Verification & Validation in the Age of Systems Engineering

Transcription

1 Verification & Validation in the Age of Systems Engineering STAR Global Conference Prague Realize innovation. Willy Bakkers C.E.O. Samtech S.A.; Vice President, Head of 3D Simulation Siemens DF-PL-STS-3D

2 Divisions Go-to-market Siemens One of the world s largest industrial enterprises Customer Digital Factory Division Factory Automation Americas Control Products Product Lifecycle Management Middle Europe, East, CIS 1) Africa Market Motion Control Asia, Australia ecar Powertrain Systems Global Healthcare Separately managed Power and Gas Wind Power and Renewables Energy Management Building Mobility Technologies Customer Services Digital Factory Process Industries and Drives Health-care Financial Services PG WP Power Generation Services PS EM BT MO DF PD HC SFS Managing Board Corporate Services Integrated product portfolio paves the way for the Digital Enterprise. Corporate Core Page 2 1) CIS: Commonwealth of Independent States

3 The integration of product development, simulation and validation is now at the top of our agenda. Anton Huber, CEO Siemens Digital Factory Page 3

4 We are investing heavily in CAE for multi-disciplinary analysis throughout the product definition cycle. Chuck Grindstaff, CEO Page 4

5 It is not the strongest of the species that survives, nor the most intelligent, but the one MOST ADAPTABLE TO CHANGE [Charles Darwin, 1809] Page 5

6 YOUR CAE DEPARTMENT WILL ONLY REMAIN RELEVANT IN THE FUTURE IF ITS ABLE Change is Happening As close to reality as possible Cover all critical performance characteristics Evolve over time to remain in-sync with the product and its operating environment TO ACCURATELY MODEL SYSTEMS BEHAVIOR WITH DIGITAL TWINS THAT ARE BECOME PREDICTIVE AND DRIVE DESIGN DECISIONS Use analytics to deliver new insights Provide results in time with the design cycle Page 6

7 Product & technology evolution From products dominated by the mechanical components. to Smart Systems integrating mechanical, electrical, controls Page 7

8 Product & technology evolution From known material and production methods to mixed materials, novel production methods e.g. additive manufacturing Page 8

9 Product & technology evolution From defined options From defined options... to personalized... to mass customization and personalization Page 9

10 Product & technology evolution From internet connectivity to system of systems and internet of things Page 10

11 One constant Addressing these engineering challenges without compromising time, quality, and cost Page 11

12 YOUR CAE DEPARTMENT WILL ONLY REMAIN RELEVANT IN THE FUTURE IF ITS ABLE Product Engineering must evolve TO ACCURATELY MODEL SYSTEMS BEHAVIOR WITH DIGITAL TWINS THAT ARE As close to reality as possible Cover all critical performance characteristics Evolve over time to remain in-sync with the product and its operating environment BECOME PREDICTIVE AND DRIVE DESIGN DECISIONS Use analytics to deliver new insights Provide results in time with the design cycle Page 12

13 Evolution of product engineering Product Representation Drafting Digital Mock-up System Mock-up Richer Performance Verification Physical Test CAE & Test Predictive Digital Twin Requirements Ad-hoc Managed Integrated Page 13

14 Siemens PLM Simulation & Test Solutions Enabling Closed Loop System Driven Product Development LMS Imagine.Lab LMS Test.Lab 1D Behavioral Simulation Virtual to Physical LMS CAESAM NX CAE, NX Nastran Fibersim 3D CAE LMS Real-Time Simulation LMS Virtual.Lab LMS Samtech Suite Page 14 Scalable 1D - 3D Simulation & Test Incl. Real-Time for MIL-SIL-HIL and Simulators Engaging with Engineering Services in manufacturers product development practices

15 Example: Rolls-Royce LMS Imagine.Lab: Optimize System Integration Performance Achieving a robust design, considering airframe integration Modeling of pump, engine and hydraulic lines Hydraulic loading test profile Surge, cavitation & pressure peaks Modifications & validation with test Improving performance and reliability at the system level Reduce the 150 hours engine type test for validation of engine maturity Solve integration challenges between engine, hydraulic pumps and aircraft loading LMS Imagine.Lab Amesim and LMS Imagine.Lab Engineering services The modeling has helped us identify the best way to go forward. We are certainly ahead of the game in specifying a new, more robust hydraulic system. Adam Harris, technical project manager at Rolls-Royce Page 15

