隨著產品生命週期縮短，產線需要不斷進行調整，為了能確保製造系統的產出能滿足顧客的需求，我們需要一個強而有力的指標。在許多產業已經運用網路可靠度作為一項重要評估製造系統是否穩健的項目，目前相關的可靠度計算方法，主要是以精確求法為主。然而，精確求法的核心在於列舉所有的可能狀況，當加工機台數量增加，或是在產線上具有多次重工的情況，或是輸入量與需求量之間的差異變大時，精確求法的計算複雜度會呈現指數增長，因隨著製造網路的複雜化，在可行解時需要花費非常可觀的時間，因此當我們面對大型製造網路時，可靠度的計算顯得耗時費力。
為此，本研究提出了一種快速且精確的估計算法，所提之演算法是以蒙地卡羅模擬法為模擬基礎，考慮各工作站的產能以及機台加工的成功率，計算產線的最終產出，並依據產出的結果是否能滿足顧客需求，來估算網路可靠度。為了驗證我們模型的有效性，本研究列舉了四個範例，面對簡易的網路，我們以桑教授 [1] 所提出的Song rule作為精確值，近似算法作為預測值，面對較複雜的網路，因精確值計算需要耗時相當久，我們以桑教授所提的模擬算法來取代Song rule 作為精確值，並且計算MAPE來評估網路可靠度的預測誤差屬何種類型的精確度。從四個範例中，我們得知隨著製造網路的複雜化，在維持高度精確度下，近似算法與模擬算法的計算時間差距會越加明顯。我們提出的方法不僅可以適用於各型態的網路，且因為是一種簡單、有效且快速的方法，非常適合產線人員用來計算製造現場的網路可靠度。

With the shortening of the product life cycle, the production line needs to be constantly adjusted. In order to ensure that the output of the manufacturing system can meet the needs of customers, we need a strong indicator. Network reliability has been used as an important project to evaluate the robustness of manufacturing systems in many industries. However, accurate calculation methods of the core is to list all the possible conditions, when processing the machine number, or on the production line has many heavy industries, or the difference between input and demand grows, the accurate calculation methods of computational complexity can present exponential growth, because along with the manufacturing of complicated network, when feasible solution need to spend a very considerable time, so when we face big manufacturing network, the calculation of reliability is time-consuming.
For this reason, a fast and accurate estimation algorithm is proposed in this study. Based on the monte carlo simulation method, the final output of the production line is calculated by considering the productivity of each workstation and the success rate of machine processing. In order to demonstrate the effectiveness of our model, this study enumerates four examples, in the face of simple network, we put forward to mulberry professor Song rule as a precise value, approximate algorithm as predicted, in the face of complex network, due to the need of precise terms take quite a long time, we sang, a professor at the proposed simulation algorithm to replace Song rule as a precise value, and calculate the MAPE to evaluate network reliability prediction error is what type of accuracy. From the four examples, we know that with the complexity of the manufacturing network, the computational time difference between the approximate algorithm and the simulation algorithm will become more and more obvious while maintaining a high degree of accuracy. Our proposed method is not only applicable to all types of networks, but also is a simple, effective and fast method, which is very suitable for manufacturing personnel to calculate the network reliability of manufacturing site.

摘要 I
Abstract II
誌謝 IV
Contents V
List of Tables VII
List of Figures VIII
Chapter 1. Introduction 1
1.1 Background, significance and motivation 1
1.2 Research Aims 3
1.3 Overview of the Thesis 5
Chapter 2. Literature Review 6
2.1 The concept of network reliability 6
2.2 Manufacturing system to manufacturing network 8
2.2.1 Manufacturing system and supply chain 8
2.2.2 Measure Manufacturing Reworking Problem 9
2.3 Remanufacturing network reliability 11
2.3.1. Method for calculating remanufacturing network reliability 11
2.3.2. Song rule for computing network reliability 12
2.4 Monte Carlo method 20
2.4.1 Overview 20
2.4.2 Typical use and application area of the MCM 20
Chapter 3. Approximation algorithms for network reliability calculation 25
3.1 Problem Definition 26
3.2 Data Collection and State Description 28
3.3 Approximation algorithms for network reliability 31
Chapter 4. Experimental Results and Analysis 39
4.1 Four workstations with one reworking action 41
4.2 Six workstations with one reworking action 44
4.3 Ten workstations with one reworking action 48
4.4 Eight workstations with two reworking action 52
Chapter 5. Conclusion & Further Research 57
References 59

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