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IIoT發展趨勢及設備業者因應之_微軟葉怡君
- 1. Cathy Yeh 葉怡君 物聯網亞太創新中心總經理 雲端暨人工智慧研發集團 工業物聯網發展趨勢 及設備業者因應之道
- 2. Agenda • 工業物聯網發展趨勢及微軟策略 • 智慧製造應用實例 •工業物聯網創新商務模式 - 以AOI 雲為例
- 4. IoT is inthe critical path of innovation
- 5. And we knowIndustrial IoT is not Consumer IoT!
- 6. 在創新轉型趨勢之下，全球製造業的現況與挑戰 (一) 產品生命週期縮短 – 客戶需求走向個人化，大量生產 轉為少量多樣 科技加速進步，營運決策大不易– 大數據時代，營運環境快速變動、 決策過程中不確定性、時效以及風 險遽升 產業生態改變及鏈重組– 科技、貿易全球化以及政經局勢 的影響之下促成製造業產業轉型 及產業鏈重組
- 7. 在創新轉型趨勢之下，全球製造業的現況與挑戰 (二) O E E 研發資本投入高，財務風險越 來越高- 各產業對於機台實務應用均有 特定規範與設定，面對產線調 整與設備設定更新曠日廢時難 以跟上產業變化的腳步。 勞力成本節節上升，經驗傳承 成為難題– 勞力成本節節升高，老師傅經 驗卻難以傳承，產業技術人員 出現斷層。 資訊流動緩慢– 公司內部不同事業單位資訊系 統互不相通缺乏整合，新舊系 統無法融合；影響決策速度同 時也難以根據客戶需求變化即 時並且精準備料及調整產線。
- 8. GET INSIGHTS Getting nearreal time insights is difficult and time consuming due to disconnected data across regions and product REDUCING COST Sub-optimal monitoring capabilities prevent manufacturers from reducing the cost of service and remaining competitive NEW REVENUE Uncontrolled costs and risks make it challenging to secure support for creating revenue streams through new innovative services or business models
- 9. Connected chillers are backonline 9x faster than unconnected equipment, avoiding more than $300,000 in hourly downtime costs Data from sensors and systems to create valuable business intelligence and reduce downtime by 50% Reduced its accident rate by 25% and fuel usage by 20%, reporting annual savings of $1.8 million Cut down-time cut for each packaging line by up to 48 hours, saving €30,000 for customers Keeping farmers informed about irrigation, disease control diseases, and pest has led to increased yields of 30%, and a 20% reduction in water use Rolls Royce “power by the hour” model provides maximize availability by cutting fuel consumption by 1% and up to $250,000 per plane, per year. Access to production and supply chain data worldwide, reduced downtime costs by as much as $300,000 per day Licorice extruders on Twizzler’s production line are performing at peak optimization, saving over $500K/year on materials alone Enabled customers to transport more than 1M additional tons of cargo, and reduce fuel consumption by 17%
- 10. 微軟工業物聯網策略 – 結合產業龍頭帶動創新 Enable innovation that matters to the industry on Microsoft and Microsoft partners Digital Twin Smart Manufacturing Asset Management Predictive Maintenance Field Services Quality Assurance Others… Compute, Network, Storage, IoT, Data & AI platform, Security, Open platform Stability/ Quality New business model Capacity planning Minimize unplanned downtime Improve workplace safety Compliance Others…
- 12. 智慧製造數位轉型各大階段 “Pay-as-you-go”, Outcome-based products Products that neverbreak “New business models” Services 7 Digital feedback loops, Functions How can an autonomous response be achieved? “Self-optimizing” Adaptability 6 AI Models, Machine Learning What will happen? “Being prepared” Predictions 5 Time Series Insights, Hierarchical Data Modeling Why is it happening? “Understanding” Transparency 4 Telemetry Dashboards What is happening? “Seeing” Visibility 3 Edge Gateways How to Connect? “Plugging in” Connectivity 2 PLCs/IPCs What Data? “Defining Tags” Computerization 1 Value Time設備聯網 數位化 數據分析可視化 可預測化 自動因應 服務化
- 13. PREDICTIVE ANALYTICS I NFACT O RY OF THE FUTU RE AT JABI L ▪ Improving Quality – Predict downstream defects products in upstream processes and evaluate the impact to production BEFORE they happen – Advanced statistics for early warning detection of quality processes going out of control long before they happen ▪ Equipment Optimization – Machine learning algorithms used for autonomous equipment adjustments and M2M with no operator intervention ▪ Increasing Equipment Uptime – Avoid unplanned downtime by predicting future equipment failures – Optimize maintenance schedules and reduce costs
- 14. • Majans usesZeiss Corona process measurement for failure detection and quality control, which are mounted in-line and checking moisture/salt, and there are only 3 such Zeiss Corona spectrometers in the world. However, the interface to this only speaks OPC DA. • IIoT helped ZEISS to connect OPC DA to OPC UA, and also enabled this at Majans for the real-time streaming of Zeiss Corona process measurement into Azure IoT Hub. The data flow ingests 15 PLC tags/measures to IoT Hub using the OPC UA Publisher, which is running as a native .NET core app on an Omron Industrial PC (IPC). This way we had nodes available via OPC UA to synchronize with the OPC DA tags from the ZEISS OPC Server. • The measurements may be small (just 5 parameters for salt, moisture and 3 more for color) but very important to our customer for establishing quality in their products. Having the capability to do this real-time is a big achievement for this industry (versus a QA/QC sampling lab). Majans – Quality Assurance
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- 18. User experiences Dashboards MixedReality Interactive speech Gestures Preconfigured Azure IoT Suite and SaaS applications Remote monitoring Predictive maintenance Connected factory Microsoft IoT Central Analytics and artificial intelligence HDInsight Machine Learning Data Lake Analytics Azure Time Series Insights Bot Framework Operations Technology Enterprise business processes PLM ERP SCMCRM Home IT architecture EdgeAnalyticsDeviceAgent StreamAnalytics onedge Logic Apps API integration BizTalk Services Azure StackSQL Server MES & Enterprise IT Business integration Hot path analytics and application platform Cold path analytics and storage Stream Analytics Event Hubs Service Fabric (Actors) Functions Data Factory DocumentDB SQL Database Data Lake Store Field Gateway Cloud Gateway Azure IoT Gateway Azure IoT Hub (device provisioning) Cognitive Services L3: Mfg Ops Mgmt, MES, CAD, PLM L2: Supervisory Control, SCADA, HMI L1: Plant Control PLC, DCS, IPC L0: Physical Equipment, I/O, Devices, Sensors L4: Business Planning
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- 21. 從機械雲, 檢測雲到智慧製造 Microsoft’s Infrastructure& Data Platform 開放整合的數據平台 (Open, Common Data Model concept) 新舊機台聯網 Connect your “Things” (Greenfield or Brownfield) 快速部署各場域應用 Onboard/ Off board “Use Cases” Predictive Maintenance 預保維修 CAD/CAM 加工模擬管理 CNC Calibration 機台校正 AI for QA 瑕疵檢測 OEE 產能優化
- 22. Recognition: Microsoft isrecognized as the first to… Microsoft is a leader in the Forrester Wave for IoT Software Platforms Microsoft is a Leader in the IDC MarketScape for IoT platforms across various use cases Microsoft is a leader in the Research Leaderboard assessment of strategy and execution for 15 IoT platform providers Azure IoT is the only cloud platform that was determined as best in class in every category • Deliver IoT solution accelerators | SaaS and PaaS for IoT | AA/AI at the edge • Solve device provisioning at scale | Support OPC UA for manufacturing