16 Example: Daimler Mercedes LMS Virtual.Lab Motion: Scalable Mechatronic Simulation - Off-line and Real-Time Off-line Simulation Real-Time Simulation Optimizing Vehicle Design for Driving Pleasure Ride and Handling, Comfort, Durability Interaction with vehicle body controls (ESP, ABS, ) Frontloading Controls development (1) Vehicle Design Optimization Handling Ride&Comfort- Durability (2) Frontload Controls Engineering Body Controls Active Safety For ride & handling, LMS Virtual.Lab Motion is a powerful development tool. It is our ambition to use the LMS Virtual.Lab for Hardware-in-the-Loop (Real Time), allowing to use the same vehicle models across simulation. Prof. Ludger Dragon, Senior Manager Vehicle Dynamics Integration Division, Daimler Page 16

17 Example: Siemens NX CAE, NX-NASTRAN and Samcef: Integrated Topology Optimization process Topology Optimization enabled within NX CAE NX Nastran and LMS Technology High Power Density Electrical Motor Maximize Mechanical Output Power Minimize Structural Weight Manage Thermal Build-in System Redundancy Make Scalable Design 10.5 kg 4,6 kw/kg 4.1 kg 5,2 kw/kg simulation solutions enabled the development of this world-record electric motor. Dr. Frank Anton, Head of Electric Aircraft Unit at Siemens Corporate Technology Page 17

18 Source: Example: Airbus LMS Test.Lab: Critical Dynamics Testing to Validate and Improve Simulation Execute mission critical Ground Vibration Test (GVT) Accelerate Aircraft Certification Flight Flutter Testing We ve been extremely impressed by the way that the LMS Test.Lab software can handle the immense amount of Airbus A380 in-flight data. - Jean Roubertier, Aeroelasticity expert at the Flight tests department - Airbus Page 18

19 Till facts be grouped and called there can be no prediction Charles Darwin Species Notebook Page 19

20 From disconnected models and data TEST MODELING Analysis data Test data 3D SIMULATION CONTROLS Benchmark data 1D SIMULATION Usage data Page 20

21 To the Digital Twin TEST MODELING Analysis data Test data 3D SIMULATION CONTROLS Benchmark data 1D SIMULATION Usage data Page 21

22 enabling Predictive Engineering Analytics TEST MODELING Analysis data Test data 3D SIMULATION CONTROLS Benchmark data 1D SIMULATION Usage data Analytics Page 22

23 Siemens PLM Simulation & Test Solutions Verification & Validation in the Age of Systems Engineering SYSTEMS DRIVEN PRODUCT DEVELOPMENT SYSTEM MOCK-UP PREDICTIVE ENGINEERING ANALYTICS 3D TEST CONTROLS Digital twin 1D ANALYTICS - REPORTING VERIFICATION & VALIDATION MULTI-DOMAIN TRACEABILITY, CHANGE AND CONFIGURATION Page 23

24 Verification & Validation in the Age of Systems Driven Product Development Enabling Predictive Engineering Analytics Predictive Engineering Analytics enables a move from verification to prediction Deliver multi-fidelity system models that are as close to reality as possible for each stage of development Cover all critical performance characteristics to be addressed by integrating different simulation disciplines Evolve models over time to remain in-sync with the product and its operating environment Apply analytics combined with performance data to deliver new insights faster and with more confidence Page 24

25 Verification & Validation in the Age of Systems Engineering STAR Global Conference Prague Willy Bakkers C.E.O. Samtech S.A. Vice President, Head of 3D Simulation Siemens DF-PL-STS-3D Siemens Industry Software NV Interleuvenlaan 68, 3001 Leuven - Belgium Thank You Realize innovation. Phone: Mobile: willy.bakkers@siemens.com siemens.com Page 25