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[{"term":"資料庫_BA","id":0,"type":"QUICKLINKS"},{"term":"應用註釋","id":1,"type":"QUICKLINKS"},{"term":"221","id":2,"type":"QUICKLINKS"},{"term":"Buildings","id":3,"type":"QUICKLINKS"},{"term":"WAGO-I/O-PRO","id":4,"type":"QUICKLINKS"}]

客製分析解決方案 2022年8月15日
WAGO Analytics

在優化系統時，挑戰在於改善和量化流程知識，並將結果重新整合到流程中。WAGO Analytics 支援您從數據採集到分析，並創建系統中依賴關係的直覺視覺化。它揭示的相互關係可以納入流程，讓您可以挖掘優化潛力。

在聯合案件中，WAGO 與客戶密切合作，為特定應用中的盈利數據使用開發量身定制的解決方案。

優勢：

  • 識別優化潛力
  • 提高品質水平
  • 量身定制的分析解決方案
  • 更高的效能和更低的成本
  • 提高流程穩定性

新產品

直接從 PLC 程式進行 Analytics 連接

這種用於 WAGO 控制器的新軟體解決方案允許您在不離開熟悉的 PLC 編程環境的情況下分析、評估和優化製程。您無需直接進入 IT 和 Linux® 環境即可使用 WAGO Analytics 應用；眾多功能模組支援數據採集、分析和評估。分析、評估和優化功能在功能強大的 WAGO Edge 設備的後台運行，可執行安裝套件可供使用。所有數據都保存在本地網路中，因此無需連接到其他系統的互聯網。可以輕鬆連接其他數據源，例如，透過 Node-RED。

  • 開始製程數據分析的簡單方法
  • 支援所有分析案件階段
  • 快速簡單的數據視覺化

數據採集的六個步驟
盈利用途

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WAGO 幫助您
有利的使用您的數據

我們幫助您獲得所需的定制分析解決方案。

1. 從各種數據源蒐集原始數據

第一步，與相關領域專家一起確定相關數據源。各種介面的讀取獨立於各自的協定。直接從控制器存取數值，必要時安裝額外的感測器。分析解決方案整合到現有控制系統中，因此在數據採集設置方面諮詢了負責系統的自動化工程。

2. 處理數據

第二步，數據是時間同步的。相關資訊以統一格式提取和解碼。過濾掉不相關的數據並刪除。此外，相關指標會持續計算。這一步驟尤為重要，因為整理數據庫是分析案件成功的基礎。

3. 持續數據採集

在接下來的 第三步，設備或系統的自訂數據記錄器投入運行。數據被儲存並用於深入分析。透過不斷的數據採集產生各種有用的數據。這可以與領域專家一起以測試計劃的形式執行。根據使用情況，在更長的時間段內運行數據記錄也可能就足夠了。

MM-4961_Analytics_Demonstrator_Screenshot_1_2000x1125.jpg

4. 探索性數據分析和正確表示的選擇

第四步 涉及探索性數據分析和正確表示的選擇。在離線分析中，依賴關係和關係被提取、解釋和視覺化。罕見的事件被揭露。數據科學家和領域專家之間的密切合作實現了首次成功識別優化潛力。複雜的算法通常是不必要的。但是，探索性數據分析還涉及在離線分析中針對不同用例評估來自機器學習和 AI 的算法。如果現有數據庫中的數據無法表示所需的用例，則要不是安裝新感測器，不然就是要調整測試計劃。

MM-4961_Analytics_Demonstrator_Screenshot_2_2000x1125.jpg

5. 整合進入操作流程

第五步，將針對設備或系統優化的分析和視覺化整合到操作流程中。再次諮詢自動化工程師關於整合到控制系統中的問題。

6：利用相關性和優化潛力

在 第六步 中，客戶利用定制分析解決方案的優勢利用相互關係和優化潛力。如有必要，可以在下一個用例的進一步迭代中擴充分析解決方案。

MM-4961_Analytics_Demonstrator_Screenshot_3_2000x1125.jpg

工業整合分析

從數據採集到數據分析

常見問題解答 – Analytics

Analytics 提供的潛力是巨大的。常見應用包括優化控制變量、減少停機時間以及最小化品質和過程波動。透過量身定制的方法，我們幫助您挖掘優化潛力並提高流程的有效性。數據分析還可用於執行新的商業模式。

透過合作，我們開發了一個解決方案來整合現有的數據庫。可以使用所有相關的協定和介面。如有必要，WAGO 可提供用於安裝附加感測器的全面產品組合。

數據採集和記錄是分析案件的一部分。因此，您可以在沒有現有數據庫的情況下啟動案件。如果您已經有數據，它將被整合到評估中。如果您的問題的解決方案需要精確檢測罕見事件，則通常需要更長的數據收集週期。目的是生成有用的各種數據。隨著數據量的增加，數據分析的精度也隨之提高。

根據應用，本地解決方案（集中式解決方案）或許是可能的。

我們提供單獨的儀表板和報告功能，以幫助您密切關注您的分析應用並自行執行分析。

經過驗證的方法範圍很廣。根據用例，可以使用有監督或無監督的學習算法。還使用了整合專家知識的架構於模型的方法。對於某些用例，實時數據的視覺化也可以增加價值。

在第一步中，將注意力集中在您認為有優化潛力的系統部分是有意義的。在結果成功整合到您的流程中之後，可以識別和處理下一個用例。
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