臺灣博碩士論文加值系統

工業4.0為我國政府近年來積極推動的產業升級計畫，其是以資訊科技為核心技術，並結合工廠現有操作技術整合後的系統，且以數據分析為基礎概念，目標為打造具適應性的智慧工廠。而在營建工程的產業中，並不常具有大量標準化流程特性的生產作業，鋼構廠鋼結構構件的生產為少數符合標準化作業特性的營建產業。因此本論文以鋼構廠之構件生產作業為研究對象，嘗試導入建築資訊模型(Building Information Model,BIM)與BLE定位的技術，以實現鋼構構件生產履歷與品保資料收集數位化、自動化的目標，提升生產線作業資料收集的品質與效率。
本研究之目的是自BIM自動化地擷取出鋼構生產線上所需記錄之各種生產履歷與品保資料之檢查對象，並進一步導入BLE室內定位技術，研究如何運用其提升鋼構廠現場資料收集的效率。其首先使用Tekla Structures進行BIM軟體的操作，並利用其應用程式介面Tekla Open API 進行程式開發，嘗試將生產線上原由人工進行判讀取得的資訊，改以程式自動化計算方式由BIM模型中擷取或推算出來，並記錄於資料庫以供現場生產人員選取，應用於現場的檢查項目的資料提供，且本研究建立電子化的表單與資料庫以紀錄生產履歷與品保資料，並利用BLE室內定位技術與QR Code識別廠內構件與生產人員在生產線上的位置以更自動化的方式進行生產履歷與品保資料收集，藉由自動化的BIM資訊提供以及電子化作業程序的結合，以達到減少人力資源與時間成本。

Industrial 4.0 is the industrial upgrading program which is actively promoted by the government in recent years. It is an integrated system with information technology as the core technology and combined with the existing operating technology of the factory. In addition, it further adopts data analysis, the goal is to build an adaptive smart factory. However, in the construction industry, most of the production operations are not often with a standardized process. The production of steel structural components in steel structure factories is the few one that meet the characteristics of standardized operations. Therefore, this thesis takes the component production operations of steel structure factories as the research target, and tries to introduce Building Information Model (BIM) and BLE indoor positioning technologies to realize the digitalization and automation for data collection of production history and quality assurance. The goal is to improve the quality and efficiency of operations in the production line.
The goal of this study is to use BIM to automatically extract various inspection items which need to be recorded for production history and quality assurance in the production line. Furthermore, the BLE indoor positioning technology is used to improve the efficiency of field data collection in steel structure factories. This study first adopts Tekla Structures as the BIM software, and uses its application program interface (Tekla Open API) for program development. Based on an existing BIM, the plug-in program can automatically calculate the information that was originally acquired by manually interpretation on the production line, and store in a database for providing the information to assist on-site production personnel to check the inspection items. In addition, this study establishes electronic forms and databases to record production history and quality assurance data, and uses BLE indoor positioning technology and QR Code to identify the position of factory components and production personnel on the production line in a more automated way to collect information. Through the combination of the above-mentioned BIM-based automated information provision and electronic operation procedures, human resources and time costs are reduced.

目錄
論文摘要 1
圖目錄 6
表目錄 8
第一章 緒論 9
1.1 研究背景與動機 9
1.2 研究目的 12
1.3 研究範圍 14
1.4 研究方法 14
1.5 論文架構 15
第二章 文獻回顧 16
2.1 相關研究發展 16
2.1.1 BIM 16
2.1.2 工業4.0 17
2.1.3 低功耗藍芽 (BLE,Bluetooth Low Energy)與室內定位 17
2.2 系統開發技術 19
2.2.1 Tekla Structures 19
第三章 系統需求分析與功能 21
3.1 模型資料擷取 21
3.2 生產履歷與品保資料收集介面 22
3.3 室內定位判斷站別 23
3.4 構件識別與人員識別 24
第四章 系統架構與運作機制 26
4.1 資料庫架構 26
4.1.1 基於BIM產生之物料清單資料庫 26
4.1.2 生產履歷與品保資料收集資料庫 26
4.1.3 人員資料庫 26
4.2 模型資料擷取 28
4.2.1 構件資料擷取 29
4.2.2 零件資料擷取 30
4.2.3 計算產生U銲資訊 31
4.2.4 計算產生本體板資訊 32
4.3 生產履歷與品保資料收集介面 33
4.3.1 介面操作共同項目 34
4.3.2 生產履歷與品保資料收集介面各站別記錄項目 35
4.4 BLE室內定位站別判斷 42
4.5 人員識別與構件識別 45
第五章 定位實驗與鋼構廠實際驗證 48
5.1 使用工具 48
5.1.1 手持智慧型行動裝置 48
5.1.2 藍芽發射器 49
5.1.3 軟體開發 51
5.2 BOX柱一次製程廠內配置 51
5.3 模擬實驗 52
5.3.1 發訊裝置配置 53
5.3.2 訊號強度地圖建立 57
5.3.3 模型訓練與測試 58
5.3.4 定位正確性驗證 61
5.3.5 投票機制決定生產站別 66
5.4 鋼構廠廠內實測 70
5.5 系統使用情境於鋼構場之展示 72
第六章 結論與未來展望 76
6.1 結論 76
6.2 未來展望 77
第七章 參考文獻 79

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