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Optimization and availability evaluation of spare parts project of multi-indenture system under incomplete cannibalization
Abstract
In order to determine the initial spare parts project and exactly evaluate the equipment availability for improving its support effectiveness, the optimization method for the initial spare parts project is given according to the METRIC theory. For the complex equipment with multi-indenture structure, the system availability evaluation model is established under the incomplete cannibalization policy. The analysis method and flow of the equipment support effectiveness under the cannibalization policy are studied. The equipment availability is calculated under the different cannibalization policies by an example. The VMETRIC software simulation results show that the error between the model and the simulation is less 5%, and the research can provide support for military equipment managers to design reasonable support projects.
... Figure 1 shows an example of cannibalization between two similar vehicles with the same component architecture, A, B, and C. Therefore, to benefit from a cannibalization policy, the fleet system should comprise compatible or identical components [12], with, for example, a homogeneous fleet system, meaning it has the same component architecture as that system [13]. In summary, cannibalization policies can increase the availability rate of fleet systems [14]. However, it is necessary to identify the requirements for using cannibalization policies in transport systems. ...
Fleet systems are considered complex due to the interaction between their units and components. Maintenance management systems face various challenges to achieve acceptable availability and reliability rates at a reasonable cost. A critical task for making maintenance decisions is understanding the system requirements to select maintenance policies appropriate for the actual and future system state. When there is a replacement shortage in a fleet system, and it is impossible to supply new spare parts quickly, cannibalization policies can mitigate this scarcity via the interchange of components. However, this procedure presents the maintenance manager with different evaluation effects, such as increased maintenance hours, decreased system reliability rate, and unavailability in some units. Finding an equilibrium between the benefits and risks has caught the attention of researchers. This work gathers diverse proposals for applying cannibalization policies and the effects that arise from using them. Models, methods, tools, and identified gaps in understanding what parameters of the components and environments of the fleet systems favor cannibalization are discussed.
The dynamic characteristics of spare inventory under nonstationary demand were researched. The Markova state transition equation of spare consume distribution function was formulated and the function derivations of expectation and variance of consumed spares with respect to time were obtained. On the base of above mentioned analysis result, the methods of calculating the expectation, variance and distribution function of consumed spares were given at arbitrary time point. Curves of the expected consumed spares (E(t)) and the expected back orders (EBO(t)) vs. time were plotted by numerical integral, influences of the demand rate and the turnaround time rate of the spares on E(t), EBO(t) were analyzed.
A type of mission oriented cannibalization policy problem is studied this paper, the problem is modeled as a multi-dimensional knapsack problem, and a solution method what is based on genetic algorithm (GA) for the problem is presented. A two stages GA with better performance is designed and comprehensive analysis and design what including the optimal-frontier restriction algorithm, encoding, crossover, mutation, evaluation function, selection policy and simulated anneal based local search algorithm is performed. At last, the practicability of the solution method is verified by an example and analyzes the performance of the GA by computational experiment respectively.
Cannibalization policy is an effective approach to improve support effectiveness. Under the current support condition, it can make equipment availability reach the upper limit. This paper establishes respectively availability models of a non-cannibalization system, a cannibalization system and a partial cannibalization system under the mode of multi-echelon maintenance supply in accordance with the characteristics of cannibalization combined with multi-echelon technique for recoverable item control (METRIC) theory. The analysis flow and method of support effectiveness are studied. In a given example, The initial spare parts inventory project is obtained under which the equipment availability is analyzed with different cannibalization policies. VMETRIC simulation is used to test the results, and the verification shows that there is high consistency between the two results, which proves the validity of the model.
Management of three-echelon maintenance and supply is a common support mode, in which the spare parts inventory project is one of the critical factors for system availability. Focus on the actual problem of the equipment support engineering, the system spare parts are divided into two levels, and based on the METRIC theory, the three-echelon support evaluation model for system spare parts is established. The three-echelon system support degree is used as the optimization target while the cost is taken as the restriction, and the margin analysis method is applied to inventory project optimization. In a given example, the optimal inventory project and the distribution rule for spare parts is got, and the influencing factors for spare parts inventory is analyzed. The optimization result is consistent with the basic principle under the three-echelon support pattern, which can supply decision assistance for equipment support personal to design a reasonable project.
This paper considers a multi-part spares inventory model for a maintenance system composed of a spares-stocking centre and a repair centre. In the maintenance system, multi-part spares are jointly needed to repair faulty end items determined by ambiguous fault isolation done by the built-in-test-equipment (BITE). If any operating end item breaks down, then all associated parts should be replaced either iteratively (one at a time) or altogether. In the case of iterative replacement, failed parts are detected in the field after fixing the broken end item. However, in the case of group (altogether) replacement, all removed parts are sent to the repair centre where the failed part is detected and fixed. The repaired or non-failed parts are then restocked at the spares-stocking centre. For the system, this paper is to derive the exact expressions for the distribution function and the expected numbers of the backlogged end items under the cannibalization policy. These expressions are then used in the optimization of the associated spares' inventory level. Illustrative numerical examples are also presented.
