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Smart Manufacturing & AIoT Digital Transformation Journey
- 1. Smart Manufacturing & AIoT Daniel Li IoT Device Experience A Digital Transformation Journey
- 3. AGENDA
- 4. A Digital Transformation Story
- 5. Open source support beyond your imagination Applications Infrastructure Management Databases and middleware App frameworks and tools DevOps
- 7. Connected chillers are back online 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%
- 9. Cloud Globally available, unlimited compute resources Waves of Innovation IoT Harnessing signals from sensors and devices, managed centrally by the cloud Edge Intelligence offloaded from the cloud to IoT devices AI Breakthrough intelligence capabilities, in the cloud and at the edge
- 11. 68
- 12. Intelligent Edge High-speed data processing, analytics and shorter response times are more essential than ever. Intelligent Cloud • Business agility and scalability: unlimited computing power available on demand. Intelligent Edge • Can handle priority-one tasks locally even without cloud connection. • Can handle generated data that is too large to pull rapidly from the cloud. • Enables real-time processing through intelligence in or near to local devices. • Flexibility to accommodate data privacy related requirements.
- 14. AGENDA
- 15. Industry Challenges We Learned
- 16. Manufacturers expect big gains from Smart Factories
- 17. Digital transformation is real – and it’s happening now 83% of manufacturers said that selling products as services increases profits 72% of field service organizations treat service as a profit center Create service- based business models 40% of industrial manufacturers use digital technologies to monitor products sold to customers 73% of manufacturing executive are launching IoT initiative in 20171 Enhance the customer experience 80% of manufacturers expect that improved factory connectivity will help them increase output levels 35% of manufacturers currently collect and use data generated by smart sensors to enhance manufacturing Innovate faster 1. Source: State of the Market: Internet of Things 2017, Verizon
- 18. CRM SRM ERP … Process interoperability (IT)Information Flow (OT) Collaborative equipment Ecosystem Interaction Mixed/Augmented Reality Simulation Industrial IoT Cloud 3D Printing Big Data and Analytics Vertical integration | Horizontal integration | End-to-end engineering Industry 4.0 Design Principles Industry 4.0 Machine Learning Autonomous Robots Cybersecurity BlockChain
- 19. IoT tangible results … moving to SMB soon Gathers data from sensors and systems to create valuable business intelligence and reduce downtime by 50% Cutting fuel usage by 1% could save $250,000 per plane per year Chillers now run 9x faster than unconnected equipment, avoiding more than $300,000 in hourly downtime costs Improves access to production and supply chain data worldwide, reducing downtime costs by as much as $300,000 per day
- 20. Connecting and controlling devices Device Registry/Management Collecting and managing data Stream Analytics External Data Sources Transforming real-time data to business insights Gateway Delivering insights to decision makers Performing advanced analytics Data Mash Ups Data Factory IoT agent Event Hubs & Service Bus IoT Hub Data Storage SQL DB Table / Blob Storage Business Intelligence Power BI Azure Websites Mobile Services Predictive Maintenance Event Analysis Generate Prediction Models Prediction Models Training Models Machine Learning (Azure ML) HDInsight (Hadoop) ML Studio External Services Local Technician Remote Expert Azure Service Bus HoloLens OS LOB Systems of Record MESERP
- 21. Service Ticket History (CRM) Other CAD Systems Long Distance Engine ? More Aluminum? Carbon Fiber Parts ? Placeholder Placeholder Placeholder Connected Product Innovation Short Range Engine Short Range Training Understand exactly how products are performing in the field 1 FLIGHT DATA Investigate issues and redesign as necessary 4 Anticipate new use cases and optimize product performance 5 Change Requests IoT Trends Service Ticket History (CRM) 010101001001010101001001 010100100101010100100100DIGITALSTREAM Engineer / Design Change 010101001001010 010100100101010DIGITAL STREAM Idea Management Center FACTORIES PRODUCING FUEL PUMP FACTORIES PRODUCING FUEL PUMP USA GERMANY Engineering RequestsSupplier Investigations Vendor Change Request Sales/Service Campaigns Combine product data across all relevant sources 2 Run simulations to predict performance issues and identify opportunities for improvement 3
- 22. Service Ticket History (CRM) Other CAD Systems Long Distance Engine ? More Aluminum? Carbon Fiber Parts ? Placeholder Placeholder Placeholder Connected Product Innovation Short Range Engine Short Range Training Understand exactly how products are performing in the field • Know how frequently the product is being used • Find usage and failure rates for specific parts or features • Discover 360°view of product performance compared to design 1 FLIGHT DATA Investigate issues and redesign as necessary • Resolve instances of over- and under-engineering to optimize product performance/cost ratio • Design different product configurations to better fit usage patterns • Support redesign of areas with regular failures • Manage vendor lists and track standard performance across suppliers 4Anticipate new use cases and optimize product performance • Save time and money by combining preventative maintenance with replacement of