information resources integrating platform and spare parts information data collecting platform. The highest level is spare parts data releasing level which includes common information platform and management information platform. The optimization of spare parts supply system architecture is also proposed through analyzing the business process of spare parts. The proposed information system architecture provides an effective method and design thought for spare parts supply chain design and optimization.

Spare Parts Support Optimization Algorithm Based on Support Degree

we consider the actual situation of wartime equipment support and the different life of the old and new spare parts, in-depth analyze the impact of spare parts scheduling on the support degree, and establishe support degree model of the three-levels spare parts scheduling. According to the characteristics of the model, the introduction of the classic scheduling algorithm for optimization of spare parts, can effectively improve the efficiency of support,the last example shows that the effectiveness of the method. DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3040

A dynamic predictive maintenance model considering spare parts inventory based on hidden semi-Markov model

The maintenance strategies optimization can play a key role in the industrial systems, in particular to reduce the related risks and the maintenance costs, improve the availability, and the reliability. Spare part demands are usually generated by the need of maintenance. It is often dependent on the maintenance strategies, and a better practice is to deal with these problems simultaneously. This article presents a stochastic dynamic programming maintenance model considering multi-failure states and spare part inventory. First, a probabilistic maintenance model called hidden semi-Markov model with aging factor is used to classify the multi-failure states and obtain transition probabilities among multi-failure states. Then, spare parts inventory cost is integrated into the maintenance model for different failure states. Finally, a double-layer dynamic programming maintenance model is proposed to obtain the optimal spare parts inventory and the optimal maintenance strategy through which the minimum total cost can be achieved. A case study is used to demonstrate the implementation and potential applications of the proposed methods.

Spare Parts Production Planning Model Based on Fuzzy Programming

In the field of civil aviation, MRO market has a strong seasonal characteristic. Combined with research on continuous airworthiness of the aircraft, the spare parts order procedure and flight planning process, and analysis on fuzzy demand and fuzzy production capacity, the model of spare parts order with fuzzy reliability constraints is established. Under the background of actual civil aviation enterprises, spare parts quantitative order model and algorithm in spare parts planning decision system in non-deterministic environment are put forward. It applies the theories and methods of fuzzy mathematics and probability and statistics, building the target programming model for reconfigurable spare parts, to formulate optimal reconfigurable spare parts production plan. Overall steps to solve the model are proposed, which make decision process in fuzzy environment more flexible, and reduce the number of emergency orders.

Spare Parts Support Model Optimization Algorithm

by deeply analyzing the impact factor of the support degree, the calculation formula of the support degree be extended to make the formula more reasonable. Taking into account the life of the old and new spare parts and the impact of scheduling for spare parts support, the spare parts scheduling support model has been established. According to the characteristics of the model, the introduction of the classic scheduling algorithm for optimization of spare parts, can effectively improve the efficiency of support.

A Continuous-Time Examination of End-of-Life Parts Acquisition With Limited Customer Information

Manufacturers often encounter difficulties in supplying an adequate number of spare parts for a product that is in its post-production phase. Current solution methods for optimal spare part order amounts use assumptions that require knowledge of the number of products in operation at any time t. In the business situation presented here, the manufacturer only has knowledge of the part and product failure rates and a probability distribution on the number of products still in operation; unless the manufacturer and customer have a close working relationship, it is likely that this information is all that the manufacturer will have available in a typical business environment. We model time-discounted revenues and costs as a function of the spare parts order amount. We consider two different versions of the problem—incremental replenishment and no replenishment—that operate by determining the rate of change of the total profit with respect to the order amount q.

Performance, reliability and failure analysis of wind farm in a developing Country

In this paper, an analysis of the performance, failure and reliability, as well as a spare parts analysis have been conducted for a wind farm, which has 15 wind turbine generators (WTGs), each of 225 kW capacity. This wind farm is located at Muppandal, Tamil Nadu, South India. The average value of performance parameters such as technical availability, real availability and capacity factor for the wind farm were 94%, 82.88% and 24.9% respectively during the years 2000–2004. This paper also deals with Pareto analysis to find out the reduction in problems, when one problem is tackled partly and completely. The Weibull technique was also used for the reliability analysis. The reliability factor in the initial period after one year seems to be good as the wind farm has a lower failure rate of 0.000019. As a supplemental activity, spare parts optimization was also carried out for a few vital components of this wind farm and the results are presented. The failure and its financial implications are also analyzed in this paper.

REDUCING COSTS OF SPARE PARTS SUPPLY SYSTEMS VIA STATIC PRIORITIES

We study static repair priorities in a system consisting of one repair shop and one stockpoint, where spare parts of multiple, critical repairables are kept on stock to serve an installed base of technical systems. Demands for ready-for-use parts occur according to Poisson processes, and are accompanied by returns of failed parts. The demands are met from stock if possible, and otherwise they are backordered and fulfilled as soon as a ready-for-use part becomes available. Returned failed parts are immediately sent into repair. The repairables are assigned to static priority classes. The repair shop is modeled as a single-server queue, where the failed parts are served according to these priority classes. We show that under a given assignment of repairables to priority classes, optimal spare parts stock levels follow from Newsvendor equations. Next, we develop fast and effective heuristics for the assignment of repairables to priority classes. Subsequently, we compare the performance of the system under these static priorities to the case with a First-Come First-Served (FCFS) service discipline. We show that in many cases static priorities reduce total inventory holding and backordering costs by more than 40%. Finally, we analyse the effect of the number of priority classes. We show that 2 priority classes suffice to obtain 90% of the maximal savings via static priorities.

