Multi-Echelon Technique For Recoverable Item Control Research Articles

Research on Location Selection Strategy for Airlines Spare Parts Central Warehouse Based on METRIC.

With the increased demands of airlines, it is important to study the location selection strategy for spare parts central warehouse in order to improve the allocation capacity of spare parts maintenance resources and reduce the operating costs of airlines. Based on the M/M/s/∞/∞ multiservice desk model and Multi-Echelon Technique for Recoverable Item Control (METRIC) theory, this paper proposes a spare parts supply strategy based on the spare parts pool network and establishes a location selection model for spare parts central warehouse. The particle swarm optimization (PSO) algorithm is used to iteratively optimize the location for spare parts central warehouse and adjust the location area of the central warehouse combining transportation facilities and geographical environment factors. Finally, the paper compares the operating results for multiple airlines in pooling and off-pooling states and verifies the effectiveness of the spare parts supply model and the advantages of cost control for airlines.

Spare parts allocation of amphibious aircraft based on hybrid two-level repair

In this paper, a hybrid two-level inventory allocation method based on multi-echelon technique for recoverable item control (METRIC) was applied to the spare parts allocation of amphibious aircraft. Firstly, the principle of the spare parts inventory configuration model for amphibious aircraft based on hybrid two-level repair was expounded. The mathematical model was established with maintenance cost as objective function and availability and volume of spare parts as constraints. Secondly, marginal analysis was used to help allocate spare parts, the process of solving the mathematical model was discussed, and the calculation formulas of the quantities involved were briefly stated. Finally, with the line replaceable units of landing gear as the research object, the spare parts inventory allocation of an amphibious aircraft was solved according to the method proposed in this paper. This paper provides an approach to allocate spare parts of amphibious aircraft.

Dynamic Safety Assessment of Aircraft Mechanism using Extremum Framework with Fault Tree Analysis

In this paper, a hybrid two-level inventory allocation method based on multi-echelon technique for recoverable item control (METRIC) was applied to the spare parts allocation of amphibious aircraft. Firstly, the principle of the spare parts inventory configuration model of amphibious aircraft based on hybrid two-level repair was expounded. The mathematical model was established with maintenance cost as objective function and availability and volume of spare parts as constraints. Secondly, marginal analysis was used to help allocate spare parts, the process of solving the mathematical model was discussed, and the calculation formulas of the quantities involved were briefly stated. Finally, with the line replaceable units of landing gear as the research object, the spare parts inventory allocation of a amphibious aircraft was solved according to the method proposed in this paper. This paper provides an approach to allocate spare parts of amphibious aircraft.

Multi-echelon inventory allocation of multi-indenture spare parts considering maintenance ratio

The existing multi-indenture spare parts maintenance has a certain maintenance proportion, a multi-echelon inventory allocation method with maintenance ratio for multi-indenture spare parts was proposed. Multi-echelon inventory allocation model for multi-indenture spare parts was established, which integrates maintenance rate into METRIC (Multi-echelon technique for recoverable item control) model, and then the marginal analysis method was applied to solve this model. First, the theory of multi-echelon inventory allocation model with maintenance ratio for multi-indenture spare parts was elaborated, and the mathematical model was established with the spare parts inventory cost as the optimization objective, the fleet availability as the constraints. Then, the procedure of solving the model by using marginal analysis method is discussed. Finally, taking an aircraft multi-indenture LRU (Line repairable units) as the research object, multi-echelon inventory allocation was investigated by considering maintenance ratio. The feasibility and effectiveness of the developed method are verified by an example analysis.

A System-Approach for Recoverable Spare Parts Management Using the Discrete Weibull Distribution

Optimal spare parts management strategies allow sustaining a system’s availability, while ensuring timely and effective maintenance. Following a systemic perspective, this paper starts from the Multi-Echelon Technique for Recoverable Item Control (METRIC) to investigate the potential use of a Weibull distribution for modelling items’ demand in case of failure. Adapting the analytic formulation of METRIC through a Discrete Weibull distribution, this study originally proposes a METRIC-based model (DW-METRIC) to be used for modelling the stochastic demand in multi-item systems, in order to ensure process sustainability. The DW-METRIC has been tested in a case study related to an industrial plant constituted by 98 items in a passive redundancy configuration. Comparing the results via a simulation model, the outcomes of the study allow defining applicability criteria for the DW-METRIC, in those settings where the DW-METRIC offers more accurate estimations than the traditional METRIC.

Multi-Echelon Inventory Allocation of Civil Aircraft Spare Parts Considering Maintenance Ratio

A multi-echelon inventory allocation technique with maintenance ratio for civil aircraft spare parts was proposed in this paper. Multi-echelon inventory allocation model was established, which integrates maintenance rate into METRIC (Multi-echelon technique for recoverable item control) model, and then marginal analysis method was applied to solve this model and accomplish multi-echelon inventory allocation of spare parts. Firstly, the theory of multi-echelon inventory allocation model with maintenance ratio was elaborated, and the mathematical model was established with the fleet availability as the optimization objective, the cost and the safeguard probability as the constraints. Secondly, the procedure of solving multi-echelon inventory allocation model considering the influence of maintenance ratio is discussed based on the marginal analysis method. Thirdly, landing gear LRU (Line repairable units) of a typical civil aircraft were selected as the research object, multi-echelon inventory allocation was investigated by considering maintenance ratio. The analysis results show that the minimum safeguard cost and fleet availability are respectively 2759833 dollars and 0.9806, and the number of LRU of multi echelon inventory allocation are obtained under the condition of satisfying the constrained optimization. The feasibility and effectiveness of the developed method are verified by comparing the traditional analysis method. This paper provides guidance for the accurate allocation of multi echelon inventory optimization for maintenance resources on the premise of reasonable cost reduction.