redesigned parts • Refine products to fit stakeholder needs at product launch and throughout the product lifecycle • Design new products lines and offer new services, like training, based on product insights 5 IoT Trends Service Ticket History (CRM) Power BI Embedded within ISV XXX Cortana Intelligence Suite Change Requests Develop new streams of revenue, like new product models, lines and services Coordinate one-off changes and preventative repairs with existing maintenance schedules Give technicians detailed repair walk-throughs using wearables and augmented reality Improve collaboration and design with wearables and augmented reality Streamline cross-org communication and automate regular handoffs between departments Visualize data from PLM and CAD systems in a unified view CAD on Azure Big Compute Connected Product Innovation Connected Field Service Hololens Azure IoT Acceleration Solutions 010101001001010101001001 010100100101010100100100DIGITALSTREAM Vendor Change Request Engineer / Design Change 010101001001010 010100100101010DIGITAL STREAM Sales/Service Campaigns Idea Management Center FACTORIES PRODUCING FUEL PUMP FACTORIES PRODUCING FUEL PUMP USA GERMANY Power BI Cortana Intelligence Suite Engineering RequestsSupplier Investigations Hololens Combine product data across all relevant sources • Aggregate data from silos such as maintenance records, design specifications, and diagnostics • Analyze data across vendors, part specifications, and other external sources • Integrate stakeholder feedback on existing and suggested features for 360°view of customer 2 Predict disruptive events and identify opportunities • Collaborate across teams and geographies with product- focused tools • Determine if products meet design benchmarks • Compare quality of variants using data-driven analysis to guide design changes 3 Product Insights Azure Data Lake Connected Product Innovation
- 23. IoT projects are complex New skill sets Time-consuming setup and integration Heavy up-front investment
- 24. Smart Manufacturing Reference Architecture Field Gateway IoT Hub Data Ingestion Device Registry Device Management HTTP/s, AMQP, MQTT Microsoft Azure Office365NUI PowerBI Enterprise Business Systems PLM ERP MES CRM Stream Analytics HD Insight Machine Learning SQLTable/Blob Storage { } DocumentDB Data Lake ID Devices Sensors Field Gateway OPC Publisher SCM Event Hub Data Catalog Data Factory Information Management Big Data Storage Azure Biztalk Logic Apps Analytics and Machine Learning Business Integration and Gateways Visualization
- 25. User experiences Dashboards Mixed Reality 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 (OT) Enterprise business processes PLM ERP SCM MESCRM Home EdgeAnalyticsDeviceAgent StreamAnalytics onedge Logic Apps API integration BizTalk Services Azure StackSQL Server 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
- 26. User experiences Dashboards Mixed Reality Interactive speech Gestures Preconfigured Azure IoT Suite and SaaS applications Remote monitoring Predictive maintenance Connected factory Microsoft IoT Central1 Analytics and artificial intelligence HDInsight Machine Learning Data Lake Analytics Azure Time Series Insights Bot Framework Operations Technology (OT) Enterprise business processes PLM ERP SCM MESCRM Home Logic Apps API integration BizTalk Services Azure StackSQL Server 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 StreamAnalytics onedge DeviceAgent
- 27. User experiences Dashboards Mixed Reality Interactive speech Gestures Preconfigured Azure IoT Suite and SaaS applications Remote monitoring Predictive maintenance Connected factory Microsoft IoT Central1 Analytics and artificial intelligence HDInsight Machine Learning Data Lake Analytics Azure Time Series Insights Bot Framework Operations Technology (OT) Enterprise business processes PLM ERP SCM MESCRM Home Logic Apps API integration BizTalk Services Azure StackSQL Server 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 StreamAnalytics onedge DeviceAgent
- 28. Microsoft’s IoT portfolio Microsoft’s vision is to democratize IoT by allowing everyone to access the benefits of IoT and provide the foundation for digital transformation Fully managed SaaS Best used when you need to get started quickly with minimal IoT experience Microsoft IoT Central Securely distribute cloud intelligence locally, quickly, and at scale Hybrid – Edge Analytics Azure IoT Edge + Customizable PaaS Best used when you need a lot of control over your IoT solution Azure IoT Suite
- 29. Azure IoT Acceleration Solutions Easily ingest data and create command & control responses Analyze incoming data via stream processing and machine learning Integrate with existing business systems and automate workflows Leverage PowerBI for rich dashboards and visualization Deploy quickly with preconfigured Solutions Predictive Maintenance Remote Monitoring v2 Securely connect to and manage devices and gateways Connected Factory
- 30. A new preconfigured solution to connect your OPC UA and OPC Classic devices to Azure to: • Monitor factory, production lines, station OEE, and KPI values • Analyze the telemetry data generated from these devices using Azure Time Series Insights • Act on alerts to fix issues Connected Factory Solution IoT Hub VM Linux VM (with multiple assembly lines) Web App hosting Solution Dashboard & OPC UA Client OPC UA Server OPC UA Server OPC UA Server Gateway SDK with OPC Proxy & OPC Publisher Modules MES Simulation (OPC UA Client) Telemetry path Command & Control path Time Series Insights