Spare parts optimization process and results

PurposeThe paper has two main aims: to focus on how the spare parts optimization process was conducted in the Norwegian Defence procurement projects that had used the system approach based on OPUS10, and whether coordination issues affected the process and results; and to analyse empirical data in order to evaluate whether the theoretical claim of the system approach used through OPUS10, being better than other methods in terms of availability and spare parts investment cost holds up in reality.Design/methodology/approachBoth qualitative and quantitative methods were used in order to answer the different questions of the study.FindingsVery few Norwegian Defence projects have used the system approach through OPUS10. Empirical data however comply with the theoretical claims of potential large savings in spare parts investment cost and/or improvement in operational availability. Several organizational factors can explain the lack of use of OPUS10. The most important being lack of resources, lack of a centralized concept and a somewhat low‐project leader attitude towards the approach.Research limitations/implicationsThe study of Norwegian Defence cases makes generalizations of findings not applicable. The research model could however easily be transferred and utilized in the study of other organizations' spare parts optimization processes.Practical implicationsThe Norwegian Defence should alter their concept for project governance and management in order to gain the full potential of the system approach used through OPUS10.Originality/valueFew research papers have evaluated the promising theoretical findings of system‐based optimization based on empirical operational data. Even fewer, if any, studies have used a combination of factors from organization theory, economic organization theory and operation management theory in order to explain findings based on predefined hypotheses. This research should have value for both practitioners and researchers within the field spare parts optimization in general and systems management in particular.

Spare Parts and Maintenance Optimization in a Mobile Telephone Company

Telecommunication companies depend on high availability of equipment to maintain service quality. In cellular communications electronic cards maintenance is basically reduced to exchanging parts as they fail. These parts are geographically dispersed in unmanned locations. Spares and maintenance policies are thus interrelated and tend to follow multiechelon configurations, following the architecture of the physical network. We describe the optimization of spare parts and maintenance policies performed by the Venezuelan mobile phone operator Movilnet. Both system issues (reduction of SKU, classification of items, network practices, and data integrity) and modeling issues, centered on the adaptation of the METRIC model to the simultaneous optimization of spare parts and personnel resources, are discussed. The systematic application of these resulted in important reductions in the purchasing of spare parts, without quality deterioration.

The problems of predicting failure and the need for optimization of spare parts on the basis of reliability and control of resources state park aircrafts flights

Розглянуто питання прогнозування відмов і оптимізація потреби в запчастинах на підставі контролю надійності та ресурсного стану парку повітряних суден авіакомпаній.

A discrete‐time order‐replacement model with time discounting and spare part provisioning

PurposeTo determine the optimal spare part order‐replacement policy for any high cost single unit complex system in a discrete‐time circumstance.Design/methodology/approachThe expected total discounted cost over an infinite planning horizon is taken as a criterion of optimality as it allows us to put emphasis on the present behavior of the system.FindingsThe problem under consideration is a two‐dimensional discrete optimization problem (regular ordering time and inventory time limit for the spare are decision variables) which is difficult to handle, in general. However, it is explored that the problem can be reduced to a simple one‐dimensional one and the optimal ordering time is to be determined under the two extreme situations: no replacement of the spare until the original unit fails and replacement of the spare as soon as it is delivered.Research limitations/implicationsFor modeling simplicity, deterministic lead time is considered for both regular and expedited orders. A more appropriate assumption would be to consider randomized lead time for both the orders.Practical implicationsThe research provides a useful order‐replacement strategy for a single‐unit system where the failure of the unit is better measured by the number of cycles completed before failure rather than the instant of failure.Originality/valueThe work done in this paper carries certain values as any continuous time model for the problem under consideration can be regarded as only an approximate model.

Optimizacija rezervnih delova za održavanje modularno građenih elektronskih uređaja

Optimizacija rezervnih delova za održavanje modularno građenih elektronskih uređaja

Optimization of spare parts in a multilevel maintenance system

This paper examines the techniques and models for allocation of an optimum number of spare parts and modules at different levels of maintenance of a hierachical structure, in order to maximize system availability and minimize the costs and delay supply downtime. Computer programmes have been developed for calculating the optimum spares allocation for two and three maintenance levels. The approach to calculate spare parts allocation has been generalized by introducing repairable-parts modules into the model. A numerical example illustrates the influence of the maintenance policy on the efficiency of the maintenance system.

The Effect of Plant Reliability Improvement in the Cost of Generating Electricity

The objective of this investigation is to study the economic benefits in operating a nuclear power plant, as a result of improving the availability of the secondary (steam) loop of the plant. A new method has been developed to obtain availability, frequency of failure, probability and frequency of operation, cycle time, and uptime for different capacity states of a parallel series system having components with failure and repair rates distributed exponentially in time. The method has been applied to different subsystems, systems, and the secondary loop of a plant as a whole. The effect of having spare parts for several components, as measured by savings in the generation of electricity, is also studied. The Kettelle algorithm was applied to determine optimal allocation of spare parts to achieve maximum availability or minimum cost of electricity, subject to a fixed spare parts budget. The savings per year for optimal spare parts allocation and different spare parts budgets were obtained. The results show that the utility will save its customers a large amount of money if spare parts are purchased, especially at the beginning of the plant operation, and are allocated judiciously.

Optimization of spare parts for hierarchicall decomposable systems

Complex technical systems are often hierarchically composed of exchangeable modules, which themselves may be composed of exchangeable submodules. The hierarchy of modules of such systems can be represented by trees. Defective systems are repaired in a supply depot system by exchanging the defective modules from a stock of spare parts. The exchanged defective modules are repaired for resupply. In this paper, a dynamic programming algorithm for optimizing the stocks of spare parts, under a budget constraint, is presented. The optimization criterion is the minimization of the backlog of entire systems at the supply depot system. An implementation of the algorithm is described and some illustrative examples are given.