The value of being right has never been greater

© 2014 IBM Corporation

Closing the gap between Systems level Modeling and Physical simulation in Model Based Systems EngineeringPresentation Number: M-12

Amit FisherProgram Director, Systems Technical Client Relationship ManagerIBM Software Group, RationalEmail: [email protected]


Software and Systems Engineering | Rational

Galaxy S - 20 million unitsGalaxy S II - 40 million unitsGalaxy S III - 50 million unitsSamsung Galaxy S IV sales expected to pass 100 million

Galaxy S - 20 million unitsGalaxy S II - 40 million unitsGalaxy S III - 50 million unitsSamsung Galaxy S IV sales expected to pass 100 million

The value of being right has never been greater

March 26, 2012

October 10, 2012

Jan 28, 2013

On 25 May 2012, an uncrewed variant of SpaceX Dragon became the first commercial spacecraft to successfully attach to the International Space Station

and the cost of being wrong has never been greater…

“At Apple, we strive to make world-class products that deliver the best experience possible to our customers. With the launch of our new Maps last week, we fell short on this commitment. We are extremely sorry for the frustration this has caused our customers and we are doing everything we can to make Maps better.”

Tim CookApple’s CEO

“At Apple, we strive to make world-class products that deliver the best experience possible to our customers. With the launch of our new Maps last week, we fell short on this commitment. We are extremely sorry for the frustration this has caused our customers and we are doing everything we can to make Maps better.”

Tim CookApple’s CEO

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Why now?

10X faster adoption

http://www.theatlantic.com/technology/archive/2012/04/the-100-year-march-of-technology-in-1-graph/255573/Innovation # of years to get to 90% penetration

Auto ~80 years

Radio ~30 years

Color TV ~20 years



Why now?

10X faster adoption

Smartphone Adoption Rate Fastest in Tech History

“The rate of Android and iOS device adoption among international users has out-paced the 1980s PC revolution, the 1990s Internet boom, and the social networking craze “

Innovation # of years to get to ~60% penetration

Smartphone 2 years !

“133.7 million people in the U.S. owned smartphones (57 percent mobile market penetration) during the three months ending in February 2013, up 8 percent since November”



Customers directions…

Industry Challenge: Increasing product complexity, pressure for shorter time to market and complex supply chains require systems manufactures to make decisions faster and earlier in the lifecycle

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“We need to commit and provide TCO assessment as early as RFP phase – over estimation leads to loss of tender, underestimation lead to troubled projects…”

US Aerospace Manufacture

“Daimler coordinated the development of a new standard that enable a virtual product development that can be assembled from a set of models assembled digitally”

European Auto Manufacture

“Design decisions made during conceptual phase are almost never changed. The cost is too high…” European Aerospace Manufacture

“We became mainly a system integrator of more than 325 suppliers across the globe. Defining integration interface early in the program was both critical and hard…”US Aerospace Manufacture

70% of Lifecycle cost is committed in Conceptual System Design Phase of the Lifecycle”. Source: DARPA

Gap between level of investment and importance…



In parallel, our products become smarter, and more complex…

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7 IBM Confidential7

The traditional V approach to Systems Engineering needs respond to these challenges… but represents a waterfall like approach:

Product Development Process

Deliver and Deploy

System Validation and Acceptance

Systems Engineering

Multi-Disciplined EngineeringSoftware

MechanicalElectronics

Integration and Verification

SystemsAnalysis & Design

DetailDesign

Implementation& Unit Test

ModuleIntegration & Test

(Sub-)System Integration

Testing

SystemAcceptance

RequirementsCapture & Analysis

1. “Multi-discipline engineering “starts only after the Systems Engineering and Requirement Engineering phases

2. Integration of the multi-disciplined artifact is being done only at the implementation phase ( physical prototype level)

3. Module and system integration testing is done only after implementation phase.

4. Redesign cycles are common as issues are discovered only at integration testing phase



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Continuous Engineering - game-changing capabilities

• Strategic Reuse“Don’t reinvent the wheel” Strategic reuse across the engineering lifecycle – to increase design efficiencies, engineer product lines, and tame complexity

• Continuous Verification“Measure twice, cut once”Verify requirements and design at all stages of the product lifecycle – to prevent rework and achieve faster time to quality

• Unlocking Engineering Knowledge“Turn Insight into Outcomes”Access, unlock and understand all engineering information, regardless of source – to enable the right decisions at the right times

Continuous Engineering is an enterprise capability that helps to speed delivery of increasingly complex and connected products by helping engineers accelerate learning throughout the lifecycle, while managing cost, quality and risk.



