本文之目標以提昇傳統鋼筋產業製程的效率與品質為主，影響製程效率與品質之因素有—製程與排程之瓶頸、物料傳輸之瓶頸、控制系統非最佳化、以及參數因製程變動浮動不定等因素，如全面更新設備所費不貲，尤其對中小企業是一沉重之負擔，唯有逐步、局部合理化與最佳化，方可花費最小，達最佳之效益。故依此一原則，首先對製程進行合理化與資訊網路化、e化，找尋最佳之資料流程與排程，與物料傳輸流程；此故，首需藉由製程之控制系統網路化—建立乙太網路之控制系統，將各製程關鍵瓶頸點網路e化，使控制工程師能快速且正確經由PLC/PC之網路，將鋼筋生產流程輸入適當的參數，並由監控系統遠端監測整個製程的關鍵細節與管制。且配合自行開發的生產管理專家系統和資料庫的整合，針對生管、品管、排程、人員等資訊管理方式，來提昇鋼筋製程的網路整合能力，藉以減少人力資本、提昇工作效率、降低成本支出、增加競爭力。並將前述各關鍵之系統加以整合、監控、管理等三大目標應用於實際鋼筋製程廠，並經實地測試與修正改良，達到製程e 化及遠端監控研究的實用效能。
其次，討論製程控制器響應與穩定度之改善，此一部份著重於鋼筋軋延製程中的最佳化控制探討，由於鋼筋是基礎建設的必需品，其品質的優劣影響建設的可靠度與穩定性，如何確保製程品質的穩定及效率提昇增加競爭性，是現今重要課題，而鋼筋拉力與張力特性，受軋延製程之張力控制影響甚大，如何維持軋延恆定張力控制為其重點；所以必須在軋鋼單元中的控制器加以探討，傳統軋延張力控制使用PID控制器方式進行，唯這種方式需要準確的數學模式，然而鋼筋製程，欲取得準確的數學模式較困難，因此傳統製程依靠人為調整，因而設定的參數並非一定是最佳值，因此本文就在固有的控制迴路上加上神經網路來加速原本系統控制響應，進而提高其產品品質。

The purpose of this thesis is to improve efficiency and quality for traditional steel bar factory. The factors of influencing effect and quality in manufacturing process are bottleneck of manufacturing process and scheduling process, bottleneck of materiel transmission, non optimum in control system, and fluctuating parameter as a result of alteration in manufacturing process and more. To renew entire apparatus costs a great deal. To renew entire apparatus costs a great deal. Particularly in Small and Medium Enterprises, it is a burden. Only gradual, partial rationalization and optimum can achieve at optimum efficiency and minimum spending. Based on that, firstly, we undergo rationalization, information over the internet and e-type in manufacturing process to find optimal information flow, scheduling flow and material transmission flow. And depending on establishing Ethernet control system in manufacturing process, we get e-type network for the keys bottleneck. Then the control engineers can input appropriate parameters in steel bar manufacturing process quickly and correctly through PLC/PC network. Furthermore, we use monitor system on remote controlling and monitoring for keys bottleneck in all manufacturing process. In order to reduce manpower expenses, enhance work efficiency, reduce the cost and enhance network integrative ability, we integrate expert system of production management and database aiming at management such as production, quality, scheduling process, workers etc,. We finally combine three major objectives--the foregoing keys system, monitoring system, and management system and apply to the cooperative factory. Through actual operation, revision and improvement, we get the practical result of e - type procreation process and remote monitor.
The next, we are improving response and stability in manufacturing processes controller. In the part stressed optimum control in steel bar roller mill. Steel bar is a requirement in a building, and its quality affects dependability and stability of the building. How to ensure stable quality of procreation process, enhance efficiency and increase competitive edge is one of important topics nowadays. Steel pulling force and tensile force are influenced by tension control of a roller mill. So the focus is how to maintain constant in tension control. In a traditional roller mill tension controller always uses PID or linear quadratic. This method requires accurate math function, but it is just hard to get accurate math function in the steel bar manufacturing processes. So the controller depends on workers to adjust parameter in a traditional roller mill but the adjusted parameter maybe not the best. Our purpose is to add neural network into inherent PID controller loop in order to accelerate the system response and enhance product quality.

中文摘要------------------------------------------------------------------------------------------- Ⅰ
英文摘要------------------------------------------------------------------------------------------- Ⅲ
致謝------------------------------------------------------------------------------------------------- Ⅴ
目錄------------------------------------------------------------------------------------------------- Ⅵ
表目錄---------------------------------------------------------------------------------------------- Ⅶ
圖目錄---------------------------------------------------------------------------------------------- Ⅷ
緒論------------------------------------------------------------------------------------------------- 1
1.1研究動機-------------------------------------------------------------------------------- 1
1.2研究方法-------------------------------------------------------------------------------- 2
1.3論文大綱-------------------------------------------------------------------------------- 3
第二章 鋼筋製程系統架構------------------------------------------------------------------- 5
2.1鋼筋製程流程-------------------------------------------------------------------------- 6
2.2製程監控系統架構-------------------------------------------------------------------- 11
2.3軋延控制系統架構-------------------------------------------------------------------- 13
第三章適應性神經網路------------------------------------------------------------------------ 16
3.1適應性神經網路----------------------------------------------------------------------- 16
3.2適應神經網路應用於直流馬達的速度控制------------------------------------ 22
第四章案例研究--------------------------------------------------------------------------------- 26
4.1製成監控系統功能-------------------------------------------------------------------- 26
4.2軋延系統模擬過程-------------------------------------------------------------------- 37
第五章結論與展望------------------------------------------------------------------------------ 53
5.1結論--------------------------------------------------------------------------------------- 53
5.2未來展望-------------------------------------------------------------------------------- 54
參考文獻------------------------------------------------------------------------------------------- 55
附錄一現場元件功能說明及位置配置圖------------------------------------------------- 58

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