現代戰機具高科技、高造價、結構繁雜、系統複雜與品質要求高標準，有關維修作業規劃，將直接影響戰機成軍服役期間之妥善之情況。灰色預測並非藉尋找系統內經統計後呈規律數列的方法達成，而是將雜亂無章之原始數據經過處理後，來尋找數據的內在規律性，經由處理過後之數列轉化為微分方程式，建立灰色預測模型。灰色關聯分析是將系統內各因素間灰色關聯清晰化，找出影響目標值的重要因素。 本研究結果分析顯示灰色預測模型精確度均在95％以上，得知GM(1,1)模型為極佳模型，適用於戰機主要系統失效預測之應用。灰色關聯分析後得知氧氣系統失效影響戰機為最大，燈光系統失效影響次之；另戰機失效影響最小的為燃油系統，電力系統次之。綜言之，本研究期盼從系統失效量數據中預測未來發生量及找出失效維修之影響因素，作為提供後勤維修管理階層決策之參考。 The modern fighters are provided with high-technology, high-price, sophisticated structure and system characteristics as well as the high-quality requirements. The maintaining planning is the crucial factor to affect the availability of the fighters during the serving period. Grey Analysis is used to find the regular patterns for the original data. It will build up Grey Forecast Model after processing. Grey Relation Analysis is also used to clear up all factors in each system and look for the best important one toward the target object. Moreover, the accuracy is more than 95 percent after this analysis. It shows that the GM (1,1) Model is the optimum model for the malfunction predication of fighters. According to the Grey Relation Analysis, two main factors which cause the malfunctions of fighters are as follows: Oxygen System and Lighting System failures. In contrast, the least two factors are Fuel System and Electrical Power System failures. To sum up, to find the future valve and the influential factors of system failure from the demonstration is our purpose and we also expect this study can help the authority to make the right decisions in logistics and maintaining fields.
