Joint Optimization of Preventive Maintenance and Spare Parts Inventory with Appointment Policy

Under the background of the wide application of condition-based maintenance (CBM) in maintenance practice, the joint optimization of maintenance and spare parts inventory is becoming a hot research to take full advantage of CBM and reduce the operational cost. In order to avoid both the high inventory level and the shortage of spare parts, an appointment policy of spare parts is first proposed based on the prediction of remaining useful lifetime, and then a corresponding joint optimization model of preventive maintenance and spare parts inventory is established. Due to the complexity of the model, the combination method of genetic algorithm and Monte Carlo is presented to get the optimal maximum inventory level, safety inventory level, potential failure threshold, and appointment threshold to minimize the cost rate. Finally, the proposed model is studied through a case study and compared with both the separate optimization and the joint optimization without appointment policy, and the results show that the proposed model is more effective. In addition, the sensitivity analysis shows that the proposed model is consistent with the actual situation of maintenance practices and inventory management

Optimal maintenance and replacement decisions under technological change with consideration of spare parts inventories

International audienceClassical spare parts inventory models assume that the same vintage of technology will be utilized throughout the planning horizon. However, replacement often occurs in the form of a new technology that renders existing spare parts inventories obsolete. This paper aims to study the impact of spare parts inventory on maintenance and replacement decisions under technological change via a Markov decision process formulation. The replacement decision is complex in that one must decide with which technology available on the market to replace the current asset. Under technological change, the do nothing and repair options have significantly more value as they allow the appearance of even better technologies in the future

Prognostics-Based Two-Operator Competition for Maintenance and Service Part Logistics

Prognostics and timely maintenance of components are critical to the continuing operation of a system. By implementing prognostics, it is possible for the operator to maintain the system in the right place at the right time. However, the complexity in the real world makes near-zero downtime difficult to achieve partly because of a possible shortage of required service parts. This is realistic and quite important in maintenance practice. To coordinate with a prognostics-based maintenance schedule, the operator must decide when to order service parts and how to compete with other operators who also need the same parts. This research addresses a joint decision-making approach that assists two operators in making proactive maintenance decisions and strategically competing for a service part that both operators rely on for their individual operations. To this end, a maintenance policy involving competition in service part procurement is developed based on the Stackelberg game-theoretic model. Variations of the policy are formulated for three different scenarios and solved via either backward induction or genetic algorithm methods. Unlike the first two scenarios, the possibility for either of the operators being the leader in such competitions is considered in the third scenario. A numerical study on wind turbine operation is provided to demonstrate the use of the joint decision-making approach in maintenance and service part logistics

An Advanced Heuristic for Multiple-Option Spare Parts Procurement after End-of-Production

After-sales service is a major profit generator for more and more OEMs in industries with durable products. Successful engagement in after-sales service improves customer loyalty and allows for competitive differentiation through superior service like an extended service period after end of production during which customers are guaranteed to be provided with service parts. In order to fulfill the service guarantee in these cases, an effective and efficient spare parts management has to be implemented, which is challenging due to the high uncertainty concerning spare parts demand over such a long time horizon. The traditional way of spare parts acquisition for the service phase is to set up a huge final lot at the end of regular production of the parent product which is sufficient to fulfill demand up to the end of the service time. This strategy results in extremely high inventory levels over a long period and generates major holding costs and a high level of obsolescence risk. With increasing service time more flexible options for spare parts procurement after end of production gain more and more importance. In our paper we focus on the two most relevant ones, namely extra production and remanufacturing. Managing all three options leads to a complicated stochastic dynamic decision problem. For that problem type, however, a quite simple combined decision rule with order-up-to levels for extra production and remanufacturing turns out to be very effective. We propose a heuristic procedure for parameter determination which accounts for the main stochastic and dynamic interactions between the different order-up-to levels, but still consists of quite simple calculations so that it can be applied to problem instances of arbitrary size. In a numerical study we show that this heuristic performs extremely well under a wide range of conditions so that it can be strongly recommended as a decision support tool for the multi-option spare parts procurement problem.Spare Parts, Inventory Management, Reverse Logistics, Final Order

