Reconf2012 V4

2012 Siemens Healthcare Diagnostics Inc. Page 1© 2012 Siemens Healthcare Diagnostics Inc. All rights reserved.

Model-based Engineering in Medical Product Development

ReConf 2012 March 14, 2012

Munich, Germany

2012 Siemens Healthcare Diagnostics Inc. Page 2

Contents

Goals

Brief look on Siemens Healthcare

Business challenges

Model-based Engineering: Issues & Solutions

Recommendations

Further Information


Contents

Goals


Business challenges


Results and Summary

Further Information


Goals of this Talk

Share the experiences using models in engineering gained at Siemens Healthcare

Discuss challenges, needs and requirements to advance model-driven product development

Show the concrete value of model-based engineering


Contents

Goals


Business challenges


Results and Summary

Further Information


Siemens Healthcare

Immunoassay Clinical ChemistryMolecular Hematology Lab AutomationUrinalysis Point of Care

In vitro diagnostics (laboratory systems)

X-Ray ComputedTomography

MagneticResonance

MolecularImaging

Ultrasound

In vivo diagnostics (imaging)

IT Solutions

Oncology


Vector Consulting ServicesYour Partner in Achieving Engineering Excellence

… offers a comprehensive consulting, tools and training portfolio for optimizing technical product development

… serves industries such as automotive, aviation, IT and telecom, energy and environment, medical and railway

… is supporting clients worldwide on efficiency improvement, requirements engineering, ALM/PLM, systems engineering, product management, interim management, and organizational change

… as a group serves companies across the world with over 1000 employees and sales of well over 150 Mio € pa

www.vector.com/consulting

Railway &Transportation

IT & Telecom

Automotive

Aviation & Defense

Energy &Environment

Medical &Healthcare


Contents

Goals

Brief look on Siemens and Vector

Project syngo.via

Business challenges

Lean Requirements Engineering

Results and Summary

Further Information

Contents

Goals


Business Challenges

Model Management: Issues & Solutions

Results and Summary

Further Information


Business Challenges in Medical Device Industry

Application Life-cycleManagement Tools

Model-basedEngineeringGlobally Integrated

Systems

PlatformsApplication Life-cycle

Management ToolsModel-based

Engineering and ReuseGlobally IntegratedSystems

Platforms

Focus of this talk

Sour

ces:

[1, 2

, 5]


Project Context

Typical Large-Scale Medical Device Projects

Several thousand single product requirements

Several million lines of code

Several hundred developers in many locations worldwide

Many fold clinical applications

Source: H IM


Disclaimer:The content discussed in this presentation needs

to be considered as work in progress.


Contents

Goals


Project syngo.via

Business challenges


Results and Summary

Further Information

Contents

Goals


Business challenges


Results and Summary

Further Information


Industry Issues and Pain Points

Pain Points Business Impact Intransparent product

structure, domain model partially incomplete

Technology-driven product platform, no link to businessdriversNon-transparent relationship between problem & solution spaceRe-scoping sessions with customers on basis of many specs.

Ambiguity and lack of accuracy in specifications

Textual-based specifications are subject to interpretation Textual use case descriptions work only for smaller projectsNatural language subject to interpretation, inconsistent, incomplete

Growing architecture complexity

Redundancy of architecture components due to lack ofunderstanding of problem- and solution spaceBusiness needs not consistently linked to features Too much variability in software architecture

Insufficient verification and validation efficiency

Test specifications in natural language are executed in a manual way only Thousands of pages of requirements to transform Test cases manually created


Overview: Solutions along the Life-Cycle

D) Architecture Model Mapping

C) Graphical Modeling of Clinical Workflows

B) Feature Model

A) Requirements Meta-Model

E) Model-based System Test

Sou

rce:

H IM


Pain point 1: Intransparent Product Structure

Solutions:

A. Requirements Meta-modelB. Feature Model

Selected issues: Non-transparent relations

between problem- & solution space

Re-scoping sessions w/ customer on basis of many engineering specs.

Sou

rce:

H IM


Solution A: Requirements Meta Model

Benefits: Lean artefact infrastructure, no

redundancy Guidance for engineering tasks

with structured input Established link between business

drivers, requirements, design and test

Characteristics:

Provides needed artifacts, their attributes and relationships to each other. Using meta-model, it is also possible to

prescribe the way how / which data are captured .

SWRS

MRS

Market Requirement

SW Feature

SW Req.(Problem)

SW Req.(Solution)

DB

Business PlanMarket Analysis,

SW Platform Roadmap, Business Case, etc.

Stakeholder Request

input for

input for

Specification/Document Structural Element Content Mapping or

Input

AnalysisUse Case Specifications,

Load Profiles,Concept Papers

analyzedby

Problem Space

Sou

rce:

H IM


Solution B: Feature Model

Highest Level of Feature Model

Graphical ViewHierarchical View

Benefits: Higher level abstraction of grouping

of requirements into sellable units: From 5,000 product requirements to 800+ features (factor ~ 6)

Visual domain model for healthcare workflows (tree & graphical)

Reduction in time to understand aspects of the system

Characteristics:

Hierarchical tree to describe the structure, dependencies and commonalities Lays out the basics for variant

management and impact analysis

Sou

rce:

H IM


Solution B: Feature Model & Its Relations (1)

Application Use CasesStakeholder Requests

Architecture Model

How can I manage huge amounts ofRequirements?

How do I scope a product version efficiently?

Sou

rce:

H IM


Solution B: Feature Model & Its Relations (2)


Architecture ModelHow do I manage stakeholder requests from different businesses most effectively?

