Focus: Digital Twin
Engineering of the Future
Digital Twin FUTURE PLM TRENDS IN ENGINEERING Digital Twin IoT The - - PowerPoint PPT Presentation
Engineering of the Future Focus: Digital Twin FUTURE PLM TRENDS IN ENGINEERING Digital Twin IoT The Digital Twin closes the circle from reality back to engineering (and within engineering), enabling deeper insights faster and helping to
Engineering of the Future
FUTURE PLM – TRENDS IN ENGINEERING
The conception and realization of complex systems requires an interdisciplinary System Engineering approach with a close interlocking of mechanics, electrics/electronics and software.
CASE PLM CAE MES … … ALM CAD ERP DMS
PLM Integration
Collaborative Systems Engineering
Data Lake
The integration of heterogeneous PLM landscapes (incl. cloud) and associated data is an important enabler for the further automation and digitization of business processes. Transparent access via Semantic Networks to all relevant data, distributed across an increasingly complex IT landscape, is becoming a key factor.
Sales/ AS. Cockpit Engineering Cockpit Manufact. Cockpit
New user interfaces in the form of Role-specific Cockpits offer innovative display and access options to all relevant information.
From mechanical products Via cyber-physical systems
The Digital Twin closes the circle from reality back to engineering (and within engineering), enabling deeper insights faster and helping to improve product development.
IoT
AI& Analytics
To Digital Twin
Digital Twin Digital Twin
Engineering of the Future
A DIGITAL TWIN is a digital representation of a physical product OR PROCESS over its lifecycle
Properties and behavior of the physical twin can be visualized, analyzed, predicted and adapted. The digital Twin leverages sensors and connectivity in addition to previous digital models.
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Product engineering (3d models, BOM,
configuration, test, …)
Production
(factory layout, machines, material, production date, ….)
Sales
(sales configuration, service manual, …)
Aftersales / Service
(maintenance, complaints, repair instruction, …) Backend
Field Use / Operations
(„What happens with my product / process?“)
Data lakes Sensor data
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Dark side of the Moon – What happens with my product or Process?
Tesla issues its largest recall ever, voluntarily, over faulty Model S steering 123,000 vehicles built before April 2016 are affected By Zac Estrada@zacestrada Mar 29, 2018, 6:00pm EDT In the email, Tesla said it had, “observed excessive corrosion in the power steering bolts,” but that the problem was most prevalent in colder climates where road salt is used.
Quelle: Internet-Recherche
Exemplary Motivation for a digital twin: Product recalls
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Product engineering (3d models, BOM,
configuration, test, …)
Production
(factory layout, machines, material, production date, ….)
Sales
(sales configuration, service manual, …)
Aftersales / Service
(maintenance, complaints, repair instruction, …) Backend
Field Use/ Operations
(„I get systematic and digitized feedback.”)
Data lakes Sensor data
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DigitaL Twin Digital Twin
Getting data-driven insights faster with the DIGITAL TWIN
(„I develop products more efficiently.”)
Physisches Produkt
Digital Twin
Sensor information for status and behaviour
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The PLM Digital Twin demonstrator shows the intelligent analysis of sensor
analytic methods allow the automatic detection of deviations compared to „normal“ product behavior (so called anomalies) that can be visualized in a dashboard. Through the analysis of real brake system data (e.g. gained during product testing) security critical indications can be utilized directly in engineering in order to realize important product quality improvements at the earliest possible stage.
The PLM Digital Twin AR Experience based on the PTC Vuforia solution offers an innovative way for displaying specific
elements can be switched on/ off via toggles:
▪ CAD drawings ▪ Sensor values ▪ Additional data from diverse backend systems (e.g. WindChill, SAP) ▪ Further videos for further explanation
▪ Live physical sensor values ▪ NEW: virtual sensor values ▪ CAD models ▪ Data from backend systems ▪ Additional videos
OEM test drive OES engineering
Data sharing of relevant data Data gathering Data enhancement Data handling
Improvement of product quality Acceleration of development Simplification of simulation and testing
Data Intelligence Hub
marketplace for secure data exchange, processing and analyzing
UC 1.1 … Assisted/automated product documentation … UC 1.x UC 2.1 … Virtual sensors … UC 2.x UC 3.1 … Virtualization of physical tests (e.g. AI-based) … UC 3.x UC n.1 UC n.2
after SOP … UC n.x
Design Simulation Test Bench Test Field
Less over-/under- Engineering More realistic and efficient simulation Increased efficiency and less physical prototype tests Less error follow-up costs
…
Closed-loop for real data Technical enablers: Connectivity, Data Ingest/ Integration, Semantic Web, Big Data infrastructure & algorithms, Analytics& AI, PLM Cloud
…
Product Performance Management Traceable Test Twin (data synchronization and visualization) … UC 4.x
Closed-loop within engineering
Data Twin Simulation/ AI Twin Condition Twin Visual 3D Twin
010010 10001101 1101011Device Connectivity Visualization Platform
Physical World
A sensor or actuator gathering information A network to send the data to the platform An infrastructure to control and distribute all information An application to display all data
Digital Application Interface
Use Case
A plan to realize your way to the digital twin
Analysis
An application to analyze all data
Integration
A solution to leverage all data
Consulting
Cloud Platform Big Data Cluster
Digital Data
Dashboard Artificial Intelligence Analytics VR/ AR Widgets Process Integration System Integration Enterprise Architecture LTE / 5G Device Management Partner network Quick check Inno Workshop Pre Assessment IoT Platform SIM
DEPENDING ON YOUR STARTING POINT WE PROVIDE THE SOLUTIONS YOU NEED
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Enable DO Operate Transform Design scope
▪ Documentation of the actual state (data, assets and processes) ▪ Analysis of processes and data ▪ Definition of processes and modules ▪ Management Summary with recommended actions ▪ Final presentation ▪ Data exploitation ▪ Data preparation and training ▪ Qualified anomalies, predictions, impact factors ▪ Definition of targeted service and maintenance processes ▪ Design of target architecture ▪ Benefit analysis ▪ Transformation plan ▪ Customizing ▪ Implementation ▪ Interface connection ▪ Integration in customer landscape ▪ Rollout and training ▪ Operation (Cloud/ On-premise) ▪ License model ▪ Maintenance ▪ Illustration of new service models
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Q&A Session
Short check for determining the
starting position on the way to digization
Assessment of level of maturity
Lokalization Idea generation
Workshop for collection and
evaluation of innovations for the field of application
Onsite or in T-Systems
Innovation Center
Enable DO Operate Transform Design scope Quickcheck Inno Workshop
Innovation Scope definition
Pre-qualification of the use
cases and the existing information Check
Data Processes IT-Systems
Pre assessment
Orientation
Sascha Leidig Head of PLM Portfolio- und Partnermgnt. Sascha.Leidig@t-systems.com +49 175 2410836 Steffen Maier PLM Portfolio- und Partnermgnt. Steffen.Maier@t-systems.com +49 160 8290415