對於製造執行系統(Manufacturing Execution System, MES)此種具整合與協調性質的系統軟體而言，隨著時間增加，由於其內在組成或外在條件的相對變化，加上隨系統日趨穩定所日益增加之效益需求，將影響甚至破壞其系統原組成之間如信賴、同步、協調與合作等之功能，從而構成現今此種系統運作上之嚴格挑戰。本論文將以系統的觀點，從適應設計 (Adaptive Design)、評估度量 (Evaluation Metrics)、與行為驗證 (Behavior Verification)等三個層面來考量系統之適應能力；並依該系統之生命週期內的不同生命階段，逐一探討此三方面的需求與特性。

在適應設計方面，提出一智慧型系統核心，並定義藉以溝通之系統內訊息介面格式，如此可解決如CIM Framework 在系統模型上經驗知識的不足，亦解決其更易交換訊息上的限制。在核心元件部分將運用多重策略組合，並封裝這些策略本身的演算法，如此將可因應當其他物件變更時，能保留外在一貫的介面；至於內在之處理策略亦將適當變更，例如採用不同程度的歷史紀錄方式，或不同層次的容錯回復方法，如此則可有效吸收測試與驗證階段的風險。此外，在介面訊息部份，則提出採取XML Ontology之描述方式，其格式可有效提供不同階段之界面訊息更改，以期滿足系統環境變動的需求。

在評估度量方面，首先定義系統上，於物件導向設計與開發過程中，計算各物件內與之間的設計屬性如封裝(Encapsulation)、耦合(Coupling)、與內聚(Cohesion)等定量性的量測指標；並定義相關軟體性能指標與其系統運作策略之關係，如可擴充性(Expandability)、可修改性(Modifiability)、與強健性(Robustness)等。就不同生命階段下，透過模糊化指標的權重調整，以解決系統多種軟體指標衝突的議題。經由歷代的比較，據以提供系統內各物件變更其設計，或調整其運作策略的依據。

在行為驗證方面，主要從系統使用歷程中，根據特性目標並與目前分類作相似度分析。經過分群後，即可萃取出其中之行為模式 (Behavior Pattern)，這些模式除轉存為歷次分類之參考外，更可就這些行為模式中各物件的參與程度，配合物件就該模式之信譽評估(Credit Evaluation)函數，以建立該物件之成熟度，並進而結合評估度量指標，以提供系統中各物件可靠性之參考依據。

總之，對一MES而言，若能參考到有效的系統指標，並內建具適應能力的系統核心與介面，且能累積歷代的經驗模式，則當有限變動時，系統將可進行有限時間限制下之變更調整，如此系統將仍具有相當的穩定性與可靠度，順遂滿足其在生命週期中適應能力的需求。

The Manufacturing Execution System (MES), the system software that possesses the properties of integration and coordination, faces a severe challenge. Because of the relative changes of the internal compositions and/or external conditions, and the increasing efficiency requirements, the relationships of trust, synchronization, coordination, and cooperation of the original system will be affected or even destroyed. Therefore, this work bases on the system’s standpoint, and from the aspects of Evaluation Metrics, Adaptive Design, and Pattern Retrieval to concern about the adaptability of the system. Besides, by each stage of the system life cycle, we respectively explore the requirements and properties of these three aspects.

For Adaptive Design, we propose an intellectual system kernel and define such a kernel to be responsible for the communication between different formats of message interfaces in the system. Therefore, we are able to solve the problems that CIM Framework encounters, for example the lacking of experiences and knowledge about the system model, and the inflexibility to message exchange and modification. For the components of such a kernel, we apply the multi-policy aggregation to encapsulate the algorithm of each policy; therefore, we are able to remain the consistency of the external interface of the kernel as once other objects is changed or modified. As to inner policies, some proper modifications will be done, such as adopting different degrees of history logging and different levels of failure recovery; hence, the risks that may happen during testing and verification can be greatly reduced. In addition, for the interface messages, we adopt XML ontology that provides the flexibility of the efficient modification to the interface messages of different stages to fulfill the requirements of system environmental changes.

During the process of object-orientated design and development, we take Evaluation Metrics to define the design attributes, such as encapsulation, coupling, cohesion, etc. to an object or among objects; and then define the relationship between the performance indices of the relative software and the operation of the system schemes, such as expandability, modifiability, robustness, etc. Referring to different stages of the life cycle, we eliminate the conflicts between different software in the system by applying the fuzzy weighting adjustment to the indices. Then through comparing the performances of different generations, these indices serve as very important references for each object in the system when the design is changed or the operation schemes are modified.

For Behavior Verification, we mainly apply the similarity analysis to the history of system usage according to the properties and current classification. After grouping, we are able to extract the behavior patterns. These behavior patterns can be saved as the references for subsequent classification. Moreover, the maturity of objects is established by the credit evaluation function from the participation of objects in these behavior patterns. Further, combining the maturity with other evaluation indices can serve as references for reliability of each object in the system.

Briefly, a MES that can effectively refer to system indices, has a built-in system kernel and interfaces which possess adaptability, and is able to accumulate the behavior patterns of experience from past generations, then this MES is able to be changed or modified under certain time limitations and still remain certain degrees of stability and reliability to fulfill the requirements of adaptability during life cycle generation.

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