The new “V in V” process - early and continuous feedback in early systems design phases

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Product Development Process

Systems Engineering

Virtual Multi-Disciplined Engineering

RequirementsCapture & Analysis

implementation

Implementation& Unit Testing

Deliver and Deploy

System Validation and Acceptance

Deploy and Monitor

Physical Multi-Disciplined Engineering

SystemAcceptance

SystemsAnalysis & Design

DetailDesign

Virtual ModuleIntegration & Test

Virtual System Integration Testing

Virtual Analysis Integration

SimulationOptimization

ModuleIntegration & Test

(Sub-)System Integration Testing

verification

verification



Marrying two model driven approaches into an integrated solution

In parallel, various CAE technologies are being used on a day-to-day basis for domain-specific analysis such as Mechanical, Electrical, Electronics, Thermal, Acoustics and more.

– These analysis technologies have evolved over the years with minimal integration consideration

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Model Based Systems Engineering ( MBSE) and languages describing system architecture are gaining momentum and market adoption.

– Focus is on the structure of the systems (composition) and the interactions between subsystems and components

“Model Driven Systems Engineering is Systems Engineering”, INCOSE IW, 2013

The value resides in the combination of the different domain-specific analysis

technologies and systems level modeling. Closing the gap creates a comprehensive,

“system as a whole” analysis platform.



Why now? Two new Open Standards to leverage



Functional Mock-up Interface (FMI)

Open Standard for models exchange and tools integration

FMI 1.0 published in 2010 by ITEA2 MODELISAR (29 partners, 30 M€)

FMI 2.0 published in October 2013 by Modelica Association Project (23 companies and research institutes, https://www.fmi-standard.org/development)

FMI is supported by more than 40 tools (https://www.fmi-standard.org/tools)

Enginewith ECU

Gearboxwith ECU

Thermalsystems

Automatedcargo door

Chassis components,roadway, ECU (e.g. ESP)

etc.

functional mockup interface for model exchange and tool couplingBlocwitz, Otter, et al, adapted from: https://trac.fmi-standard.org/export/700/branches/public/docs/Modelica2011/The_Functional_Mockup_Interface.ppt



Functional Mock-up Interface Problems / Needs

Component development by supplier

Integration by OEM

Many different simulation tools?

supplier1 supplier2 supplier3 supplier4 supplier5

OEM

supplier1

tool 1

supplier2 supplier3 supplier4 supplier5

tool 2 tool 3 tool 4 tool 5

FMI OEM

SolutionReuse of supplier models by OEM:

DLL (model import) and/or

Tool coupling (co-simulation)

Protection of model IP of supplier

!supplier1

supplier2

supplier3

OEMAdded Value

Early validation of design

Increased processefficiency and quality

Blocwitz, Otter, et al, adapted from: https://trac.fmi-standard.org/export/700/branches/public/docs/Modelica2011/The_Functional_Mockup_Interface.ppt

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Emerging tool ecosystem - FMI

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Allow heterogeneous behavior modeling of the system using domain specific languages and tools (Simulink, Modelica, SysML/Rhapsody)

Allow earlier design run-time verification by simulation, monitoring, analysis of the emergent behavior of the system model

Improve communication between engineering domains (SE, control, mechanical, electrical and etc.) by providing virtual lab environment for all stakeholders

Use accepted open standards and methodologies instead of brittle tools specific ad-hoc solutions

Closing the gap between Systems level Modeling and Physical simulation - Hybrid Simulation Platform

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Leverage SysML to specify hybrid (continuous and discrete) system behavior using composition of FMUs and SysML components.

