The Place for Digital Twins in Supply Chain Management

Transcription

1 The Place for Digital Twins in Supply Chain Management Brian Williams, Industry Advisor, EMEA South SAP and SAP Partner Use Only

2 Agenda What is a Digital Twin? Supply Chain Dynamics with Digital Twins s in the New Digital Supply Chain SAP Leonardo: Your Intelligent Management Portfolio Thank You! 2

3 What is a Digital Twin?

4 Digital Twin Defined Digital twin Data Info Physical asset in real space Virtual asset in virtual space 4

5 End to End Value Across the Lifecycle of the Digital Twin Questionnaire & Checklist Improvement Request Spare Part Ordering Automatic Onboarding & Topology Detection Service Ticket Health & Key Indicators Work Orders & PM Notifications 2D Sensor Chart and Alert List 3D Repair Instructions Failure Mode based Predictions Error Codes and Knowledge Base 5

6 Jumpers Flow Induced Vibration of Jumpers due to internal and external flow would lead to fatigue and possible failure Stream the wave/current data as well as internal flow to the digital twin and calculate/update remaining life live Plan for inspection/maintenance accordingly 6

7 Erosion Stream flowrate going through equipment to Digital twin Calculate erosion and remaining life of equipment Manage operation/schedule maintenance accordingly Eroded Tools Failed Tool 7

8 Supply Chain Dynamics with Digital Twins

9 The Physical and the Digital Twin Full digital representation of connected assets along their lifecycle delivering an embedded, collaborative and real-time set of next generation processes and systems Physical Digital Twin 9

10 Digital Supply Chain Design to Operate s s s Manufacturers Manufacturers Logistics Logistics 10

11 New Business Models Share Information and Collaborate The new ecosystems and business network enables new business models to buy and sell digital services such as content packages, premium services, firmware updates and specialized asset-specific applications on top. Manufacturers (OEM) Engineering & Construction Service Provider Operator (Owner) From Selling equipment To Pay per use / equipment as a Service Untrusted asset information Collaborative Single source of truth Limited analytical capabilities Real time analytics with simulation Reactive maintenance Prescriptive maintenance 11

12 12

13 s in the New Digital Supply Chain

14 Technology Enablers for Intelligent Management The Internet of Things (IoT) Artificial intelligence and machine learning Real-time engineering simulation 3D visualization and augmented reality Provides sensor-enabled condition monitoring for real time insights and new valueadded services Bring unprecedented insights and automation of knowledge work across the enterprise Use physics-based digital twins for predictive engineering analysis in product development and operations Provides unmatched situational awareness and enhanced perception for better decision making 14

15 Intelligent Management Vision and Objectives s s s Support manufacturers and asset operators in defining, planning and monitoring the optimal service and maintenance strategy for physical products and assets by providing the required level of collaboration, integration and analytical insights. Manufacturers Manufacturers Logistics Logistics 15

16 Product and Lifecycle and the Digital Twin Operator Manufacturer Products & s Intelligence Management, Predictive Maintenance and Service Predictive Engineering Insights As Operated Strategic Partnership with Product Intelligence Collaborative R&D, Engineering and Manufacturing 16

17 Intelligent Management Central as One Common Data Set Central One Common Data Set Central Connect to s Central, SAP s digital twin for physical assets, is the foundation layer across the SAP portfolio. 17

18 18

19 SAP Leonardo: Your Intelligent Management Portfolio

20 SAP Intelligent Management Portfolio Business Capabilities State-of-the-art business processes Leverage new technologies to enable new asset management business processes anywhere and anytime Real-time insights End-to-end visibility on strategic, tactical and operational level Connected assets Bring together information from operational and business systems using IoT for scalable transparency Network and Collaboration Strategy and Performance Health Prediction and Optimization The power of prediction, optimization and simulation Drive smarter decisions, improve reliability, and reduce outages Maintenance and Service Management SAP S/4HANA SAP Leonardo IoT Collaboration throughout the asset lifecycle Share asset information, access one version of the truth, and collaborate on a cloud-based business network with integrated processes 20