System optimization-oriented spare parts dynamic configuration model for multi-echelon multi-indenture system

In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for recoverable item control (METRIC) theory. According to the method of systems analysis, the dynamic palm theorem is introduced to establish the prediction model of the spares demand rate, and its main influence factors are analyzed, based on which, the spares support effectiveness evaluation index system is studied, and the system optimization-oriented spares dynamic configuration method for multi-echelon multi-indenture system is proposed. Through the analysis of the optimization algorithm, the layered marginal algorithm is designed to improve the model calculation efficiency. In a given example, the multi-stage spares configuration project during its life cycle is gotten, the research result conforms to the actual status, and it can provide a new way for the spares dynamic optimization.

Spare parts management for irregular demand items

Inventory optimization of high-value spare parts may generate a significant reduction of cost to allow a better allocation of resources in maintenance management. Sherbrooke's METRIC (Multi Echelon Technique for Recoverable Item Control) is the most common method to define an overall optimization process adopting a system-approach. Its main assumption consists of adopting a Poisson distribution to describe the demand pattern of the items. However, many studies proved that in high-availability systems, high-cost spare parts often follow irregular demand patterns, with very frequent zero-demand values.For this purpose, we propose an innovative model for a single site, the ZIP-METRIC, to take advantage of a distribution yet widely adopted in the healthcare and biological sciences, i.e. the Zero-Inflated Poisson. A case study of 1745 items of a European airline fleet demonstrates the model effectiveness, confirming that the ZIP-METRIC outperforms the traditional Poisson-based approach.

The effect analysis of multi-echelon inventory models considering demand rate uncertainty and limited maintenance capacity

Multi-echelon technique for recoverable item control (METRIC) has been a basic model in spare part stocking problem for high value with relatively low demand items. As METRIC is improved to vari-METRIC, the accuracy of the model is significantly increased. However, METRIC-based analytical models require strict assumptions for calculating spare stock levels. Many researchers have dedicated to relax those assumptions. Most of those efforts become either computing heuristics or relatively complex models. In this study, we propose a relatively simple METRIC-based model for the optimal allocation of spare stocking problems considering uncertain demand rate and limited repair capacity at the same time. Our models can be applicable to minimise either the expected backorders (EBOs) under a certain budget restriction or spending over certain availability. The proposed model relaxes those two assumptions by applying queueing theory and conditional Poisson probability distribution on demand rate. A numerical study shows the precision improvement. The EBO variation of our proposed model is decreased more than 50% when comparing to that of vari-METRIC.

Improving the computational efficiency of metric-based spares algorithms

We propose a new heuristic algorithm to improve the computational efficiency of the general class of Multi-Echelon Technique for Recoverable Item Control (METRIC) problems. The objective of a METRIC-based decision problem is to systematically determine the location and quantity of spares that either maximizes the operational availability of a system subject to a budget constraint or minimizes its cost subject to an operational availability target. This type of sparing analysis has proven essential when analyzing the sustainment policies of large-scale, complex repairable systems such as those prevalent in the defense and aerospace industries. Additionally, the frequency of these sparing studies has recently increased as the adoption of performance-based logistics (PBL) has increased. PBL represents a class of business strategies that converts the recurring cost associated with maintenance, repair, and overhaul (MRO) into cost avoidance streams. Central to a PBL contract is a requirement to perform a business case analysis (BCA) and central to a BCA is the frequent need to use METRIC-based approaches to evaluate how a supplier and customer will engage in a performance based logistics arrangement where spares decisions are critical. Due to the size and frequency of the problem there exists a need to improve the efficiency of the computationally intensive METRIC-based solutions. We develop and validate a practical algorithm for improving the computational efficiency of a METRIC-based approach. The accuracy and effectiveness of the proposed algorithm are analyzed through a numerical study. The algorithm shows a 94% improvement in computational efficiency while maintaining 99.9% accuracy.

Modeling diminishing marginal returns in ahierarchical inventory system of reparable spare parts

Safety stock levels of reparable spare parts in a hierarchical inventory structure are determined relative to the marginal improvement to end item availability provided by each stock level. This research is focused on the United States Air Force (USAF) hierarchical inventory and repair system as modeled by the Multi‐Echelon‐Technique‐for‐Recoverable‐Item‐Control (METRIC) methodology. A piecewise linear modeling framework is introduced based on output from the Aircraft Availability Model (AAM), a model that is part of the METRIC family of models. The underlying nature of the piecewise linear formulation provides integer stock levels with continuous decision variables. This model provides the highest attainable end‐item availability relative to an inventory of reparable spare parts. Additionally, the model provides a robust platform for the conduct of extensive post‐optimality analysis. While this research focuses on the METRIC family of models, the methodology developed may be applied to any hierarchical inventory of reparable spares that conforms to the model’sunderlying mathematical structure.