Use FMI to include models from other tools and languages (e.g., Simulink)

Contribute SysML behavioral models to hybrid simulation using FMI

Use joint simulation of components from different tools to analyze the emergent system behavior

Formalize requirements to simulation monitors to allow automatic run-time verification

Approach



Models

Physical Domain

SW Domian

Hybrid Simulation Platform Vision

Comp11 comp21

comp31

System model

Simulation centerSystem Requirements

Models, designs and results repositoryVersion control and dependency analysis

FMU1 FMU2

FMU3

Textual requirements

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HiL components

Contracts/ Simulation Monitors



Features

– Support FMI 1.0 for Model-exchange

– Exported FMU can use Rhapsody animation capabilities

FMU export from SysML (RHP 8.0.6)

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SysML element FMI element

Block FMUOutput flow port Scalar output discrete variable

Input flow port Scalar input (discrete or continuous) variable

Attribute with no corresponding flow port Scalar internal discrete variable

SysML attribute with <<FMUParameter>> stereotype Scalar internal parameter variable

Initial value of attribute Start value of scalar variable

Flow port or attribute with <<FMUIgnore>> stereotype No FMU element



Example : ITI SimulationX / IBM Rhapsody Integration

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Systems Engineering – Rhapsody

• Requirements management• System composition• Behavioral modeling• Results monitoring/guarding

System Simulation –SimulationX• Dynamic modeling• Component library management• Universal simulation engine

Model Exchange through FMU



Example ; FMU export plugin - typical tool chain

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SysML block

SimulationX model

FMU

FMU

FMU

SysML block

SysML block Other components (Simulink,

FMUs, Modelica)

Results

FMU export from IBM Rhapsody and simulation in SimulationX



Driveline performance«Requirement»

ID = 1

The car should accelerate in less than 11s from 0 to 100 km/hr

Sequential operation of controller«Requirement»

ID = 2

The car should reach at least 170 km/hr in 4th gear

Engine speed«Requirement»

ID = 3

Engine speed should not exceed 5500 rpm

Systems engineering requirements:

– Acceleration performance (0…100 km/h)

– Top speed in individual gears

– Speed or load limits on individual components

System composition

Domain specific behavioral models

Example: Automatic Transmission

NeutralGear

Gear1

Reactions

actualGear=1; ...

tm(swTimeout)

tm(swTimeout)

Gear2

/ / 2nd ge...

[omGB>omParam12]

[omGB<omParam21]

tm(swTimeout)

Gear3

[omGB>omParam23][omGB<omParam32]

tm(swTimeout)

Gear4

[omGB<omParam43][omGB>omParam34]

tm(swTimeout)

aT11

Attributes

engGear

shiftTime

inEinDinCinBinA om

ctr2ctr1mapEngine11

Attributes

om

in1

ctr1

Driver:DriverM1

Attributes

«fixed» pulse1_amplitude:F...out_y:FMIReal

driveline4WD11

Attributes

v

ctr1

rHPController2:RHPController21

Attributes

accPedal:RhpReal=0

actualGear:RhpInteger=0

BC:RhpInteger=0

omGB:RhpReal

CE:RhpIntegerCB:RhpIntegerCA:RhpInteger BD:RhpIntegerBC:RhpInteger

accPedal:RhpReal

actuator:FilterDelay1

Attributes

Operations

y1:FMIReal u1:FMIReal

sensor_CAN:FilterDelay1

Attributes

Operations

y2:FMIReal

u2:FMIReal

UML Statechart

Modelica

Simulink

SysML

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Example : ITI SimulationX / IBM Rhapsody Integration

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• Composition of multiple Model of Computation under single Framework utilizing FMI

• Heterogynous modeling and co-simulation

• SysML as entry point for Heterogynous modeling and analysis

• Hocks to commercial tools such as Rational Rhapsody, Modelica and Simulink

• Performance analysis

• Aspect based • Hocks to standard

architecture languages such as systemsC and AADL

EXAMPLE: iCyPhy - multi-domain simulation



What can you do next ?

Engage with IBM to get detailed demo of new FMI based integration capabilities

Jointly define a small pilot to evaluate needs and value

Engage with IBM to influence product directions

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