21 SAP Intelligent Management S/4HANA for Maintenance and Service Management Strategy and Performance Network and Collaboration Health Prediction and Optimization Maintenance and Service Management Plan maintenance activities with the right person providing the appropriate tools and resources SAP S/4HANA SAP Leonardo IoT Schedule proactive preventive or condition-based maintenance tasks Leverage integrated documentation for job execution and safety for a holistic view of asset status 21

22 SAP Intelligent Management SAP S/4HANA for Maintenance and Service Management Execution (Scheduling- and Geospatial Optimization) Execute planned and unplanned maintenance tasks to help ensure optimal operations Network and Collaboration Strategy and Performance Maintenance and Service Management SAP S/4HANA SAP Leonardo IoT Health Prediction and Optimization Manage preventive and condition-based maintenance proactively Increase equipment reliability and improve asset usage as well as safer maintenance processes Manage asset information for work orders, maintenance, measurements, inspections, metering, and inventory 22

23 SAP Intelligent Management Intelligence Network (AIN) Strategy and Performance Enable secure asset information collaboration across your business network Network and Collaboration Maintenance and Service Management SAP S/4HANA SAP Leonardo IoT Health Prediction and Optimization Collaborate with manufacturers, operators, service suppliers, across the network on asset information Provide one network channel for electronic handover of technical asset and maintenance data to OEMs, service providers, and procurement vendors Improve data reliability, reduce master data maintenance, and maintain higher asset availability 23

24 SAP Intelligent Management Strategy and Performance Management (ASPM) Segment assets based on risk, criticality, impact, and environmental factors to determine best maintenance strategies at lowest cost and risk Network and Collaboration Strategy and Performance Maintenance and Service Management SAP S/4HANA SAP Leonardo IoT Health Prediction and Optimization Adopt Reliability Centered Maintenance processes, considering failure modes, effect and root causes Manage performance to optimize return on assets across lifecycles. Monitor, review, and improve maintenance plans and budgets Reduce bottlenecks, improve decision making, and prevent incidents using a holistic view of asset types and maintenance strategies 24

25 SAP Intelligent Management Health Prediction and Optimization Predictive Maintenance & Service (PdMS) and Predictive Engineering Insights (PEI) Optimize the availability of your assets by using predictive maintenance and service capabilities and the Internet of Things to take corrective actions early Network and Collaboration Strategy and Performance Maintenance and Service Management SAP S/4HANA SAP Leonardo IoT Health Prediction and Optimization Collect and analyze sensor data from physical assets to predict operational failure Initiate preventive countermeasures that trigger service or maintenance orders Optimize asset performance with a closed-loop maintenance and service process Create physics-based digital twins of industrial assets based on a real-time and predictive engineering analysis 25

26 SAP Intelligent Management Mobile Management Strategy and Performance Network and Collaboration Health Prediction and Optimization Eliminate paperwork while reducing downtime and maintenance backlog Maintenance and Service Management SAP S/4HANA SAP Leonardo IoT Extend and improve asset life and reliability by shortening work cycles Turn capital spending into operational investments using cloud deployment Manage existing work and asset data whether you re online, offline, or occasionally connected 26

27 Failure-Mode-Specific Health Monitoring The power of integrated ASPM, PdMS & PEI Common Data Model Failure Modes Detection Method Machine Learning Engine Machine Data Business Data Equipment Class Pump Subclass rust flex winding deterioration erosion visual inspection structural integrity threshold-based forecasting anomaly based failure prediction Health Indicator PdMS Algorithms for Anomaly Detection PdMS Algorithms for Failure Prediction PEI Simulation Customer-specific R Algorithms Image classification by Deep Learning Model Management Scheduling Data Preprocessing Extensibility Common Business Data & Processes Predictive Maintenance, Maintenance Planning, Monitoring 27

28 28

29 Thank you. Brian Williams ENR Industry Advisor SAP EMEA South Cell: