在與生產設備連接的全工廠邊緣裝置上實現智能製造服務，並使得這些製造服務可通過網絡插拔，隨插即用和可管理，是一項具有挑戰性的任務，也對促進實現智能工廠非常有利。本論文利用雲計算，邊緣計算和兩層式RESTful 網路服務等技術，提出了一種基於雲的可插拔製造服務機制（CPMSS, Cloud-based Pluggable Manufacturing Serivce Scheme），來解決上述問題。通過使用兩層RESTful服務機制，能以可插拔應用程式模組（PAM）的形式構建製造服務。CPMSS允許工程師使用網頁操作介面(Web GUI)將選定的PAM從雲端平台部署至目標邊緣裝置中，並能夠遠程運行和管理PAM，以便為所連接的生產機台提供各種智能製造服務。CPMSS可支援各種不同語言實現的PAM，例如腳本語言Python、R等，以及編譯式語言C#、Java等。最後，本論文以3種PAM：(1) R PAM-太陽能電池PECVD機台之預測性維護(Predictive Maintenance)、(2) C# PAM-螺絲破損偵測(Breakage Detection)、及(3) Python PAM-鍛造模具老化特徵萃取(Feature Extraction)，進行整合測試及效能評估，測試結果驗證了所提CPMSS之有效性與效率。因此，CPMSS可作為在全工廠邊緣設備上實現智能機邊製造服務之可行方案。

Implementing intelligent manufacturing services on factory-wide edge devices connected with production equipment efficiently so that those manufacturing services are pluggable, plug-and-play, and manageable through the network is a challenging task and is highly beneficial for facilitating realizing a smart factory. This thesis proposes a cloud-based pluggable manufacturing service scheme (called CPMSS) by leveraging cloud computing, edge computing, and RESTful Web Service to address this issue. By using a two-layer-RESTful-service mechanism, the manufacturing services can be built in the form of pluggable application module (PAM). The proposed CPMSS allows the engineers to deploy selected PAMs from the cloud to target edge devices efficiently to provide intelligent manufacturing services for production equipment. Further, CPMSS enables the engineers to
run and manage the plugged PAMs remotely through the cloud platform using Web-based GUIs for supporting intelligent manufacturing activities on target production equipment. Thereby, CPMSS can facilitate fast and factory-wide deployment of intelligent manufacturing services on edge devices for supporting smart manufacturing. In addition, CPMSS can support various types of PAMs implemented in different languages, including scripting languages, such as Python and R, and complied languages, such as C# and Java. Finally, a R-based PAM that implements a function for predictive maintenance of PECVD equipment of solar cell manufacturing, a C#-based PAM that implements a function for screw breakage detection, and a Python-based PAM that implements a function for feature extraction of forging die aging are used to conduct the integrated tests and performance evaluation of CPMSS. Testing results validate the effectiveness and efficiency of the proposed CPMSS, which can thereby provide a promising solution to implementing manufacturing services on factory-wide edge devices.

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