- 31. Designed for IoT Connect up to 10 million devices Cloud-scale messaging Device-to-cloud and Cloud-to-device Durable messages (at least once semantics) Per-device authentication Individual device identities and credentials Multi-protocol support Natively supports AMQP, HTTP, MQTT Designed for extensibility to custom protocols Service assisted communications Secure bi-directional communication Command and control Cloud-facing telemetry ingestion Delivery receipts, expired messages Device communication errors Connection multiplexing Single device-cloud connection for all communications (C2D, D2C) Multi-platform Device SDKs available for multiple platforms (e.g. RTOS, Linux, Windows) Multi-platform Service SDK
- 32. Azure IoT Edge • Low-latency (important in safety scenarios, such as stop the machine immediately) • Intermittent connectivity (remote mining, oil, factories) • Integrate sensor data from different devices • Filter or aggregate telemetry data before sending it to the cloud • Transform raw input from sensors to meaningful information On Premise Azure IoT Edge Devices RTOS,Linux,Windows, Android,iOS Stream Analytics Custom OPC UA or Modbus ingestion module Azure Functions Machine Learning Cognitive Services Container Management Functions Runtime Device Twin Local Storage IoT Hub Device Twin Stream Analytics Machine Learning Power BI
- 33. • Moxa • Softing • Unified Automation • Hewlett Packard Enterprise • Kepware • Beckhoff • Advantech • Nexcom • Prosys OPC • Matrikon • Kontron • Hilscher Azure IoT Edge Industrial Gateway Program
- 34. Platform independent Protocol independent Information model Encryption, Validation & Authentication Open Source
- 35. Brownfield Enabled <$500 + No changes to machines required! Consistent, compatible data model for all machines, plus security! No compatibility! No winner in the field bus/industrial ethernet wars!
- 36. OPC Publisher Device Connectivity & Management Analytics & Operationalized Insights Presentation & Business Connectivity IndustrialDevices (OPCandOPCUAServers) Hot Path Analytics Azure Stream Analytics, Azure Storm Presentation & Business Connections Websites, Mobile Services Dynamics, BizTalk Services, Notification Hubs Cloud Gateway IoT Hub Field Gateway OPC API & Client Hot Path Business Logic Service Fabric & Actor Framework Azure IoT Accelerator Solutions Supports OPC UA
- 37. Azure Time Series Insights (提供強大時序資料處理能力)Devices Storage • IoT SCALE TIME-SERIES DATA STORE Schema-less store, just send data Easy IoT Hub connection Store, query and visualize billions of events Simple and fast navigation
- 38. Combine human and digital intelligence Challenge Achieving fine-tuned composition of precision- manufactured parts requires tight control of the tools and processes to ensure consistent quality and reliability; and minimize waste. Strategy Convert the knowledge of service technicians into a digital format and apply machine learning to adjust cutting configuration and optimize production. Results • Retrofit machine learning information to automatically adjust equipment and manage tooling inventory • Tool-level intelligence to minimize idle time up to 50% • Improve Customer service level “What sets us apart is our deep knowledge of the machining process and our ability to translate that knowledge into the algorithms used to analyze the data.” — Mats Lindeblad, Global Product Manager Sandvik Coromant
- 40. AGENDA
- 43. Machine Learning addresses a range of scenarios High-yield use cases that transform Manufacturing Supply Chain and Inventory Optimization Predictive Maintenance Anomaly Detection Production Scheduling Demand Forecasting Quality Assurance
- 46. Presentation & Action Storage & Batch Analysis Stream Analytics Event Queuing & Stream Ingestion Event production IoT Hubs Archiving for long term storage/ batch analytics Real-time dashboard Stream Analytics Machine Learning Blobs Devices & Gateways Azure IoT Streaming Pipeline PowerBI Blobs
- 47. Azure IoT Edge • Low-latency (important in safety scenarios, such as stop the machine immediately) • Intermittent connectivity (remote mining, oil, factories) • Integrate sensor data from different devices • Filter or aggregate telemetry data before sending it to the cloud • Transform raw input from sensors to meaningful information On Premise Azure IoT Edge Devices RTOS,Linux,Windows, Android,iOS Stream Analytics Custom OPC UA or Modbus ingestion module Azure Functions Machine Learning Cognitive Services Container Management Functions Runtime Device Twin Local Storage IoT Hub Device Twin Stream Analytics Machine Learning Power BI
- 50. 5050
- 51. The industry’s most comprehensive portfolio Azure IoT Suite (PaaS) Preconfigured solutions for common IoT scenarios Data and Analytics Azure Time Series Insights Azure Machine Learning Cosmos DB Azure Stream Analytics Azure Data Lake Azure Data Lake Analytics Azure HD Insight Visualization and Integration Azure Logic Apps Notification Hubs Azure Websites Microsoft Flow Microsoft Power BI Azure Monitor Azure Active Directory Device support Azure IoT Device SDK Azure IoT certified devices Security Program for Azure IoT Windows 10 IoT IoT Edge Azure IoT Hub Azure IoT Edge IoT Hub Device Provisioning Service Microsoft Dynamics Connected Field Service Microsoft IoT Central IoT SaaS Solutions (PaaS) Technologies (PaaS) Solutions (SaaS)
- 52. Building an IoT Solution ActionsThings Insights
- 53. © 2017 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.