An Ordering Decision-Making Approach on Spare Parts for Civil Aircraft Based on a One-Sample Prediction

Sun, Yongquan; Hao, Xueling; Su, Zimei; Ren, He

doi:10.1109/access.2018.2818404

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…52 The scholar then employed a Weibull process to establish a prediction model for LRUs in the airline, downtime was predicted through the point estimation and prediction limits under different confidence levels. 53 Zhang et al 54 aimed at the management problem of spare parts whose life is subjected to Weibull distribution, proposed an optimization model based on residual life prediction. Lowas et al performed a Monte Carlo simulation of notional aircraft components that subjected to Weibull distribution, which provided a simulated spare parts demand characteristics.…”

Section: Failure Observation Methods Of Spare Parts Predictionmentioning

confidence: 99%

Civil Aircraft Spare Parts Prediction and Configuration Management Techniques: Review and Prospect

Feng

Chen

et al. 2021

Advances in Mechanical Engineering

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Spare parts are treated as the basis to guarantee the safe and economic operation of civil aircraft, its scientific prediction and reasonable configuration play an important role in perfecting integrated logistics support (ILS) and achieving win-win situation of stakeholders (e.g. manufacturers, operators, maintenance providers). This paper studies the existing spare parts prediction and configuration methods of civil aircraft, and discusses future development trend of spare parts from the perspective of prediction and configuration, respectively. The current development status of civil aircraft spare parts prediction techniques are firstly introduced, according to demand characteristics of spare parts; the present research status of civil aircraft spare parts configuration methods are then elaborated, based on the traditional methods and machine learning methods; the development trend of civil aircraft spare parts prediction and configuration methods is finally analyzed, combined with the advantages and disadvantages of the existing methods of civil aircraft spare parts management methods. The efforts of this work provide a reference for the comprehensive management of civil aircraft spare parts and improve the perfection degree for the ILS of civil aircraft.

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Section: Failure Observation Methods Of Spare Parts Predictionmentioning

confidence: 99%

Civil Aircraft Spare Parts Prediction and Configuration Management Techniques: Review and Prospect

Feng

Chen

et al. 2021

Advances in Mechanical Engineering

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“…Table 1 shows the previous works, searched initially by us to investigate spare parts demand forecasting in various industries. Though the applications of spare parts demand forecasting have been made in different industries such as electronics [34], automobile [35], mining [11], maintenance/repair [36,37], consumer goods [38], aviation [39][40][41], energies [42], etc., those can be grouped into three according to their demand forecasting methods as shown in Table 1. Table 1, we could confirm that the prior works on spare parts demand forecasting have applied different methods to solve their specific problems in their industries.…”

Section: Reviews On Related Workmentioning

confidence: 99%

Forecasting Spare Parts Demand of Military Aircraft: Comparisons of Data Mining Techniques and Managerial Features from the Case of South Korea

Choi¹,

Suh²

2020

Sustainability

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In a weapon system, the accurate forecasting of the spare parts demand can help avoid the excess inventory, leading to the efficient use of budget. It can also help develop the combat readiness of the weapon system by improving weapon system utilization. Moreover, as performance-based logistics (PBL) projects have recently emerged, the accurate demand forecasting of spare parts has become an important issue for the PBL contractors as well. However, for the demand forecasting of spare parts, the time series methods, typically used in the military sector, have low prediction accuracies and the PBL contractors are mostly based on the judgment of practitioners. Meanwhile, most of the previous studies in the military sector have not considered the managerial characteristics of spare parts (e.g., reparability and the irregularity of maintenance). No previous work has considered any such features, which can indicate the reliability of spare parts (e.g., mean time between failures (MTBF)), although they can affect the spare parts demand. Therefore, to develop a more accurate forecasting of the spare parts demand of military aircraft, we designed and examined a systematic approach that uses data mining techniques. To fill up the research gaps of related works, our approach also considered the managerial characteristics of spare parts and included the new features that represent the reliability of spare parts. Consequently, given the case of South Korea and the full feature set, we found random forest gave better results than the other data mining techniques and the conventional time series methods. Using the best technique Random Forest, we identified the contribution of each managerial feature set to improving the prediction accuracy, and we found the reliability and operation environment are valuable feature sets in a significant way, so they should be collected, managed more carefully, and included for better prediction of spare parts demand of military aircraft.

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“…At present, most of the maintenance cost prediction research is carried out for military and civil aircraft (Castagne et al, 2008;Chen et al, 2019aChen et al, , 2019bJohnson, 1990;Ross and Crossley, 2000). The cost prediction method for aircraft mainly includes grey correlation analysis (Chen et al, 2021;Hu et al, 2015), multiple linear regression (Chen et al, 2019a(Chen et al, , 2019bScanlan et al, 2002;Zhang et al, 2014), BP neural network (Li et al, 2012;Sun and Li, 2012;Wu and Yuan, 2011;Zhou and Zheng, 2007), engineering estimation (Sun et al, 2018), support vector machine (Ben-Arieh, 2000;Wang et al, 2014) and genetic algorithm (Yang and Yang, 2012). Large international aviation enterprises usually use parameter method to predict the maintenance cost of civil and military aircraft and express the maintenance cost by the performance parameters of some aircraft and engines.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the maintenance cost of general aviation aircraft based on engineering method

Chen

Chu

Zhang

et al. 2023

AEAT

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Purpose General aviation aircraft has a wide range of applications, and effective cost management is one of the hot spots in the research of general aviation manufacturers. The purpose of this paper is to build a flexible engineering method to predict maintenance cost of general aviation aircraft. Design/methodology/approach To establish a reasonable general aviation aircraft maintenance cost prediction model, it is necessary to analyze the influencing factors and extract the main components of maintenance cost. The maintenance cost is divided by engineering method, and the estimation model of each component cost is established. Then, the general aviation aircraft maintenance cost model is obtained. The results show that the relative error of this method is between 13% and 20%, which has a good estimation accuracy and can be effectively used to estimate the maintenance cost of general aviation aircraft. Findings The maintenance cost plays an important role in the life cycle cost of general aviation aircraft. Accurate cost prediction method is of great significance to the optimal design of general aviation aircraft. However, there are few prediction models suitable for maintenance cost, the proposed approach is meaningful and quite desirable. Originality/value To some extent, this method overcomes the shortage of the work on maintenance cost prediction for general aviation aircraft. The model established in this paper has certain generality, which can provide some reference for general aviation aircraft design and operation enterprises.

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An Ordering Decision-Making Approach on Spare Parts for Civil Aircraft Based on a One-Sample Prediction

Cited by 6 publications

References 18 publications

Civil Aircraft Spare Parts Prediction and Configuration Management Techniques: Review and Prospect

Civil Aircraft Spare Parts Prediction and Configuration Management Techniques: Review and Prospect

Forecasting Spare Parts Demand of Military Aircraft: Comparisons of Data Mining Techniques and Managerial Features from the Case of South Korea

Prediction of the maintenance cost of general aviation aircraft based on engineering method

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