機車產業在目前經營環境不斷改變下，若備用零件之庫存能良好的管控，將可使機車維修服務的品質得以維持，其中備用零件需求預測的精確度的好壞便顯得格外重要，然而，備用零件之需求量為隨機且不規則發生的需求型態，此讓事前作需求預測較為困難，本研究針對機車產業備用零件需求預測議題加以探討，盼能找出最適宜之備用零件需求預測方法。
本研究模式建構上考慮到使用正副廠零件與季節性因素，並以貝氏統計配合馬可夫鏈蒙地卡羅法對模式參數進行校估。實證研究主要挑選出40種備用零件，並比較本研究方法實證結果與時間序列預測方法(移動平均法、指數平滑法、CR法與各CR法修正法)以及常態壽齡模式的需求預測能力。
結果發現，本研究模式之預測效果最佳，代表本研究模式在預測間歇型需求資料上是相當適切的。此外，值得一提的是本研究實證結果中使用正廠零件比率之資訊，可供機車產業管理者作為訂定經營策略之用。

The environment of motorcycle industry is changing currently. If the spare parts in inventory can be control well, it will make the motorcycle maintain service to keep the quality. Among them, the spare parts demand forecasting accuracy will be particularly important. Therefore, the random demand and uncertainty for spare parts make the demand forecasting more difficult. This study discuss this problem and hope to find the most appropriate method to forecast demand for spare parts.
This research considers to introduce the usage rate of genuine spare parts and seasonal factors to construct the demand models, and we through Bayesian statistics with Markov Chain Monte Carlo method (MCMC) to estimate model parameters. This research choose 40 spare parts, and Comparing the forecasting abilities of our models and time series forecasting methods(moving average method, exponential smoothing method, CR method, and the modification CR method), and the normal life time model.
As a result, our models have the best performance for demand forecasting, and our models are quite appropriate for forecasting intermittent demand. In addition, using the information of genuine spare parts ratio in this research, can help the motorcycle industry managers to adjust their market strategy.

摘 要......................................................i
ABSTRACT..................................................ii
誌謝.....................................................iii
目錄......................................................iv
表目錄....................................................vi
圖目錄...................................................vii
第一章 緒論................................................1
1.1 研究背景與動機..........................................1
1.2 研究目的................................................3
1.3 研究範圍與限制..........................................4
1.4 研究架構................................................4
第二章 文獻探討.............................................6
2.1 備用零件需求特性.........................................6
2.2 需求預測方法介紹.........................................7
2.2.1 移動平均法............................................9
2.2.2 指數平滑法............................................9
2.2.3 Croston法...........................................10
2.3 備用零件需求預測相關文獻回顧.............................13
2.4 馬可夫鏈蒙地卡羅法......................................14
2.4.1 馬可夫鏈.............................................15
2.4.2 蒙地卡羅積分法.......................................16
2.4.3 Metropolis-Hastings演算法...........................16
2.4.4 Gibbs演算法.........................................18
2.5 小結..................................................19
第三章 研究方法............................................20
3.1 問題描述與模式理念......................................20
3.2 預測模式設計與建構......................................22
3.2.1 符號定義.............................................22
3.2.2 建構模式說明.........................................23
3.3 參數校估...............................................26
3.3.1 貝氏定理說明.........................................26
3.3.2 待估參數推估.........................................27
3.4 小結..................................................30
第四章 實證研究分析.........................................31
4.1 實證資料說明...........................................31
4.2 備用零件預測之實證研究分析...............................36
4.2.1 本研究模式程式運作時間改善成效說明......................36
4.2.2 本研究模式預測結果說明................................37
4.2.3 本研究模式與常態壽齡模式預測結果之比較分析...............44
4.2.4 本研究模式與各時間序列預測法結果分析....................46
第五章 結論與建議...........................................51
5.1 結論..................................................51
5.2 本研究貢獻.............................................52
5.3 未來研究建議...........................................53
參考文獻...................................................54
中文文獻...................................................54
英文文獻...................................................55
附錄一 各時間序列方法參數校估值..............................59
附錄二 本研究備用零件預測結果走勢圖...........................61

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