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The purpose of this paper is to compare various features of modular repair inventory flow in large maintenance organizations such as the Indian army with those of basic multi‐echelon repair inventory model METRIC.

Two models are selected and validated with user trials for a period of six months. A few performance measures for multi‐echelon repair inventory systems (MERIS) have also been identified using questionnaires. These two models are compared with the base model using developed performance measures and finally the most preferred model is identified which may replace the existing model. Finally, some recommendations are made for future researchers working in the area of multi‐echelon repair inventory systems.

The action research (AR)‐based approach has been used to solve a problem which is interactive and aims at developing a holistic understanding. A crisp codification scheme has also been suggested for a multi‐echelon repair inventory environment.

The paper demonstrates identification of inadequacies in the existing model of certain organizations and develops a number of alternate models with the prime objective of reducing the total number of echelons, using an AR‐based approach.

A number of approaches have been suggested in the literature for maintenance performance measurement, including use of the balanced scorecard (BSC). However, its application towards assessing maintenance contribution to business objectives is limited. Currently, a framework integrating maintenance activities in a supply chain environment is lacking in the literature. The purpose of this paper is to develop a maintenance performance measurement framework using BSC for multi echelon repair inventory systems (MERIS) comprising of modular electronic equipment. The paper also suggests a large number of performance measures/indicators (PMs/PIs) pertaining to both maintenance and supply chain components including a few BSC implementation issues for such types of supply chains.

The paper analyses a base model of a large maintenance organization and after carrying out SWOT analysis, identifies strategic themes/objectives for performance measurement. Performance measures for various objectives are identified for MERIS and implementation strategy including cascading of BSC is suggested. The developed performance measurement model is also validated using an action research (AR) based approach.

A performance measurement system (PMS) for MERIS using BSC approach has been developed and an implementation strategy suggested. AR methodology is used for developing BSC for an organization using the selected performance measures. The importance of cause‐effect relationships between various performance objectives and measures is also established.

Quantification of each of the developed PMs/PIs and establishing an effective information system for MERIS are the limitations of the present work and may be taken up for more research.

The paper will be useful for practitioners in the field of MERIS of electronic repairables wherein relevant PMs/PIs can be selected for implementation as per the requirement of the application.

The paper is of value by being original, as no work towards performance measurement of MERIS using BSC concept (as applicable for non‐profit organizations like military, government, NGOs etc) is reported in literature so far. The paper is relevant in this context and its contribution lies in the area of performance measurement.

The purpose of this paper is to describe the development of a balanced scorecard (BSC) for flight line maintenance (MX) activities in the US Air Force.

The BSC development process consists of three stages: groundwork, design beginning with structuring of organizational strategic elements through performance measure identification and construction of the BSC framework, and finalization for continuous improvement.

Based on logistics expert responses the authors validated a case BSC for flight line MX activities within an aircraft maintenance unit. Validation was done with respect to perspective measures including mission, influencing factors, management, and information enhancement.

BSC development through identification of mission critical performance measures should improve performance of aircraft scheduling and achievement of mission objectives. Guidelines were used to develop a case validated by Air Force logistics personnel.

The weapon system of The Navy is the small quantity producing system on multiple kinds. It is consisted of various equipment and the subordinate parts of those which can repair the damaged part. The operating procedure concerning warship's repair parts managed under these systems is as follows. Firstly, if demand of repair parts occurs from warship which is the operating unit of weapon, then the Fleet(the repair & supply support battalion) is in charge of dealing with these requests. If certain request from warship is beyond the battalion's capability, it is delivered directly to the Logistic Command. In short, the repair and supply support system of repair parts can be described as the multi-level support system. The various theoretical researches on inventory management of Navy's repair parts and simulation study that reflects reality in detail have been carried out simultaneously. However, the majority of existing research has been conducted on aircraft and tank's repairable items, in that, the studies is woefully deficient in the area concerning Navy's inventory management. For that reason, this paper firstly constructs the model of consumable items that is frequently damaged reflecting characteristics of navy's repair parts inventory management using ARENA simulation. After that, this paper is trying to propose methodology to analyze optimal inventory level of each supply unit through OptQuest, the optimization program of ARENA simulation.

