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工業技術研究院

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技術名稱: 工業大數據智能分析與管理系統

技術簡介

工業大數據智能分析與管理系統是一個完整的應用方案,包含了從前端資料擷取到後端網頁視覺化呈現等系統元件,其分析模組提供了工業領域所需要的管理工具,如能源管理、整體設備效率監控、轉動設備預知保養、生產製程監控與預測等功能,透過APP推撥、email、或簡訊等,使用者可於行動裝置獲得即時訊息,搭配內部行政管理與外部激勵措施,應用此系統將可獲得能源使用降低、設備妥善率提高、生產排程優化等改善效益。

Abstract

The Industrial Big Data Intelligent Analysis and Management System is a total solution, which includes necessary components from front-end data acquisition and back-end webpage. The analysis module provides management tools needed in the industrial field, such as energy management, overall equipment efficiency monitoring, rotating equipment predictive maintenance, production process monitoring and prediction. Through the email, message, or APP push, users can get instant information on mobile devices. With internal administrative management and external incentives, the application of this system will result in improved benefits such as reduced energy use, improved equipment availability, and optimized production schedules.

技術規格

(1)系統管理模組:可接受工業泛用通訊協定之資料來源(Modbus, BACnet, OPC UA等);以大數據資料庫(Hadoop\Hbase)與關聯式資料庫(SQL)儲存各類型資料;可使用開源分析工具(如R, Spark, Python等);執行於虛擬機器環境,具備可擴充和分散式運算能力。 (2)能源管理分析模組:提供電力的即時使用與統計資訊,並對生產過程所使用的蒸汽、燃料、空氣等能源物料,提供其使用狀態與分析資訊。 (3)能源基線建置與管理模組:以統計分析工具建立能源基線,用以作為能用使用異常監視或改善前後效益評比。 (4)整體設備效率(OEE)監控技術:提供產品能源單耗與設備OEE效率等資訊,並監視相關製程參數,用以提高能源使用效率。 (5)統計製程管制(SPC)技術:提供管制線計算與管制規則設定之功能,用以監視生產過程的產品品質或能源使用。 (6)多變量統計製程管制(MSPC)監控預測技術:以高階的多變量分析技術監控製程異常發生,減少跳?等所造成之製程減產損失,並可對關鍵品質進行預測。 (7)轉動設備預知保養技術:監控與預測轉動設備異常發生,有效管理關鍵設備提高妥善率。

Technical Specification

(1) System management module: Receive the data from devices with the function of industrial generic communication protocol (Modbus, BACnet, OPC UA, etc.); data storage using big data database (Hadoop\Hbase) and associated database (SQL); Open source analysis tools (such as R, Spark, Python, etc.); executable in a virtual machine environment with scalable and decentralized computing power. (2) Energy management analysis module: Provides real-time use and statistical information of electricity, and provides information on the status and analysis of energy materials such as steam, fuel, and air used in the production process. (3) Energy baseline establishment and management module: Establish an energy baseline using statistical analysis tools to serve as an anomaly monitoring or a benchmark to verify the performance after improvement action. (4) Overall Equipment Efficiency (OEE) monitoring technology: Provide information such as unit energy consumption of a product and overall equipment efficiency, and monitor relevant process parameters to improve energy usage. (5) Statistical Process Control (SPC) technology: Provides the function of control line calculation and control rule setting to monitor product quality or energy use in the production process. (6) Multivariate Statistical Process Control (MSPC) monitoring and prediction technology: Advanced multivariate analysis technology is used to monitor process anomalies, reduce process losses caused by fleas and predict critical quality. (7) Rotating equipment predictive maintenance technology: monitoring and predicting abnormal occurrence of rotating equipment, effectively managing key equipment to increase the availability.

技術特色

(1)本方案是從前端資料擷取到後端網頁視覺化呈現的完整應用方案。 (2)採用開源平台,使用者對系統維護與開發有較多自主權。 (3)大數據資料庫可以整合全廠各類型數據,並能保持高效率的資料庫讀取性能。 (4)自主開發的工業領域分析模組,提供圖形化分析工具與網頁,有效解決一般性管理需求。 (5)採用開源的分析工具,透過客制化設計,能解決特殊性的管理需求。

應用範圍

工業領域的生產廠場

接受技術者具備基礎建議(設備)

none

接受技術者具備基礎建議(專業)

對程式語言、通訊協定、作業系統、數據分析等有一定瞭解基礎。

技術分類 01 綠能環境

聯絡資訊

聯絡人:劉子吉 電網與電力電子技術組

電話:03-5914258 或 Email:tzuchi.liu@itri.org.tw

客服專線:+886-800-45-8899

傳真:03-5916457

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