Maintenance systems serving fleets of aircraft or vehicles are quite complex, often including spares, repair, cannibalization, manpower constraints and other factors. Analytic models of such systems in the literature, however, rarely include manpower constraints and usually incorporate only complete cannibalization if any at all. This paper presents a continuous Markov process model suitable for evaluating the performance of a maintenance system with spares, repair, cannibalization and manpower constraints. Several cannibalization and repair options are included, and the model's usefulness is demonstrated by a sequence of experiments identifying desirable cannibalization policies under various failure, repair and cannibalization rates.
Organizations that utilize fleets of expensive repairable equipment are faced with numerous challenges related to the specification of maintenance policies and the allocation of maintenance resources. The associated maintenance decisions can have a drastic impact on fleet performance. Due to the significant acquisition costs associated with the components that comprise the units of equipment in the fleet, cannibalization is often used in the absence of available spare parts to enable fleet maintenance managers to satisfy fleet performance constraints such as readiness requirements. This research is focused on the development and analysis of a closed-network, discrete-event simulation model that is used to assess the impacts of cannibalization, small spare parts inventories and maintenance-induced damage on a fleet of systems. Using numerical examples, we demonstrate the comparison between cannibalization and the investment in limited spare parts inventories. We evaluate fleet performance using average readiness and total maintenance cost. Specifically, we demonstrate that investments in spare parts inventories can reduce the need for and value of cannibalization. However, our results also support the use of cannibalization as a low-cost alternative to investing in expensive spare parts. We also explore the impact of damage induced by maintenance on fleet performance. Specifically, we demonstrate that maintenance-induced damage can reduce the benefit of cannibalization while drastically increasing maintenance expenditures. Copyright © 2006 John Wiley & Sons, Ltd.
This article presents the results of comparing the performance of several cannibalization policies using a simulation model of a maintenance system with spares, repair, and resource constraints. Although the presence of cannibalization has been incorporated into a number of maintenance system models reported in the literature, the questions of whether cannibalization should be done and what factors affect canibalization have received little attention. Policies tested include both no cannibalization and unlimited cannibalization as well as other based on the number of maintenance personnel available, the short-term machine failure rate at the time of cannibalization, and the relationship between the mean cannibalization and repair rates. The best policies found are those that allow cannibalization only when it can be done quickly relative to repair or when it can be done without delaying part repair actions. The policy of complete cannibalization (always cannibalize when it is possible) is found to perform poorly except when either average maintenance personnel utilization is very low or when mean cannibalization times are very short relative to mean repair times. The latter result casts doubts on the appropriateness of the assumption of complete cannibalization in many models in the literature.
This paper presents a mathematical model to predict the number of units of equipment available in the future. The components of this equipment are subject to Poisson failures and replacements are obtained by cannibalization. A numerical example is presented, and some difficulties encountered in the practical application of this model are discussed.
This paper explores the applicability of sophisticated models and techniques for spare parts inventory management within a highly technology-driven environment, viz. the Royal Netherlands Navy. In particular, we discuss the structure of the so-called VARI-METRIC models, a set of tools that has been designed for decision support in spare parts management, initially in a military organization. These tools aim at a high availability of complete technical systems, as opposed to more classical inventory management approaches, that are primarily directed towards a high availability of individual items. Unfortunately, the VARI-METRIC models suffer from a series of limiting assumptions that are not satisfied in most technology-based large organizations. We identify these shortcomings and suggest a research agenda to deal with these issues. Important extensions include the study of capacitated systems, and the study of hybrid product structures, consisting of both repairable and consumable parts. When consumption and condemnation occur (i.e. not every broken part can be repaired), the operational availability of systems during their exploitation period becomes a function of the allocated resupply budgets. This highly important field, relating issues such as maintenance policies, spare parts repair and resupply, to concepts of life cycle management, seems unexplored so far.
In this paper a repairable item system for the maintenance support of a fleet of aircraft is introduced. The purpose of the system, a complex conjunction of repair departments and stock locations, is the repair and supply of serviceable engines to the maintenance process of the aircraft. The performance of the repairable item system is measured by a service level. If the realized service level corresponds with the required service level, conditions are created among which the maintenance process can be carried out efficiently. Thus the setting of service levels is a means for the control of the repairable item system. To meet the required service level target for the entire repairable item system, it is important that the performance of the individual repair departments and the stock locations of the repairable item system are tuned. In this coordination process, service level targets must also be set for the repair departments and stock locations. In this paper it is show that the deduction of these service level targets can be supported with the help of well-known models such as METRIC and MOD-METRIC. In a numerical analysis it is shown that the targets for the repair departments can be substantially lower than the targets for the downstream stock locations of the repairable item system.
Retailers of products with limited shelf life are faced with the dilemma of stocking the right mix of standard product and its customized stock keeping units, in each product category. In this paper we model the retailer multi-item inventory problem with demand cannibalization and substitution. The model focuses on the twin problems of optimal portfolio selection as well as optimal stocking under retailing context. Owing to analytical complexity in determining optimal solution, we develop heuristics for solving the problem. Using set of numerical examples we compare the heuristic solutions against the optimal solutions. In addition, we also attempt to understand the impact of important parameters on retailer profits through a series of sensitivity analysis.