Conventionally, fleet maintenance decisions are made based on the level of repair (LOR) analysis. A general assumption made during LOR analysis is the consideration of the lifetime distribution with constant failure rate (CFR). However, industries do use preventive maintenance (PM) to extend the life of such components, which in turn may affect the LOR decisions such as repair/move/discard. The CFR assumption does not allow the consideration of effect of PM in LOR analysis. The purpose of this paper is to develop a more practical LOR analysis approach, considering the time-dependent failure rate (TDFR) of components and the effect of PM.

In the proposed methodology, first, a detailed life cycle model considering the effect of various parameters related to LOR and PM is developed. A simulation-based genetic algorithm approach is then used to obtain an integrated solution for LOR and PM schedule decisions. The model is also evaluated for the various cases of quality of maintenance measured in terms of degree of restoration.

The results, from the illustrative example for a multi-indenture and multi-echelon fleet maintenance network, show that the proposed integrated strategy leads to better LCC performance compare to the conventional approach. Additionally, it is identified that the degree of restoration also affects the PM schedule as well as LOR decisions of the fleet system. Therefore, consideration of TDFR is important to truly optimize the LOR decisions. The proposed approach can be applied to fleet of any equipment.

The approach is illustrated using a hypothetical example of an industrial system. A more complex system structure in terms of number of machines, types of machines (identical vs non-identical), number of echelons, possible repair actions at various echelons, etc. may be present for a particular industrial case. However, the approach presented is generic and can be extended to any system. Moreover, the aim of the paper is to highlight the importance of the considering PM and quality of maintenance in LOR decision making.

To the best of the authors’ knowledge, this is the first work which considers the effect of PM and quality of maintenance on LOR analysis. Consideration of TDFR and imperfect maintenance while optimizing LOR decisions is a complex problem. Thus, the work is of high significance from the research point of view. Also, most of the real life fleet systems use PM to extend the life of the equipment. Thus, present paper is a more practical approach for LOR analysis of such systems.

This paper discusses integrated logistics in a two‐level repair‐inventory system of a transport corporation where there is one central depot and twenty subordinate depots which cater to the needs of the population in a metropolitan city in India. An expensive, recoverable spare (engine) is considered with (S — 1, S) inventory policy. It is reported that the present location of the central facility is not optimal. The advantages possible by optimally locating this central facility are highlighted with results. The impact of increasing the maintenance effectiveness on the optimum spare stock level and the total system cost are discussed.

Notes, in recent years, an increase of interest in the field of service parts inventory ‐ particularly in the computer industry. Explains that the computer industry is a highly competitive industry; products have to be repaired as quickly as possible, since slow repair can lead to loss of future business to competitors with better service reputations. Maintains that a good reputation is therefore closely linked to the availability of spare parts on the market. Using a real‐life case study, elaborates on the management and control of service‐parts inventory and gives a brief overview of the contemporary literature on the subject. Presents the solution approach adopted and the results of the study, which indicate that significant savings can be realized through good management of service‐parts inventory.

The article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of parts used to repair equipment acquired over many decades. Demand is intermittent, procurement lead times are long, and the total inventory investment is significant.

Demand exists for repair kits, and a repair cannot start until all required parts are available. The cost model includes holding cost to carry the part being modeled as well as shortage cost that consists of the holding cost to carry all other repair kit parts for the duration of the part’s lead time. The model combines deterministic and stochastic approaches by assuming a fixed ordering cycle with Poisson demand.

The results show that optimal service levels vary as a function of repair demand rate, part lead time, and cost of the part as a percentage of the total part cost for the repair kit. Optimal service levels are higher for inexpensive parts and lower for expensive parts, although the precise levels are impacted by repair demand and part lead time.

The proposed model can impact society by improving the operational performance and efficiency of public transit systems, by ensuring that home repair technicians will be prepared for repair tasks, and by reducing the environmental impact of electronic waste consistent with the right-to-repair movement.

The optimization model is unique because (1) it quantifies shortage cost as the cost of unnecessary holding other parts in the repair kit during the shortage time, and (2) it determines a unique service level for each part in a repair kit bases on its lead time, its unit cost, and the total cost of all parts in the repair kit. Results will be counter-intuitive for many inventory managers who would assume that more critical parts should have higher service levels.

This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system.

A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it.

The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods.

In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.