Test, Control and Monitor System maintenance plan

The maintenance requirements for Test, Control, and Monitor System (TCMS) and the method for satisfying these requirements prior to First Need Date (FND) of the last TCMS set are described. The method for satisfying maintenance requirements following FND of the last TCMS set will be addressed by a revision to this plan. This maintenance plan serves as the basic planning document for maintenance of this equipment by the NASA Payloads Directorate (CM) and the Payload Ground Operations Contractor (PGOC) at KSC. The terms TCMS Operations and Maintenance (O&M), Payloads Logistics, TCMS Sustaining Engineering, Payload Communications, and Integrated Network Services refer to the appropriate NASA and PGOC organization. For the duration of their contract, the Core Electronic Contractor (CEC) will provide a Set Support Team (SST). One of the primary purposes of this team is to help NASA and PGOC operate and maintain TCMS. It is assumed that SST is an integral part of TCMS O&M. The purpose of this plan is to describe the maintenance concept for TCMS hardware and system software in order to facilitate activation, transition planning, and continuing operation. When software maintenance is mentioned in this plan, it refers to maintenance of TCMS system software

Development of Availability and Sustainability Spares Optimization Models for Aircraft Reparables

The Republic of Singapore Air Force (RSAF) conducts Logistics Support Analysis (LSA) studies in various engineering and logistics efforts on the myriad of weapon systems. In these studies, inventory spares provisioning, availability and sustainability analyses are key focus areas to ensure asset sustenance. In particular, OPUS10, a commercial-off-the-shelf software, is extensively used to conduct reparable spares optimization in acquisition programs. However, it is limited in its ability to conduct availability and sustainability analyses of time-varying operational demands, crucial in Operations & Support (O&S) and contingency planning. As the RSAF seeks force structure expansion to include more sophisticated weapon systems, the operating environment will become more complex. Agile and responsive logistics solutions are needed to ensure the RSAF engineering community consistently pushes for deepening competencies, particularly in LSA capabilities. This research is aimed at the development of a model solution that combines optimization and sustainability capabilities to meet the dynamic requirements in O&S and contingency planning. In particular, a unique dynamic operational profile conversion model was developed to realize these capabilities. It is envisaged that the research would afford the ease of use, versatility, speed and accuracy required in LSA studies, to provide the necessary edge in inventory reparable spares modeling

OR in Spare Parts Management:A Review

Abstract Spare parts are held to reduce the consequences of equipment downtime, playing an important role in achieving the desired equipment availability at a minimum economic cost. In this paper, a framework for OR in spare parts management is presented, based on the product lifecycle process and including the objectives, main tasks, and OR disciplines for supporting spare parts management. Based on the framework, a systematic literature review of OR in spare parts management is undertaken, and then a comprehensive investigation of each OR discipline's contribution is given. The gap between theory and practice of spare parts management is investigated from the perspective of software integration, maintenance management information systems and adoption of new OR methods in software. Finally, as the result of this review, an extended version of the framework is proposed and a set of future research directions is discussed

No. 02: The Urban Food System of Maputo, Mozambique

The city of Maputo, with a population of around 1.3 million, has been at the forefront of urbanization in Mozambique. While the Southern African country has posted impressive macro-economic growth rates in the last two decades, there has been only limited formal sector employment generation. Most of its working population is absorbed in informal employment and self-employment. The informal food economy is easily the most important source of food in Maputo. Almost all households regularly obtain food from informal sellers; over 90% at least once a week and many on a daily basis. For many households, daily purchasing is necessitated by unpredictable daily income and a lack of accumulated funds. Such purchasing raises the unit cost per item and leads to higher household expenditure on food. The informal food economy is not confined to the markets, and is particularly visible and extensive on the streets and in the bairros of Maputo. There are many thousands of street vendors selling a range of fresh and processed food, often from the same stall. Most of the fresh fruit and vegetables, processed food and junk food are imported from South Africa. Food insecurity is highly prevalent throughout Mozambique. This audit of the city of Maputo highlights that there are still major information gaps in our understanding of the urban food system. As its work progresses, the Hungry Cities Partnership aims to fill many of these gaps