建立直升機主旋翼葉片維修策略

Developing A Maintenance Strategy For The Main Rotor Blade Of Helicopters

林永仁(Yung-Jen Lin) ； 藍天雄(Tian-Syung Lan) ； 曾瑞穎(Jui-Ying Tseng)

《管理資訊計算》 4卷特刊1 (2015/08) Pp. 136-147

https://doi.org/10.6285/MIC.4(S1).15

摘要

因應不同任務需求，直升機維修需求量不斷增加，但零附件故障影響比例甚高，若能對直升機的關鍵零附件建置故障預測系統，並於故障前即執行檢修，將有助於降低因非預期性故障所導致的航班延誤，作為直升機零附件維修管理上的一項參考。本研究以A型直升機的主旋翼葉片為例，首先採用德菲法(Delphi Method)製作第一次專家調查問卷，蒐集關鍵因素，再運用李克特五點量表(Likert)評選出重要關鍵因素，再選定2012年至2014年主旋翼葉片的維修資料數據為樣本，載入倒傳遞類神經網路軟體（Neuro Intelligence）建置預測模式，以預測主旋翼葉片下一次故障。經由倒傳遞類神經網路軟體學習訓練後，關聯性（Correlation）與模式配適度（R-squared）分別達到0.999及0.998，預測準確度高達97%，可有效作為直升機零附件壽命預測的方法。

關鍵字

直升機零附件 ； 德菲法 ； 李克特量表 ； 倒傳遞類神經網路

並列摘要

In response to operation readiness, disaster prevention, disaster relief, transportation and a variety of different mission requirements, the demand for helicopter maintenance is keeping increased, but the part failures highly affect flights and missions. If we can create prediction systems for the helicopters’ critical parts failures, so as to perform maintenance before the failure occurs, and that system will help to reduce the rate of flight delays caused by unpredictable failures. The creation may serve as a reference for our Armed Forces to manage its maintenance and spare parts. This study takes the main rotor blade used on the helicopters as an example. At the beginning, it uses Delphi Method to prepare the first expert questionnaire to collect the key factors affecting the life of the main rotor blades. After that, the study uses Likert five-point scale to score the expert questionnaires, and, in accordance with experts’ consistency index, Further, the data of main rotor blade maintenance performing during year 2012 to 2014 is used as samples to be loaded into back-propagation neural network software (Neuro Intelligence) to test the relationship between input and output to build predictive models. The number set is used as BPN prediction criteria in order to predict the usage life of a main rotor blade after installation. After learning and training by the inverted neural network software, the relevance (Correlation) and mode of fit (R-squared) reaches 0.999386 and 0.998655, respectively, and the accuracy of prediction is as high as 97%, and that proves back-propagation neural network is indeed an effective method to predict the life of helicopter parts.

並列關鍵字

Make-To-Order Helicopter spare parts ； Delphi method ； Likert scale ； Back-propagation neural network

參考文獻

王魯湘(2005)，以類神經網路建立消耗性零件之壽命預測模式－以晶圓測試探針卡為例，私立中原大學工業工程學所碩士論文。

李永山、黃錦川、許譽勝（2008），以修正式德菲法探討台灣資訊軟體公司競爭策略之研究 Journal of Informatics & Electronics, Vol.3, No.1, pp.39-50,N ovember

陳東穎（2013），應用倒傳遞類神經網路預測飛機零組件使用壽命，大同大學工程學院工程管理碩士在職專班碩士論文。

張斐章、張麗秋、黃浩倫(2010)，類神經網路：理論與實務，台北市：臺灣東華書局。

葉怡成(2001)，類神經網路模式應用與實作，儒林圖書有限公司。