Sou

rce:

H IM


Pain point 2: Ambiguity and Lack of Accuracy of Specifications

Issues: Textual use case descriptions work only

for smaller projects < ~ 100 requirements

Natural language subject to interpretation, usually inconsistent, incomplete with incorrect version (and conflicting)

Root causes: Textual requirements engineering do not

scale for platform projects Missing versioning No direct access to single requirements Lack of product structure Inconsistently executed change

management process

Level Requts.Object

Manually Embedded graphs

Manual testcase creation

Document

Features

Paragraph

Req. 1(text)

Req. 2(text)

Req. 3(text)

Picture / diagram

Picture / diagram

Picture / diagram

Solutions:

C. Graphical Modeling of Clinical Workflows

Sou

rce:

H IM


Characteristics: Used to describe clinical workflows that

consist of a collection of steps in a defined sequence together with accompanying specification of pre-/post-conditions, business rules, performance aspects, etc.

Benefits: Increase expressiveness of clinical

workflows to describe dynamic behaviors of clinical workflows Early analysis of stakeholder requests

from customers Improved impact analysis of change

requests Joint modeling sessions to describe the

needs from the customer‘s point of view

Solution C: Graphical Modeling of Clinical Workflows (1)

Sou

rce:

H IM


Solution C: Graphical Modeling of Clinical Workflows (2)


Architecture ModelHow can I analyze a feature or a stakeholder request?

Sou

rce:

H IM


Pain point 3: Growing Architecture Complexity

Solutions:

D. Architecture Model Mapping

Selected issues: Business needs not consistently

linked to features/ requirements; dependencies between features not easily visible

Too much variability in software architecture

Sou

rce:

H IM


Solution D: Architecture Model Mapping

Characteristics:

Identifies links between features and their

implementation

Explicit modeling of variability in the architecture

Benefits:

Architectural decisions motivated by features

and product-line variability

Enabling reduction of architectural complexity

Support impact analysis for (de-) scoping

sessions Early identification of architectural risks

Improved accuracy of early effort estimates

Reduction of number of scoping sessions

F

F F F

SWF SWF SWF SWF SWF SWF SWF

S

SS SS SS

C C C C C C

Feature Model

Architecture Model

Sou

rce:

H IM


Pain point 4: Insufficient Verification and Validation Efficiency

Solutions:

E. Model-based System Test

Issues: Test cases often manually

generated from prose use cases Cycle times for system test too

long

Sou

rce:

H IM


Solution E: Model-based System Test (1)

Benefits: Early identification of requirements

defects through validation by testers Effort reduction for test (cycle time,

cost ~ -30%) and increase of test coverage (*)

Decrease number of defects

Model-based testing is highly structured, reproducible and efficient Increase reuse of development

artifacts Quicker impact analysis by parsing

model for late requirements changes

(*) Based on experience from other projects

Sou

rce:

H IM


Solution E: Model-based System Test (2)


Architecture Model

Which application use case is covered by which test case?

Sou

rce:

H IM


Contents

Goals


Project syngo.via

Business challenges


Results and Summary

Further Information

Contents

Goals


Business challenges


Results and Summary

Further Information


Major Changes to Development forModel-based Engineering

Sou

rce:

H IM

D) Architecture Model Mapping

C) Graphical Modeling of Clinical Workflows

B) Feature Model

A) Requirements Meta-Model

E) Model-based System Test


Benefits from Model-based Engineering

Feature models can help to reduce detail of product requirements through abstraction (~ factor 6) [6]

Reduction of review times by ~ 40% using graphical modeling of product requirements [9]

Reduction of analysis time for requirements changes

Model-based testing reduces testing effort by ~ 30% through automation

Reduction in overall cycle time for development projects driving more efficiency [3, 6]


Experiences with Introducing Model-based Engineering

Model-based engineering means a huge organizational change. Only 10% of organizations in medical have moved that road so far [10]

Modeling competence of product managers and requirements engineers needs to be built up step-by-step thereby facilitating acceptance

Seamless model-driven engineering needs adequate tools support.

Continuous assessment and verification of business benefits for model-based engineering is mandatory to maintain sponsorship.

Model-basedEngineering

Processes

Tools Persons


Thank you for your attention!

© Siemens AG 2012. All rights reserved.


Contents

Goals


Project syngo.via

Business challenges


Results and Summary

Further Information

Contents

Goals


Business challenges


Results and Summary

Further Information


References

1. US Food & Drug Administration, Design Control Guidance for Medical Device Manufacturers; March 11, 19972. US Food & Drug Administration, Quality System Regulation,; January 1, 1997, http://www.fda.org/cdrh/qsr/01qsreg.html 3. Brian Berenbach, Daniel Paulish, Arnold Rudorfer, Juergen Kazmeier, Software Systems Requirements Engineering; Mc-

Graw Hill 2009; http://www.mhprofessional.com/product.php?isbn=00716054794. Renate Loeffler: Formal Scenario-based Requirements Specification and Test Case Generation in Healthcare

Applications, Diplomarbeit, Univ. Paderborn, 10/20095. Medical Device & Diagnostic Industry 101, Carey Smoak, Roche Molecular Systems Inc., Pleasonton, CA, Pharma SUG

2010, Paper 1B016. Arnold Rudorfer, Christof Ebert: Lean Requirements Engineering in Medical Systems, MedConf 2010, Munich, Germany,

October 14, 2010; http://2010.medconf.de/downloads/abstracts2010/T2_T3_V1_vector_siemens.pdf7. Arnold Rudorfer, Christof Ebert: Quality Requirements Engineering in in Medical Systems, OOP11, Munich, Germany,

January 27, 2011 http://www.sigs.de/download/oop_2011/downloads/files/Do2-3_Ebert_Rudorfer_Update_QualityRE_OOP2011.pdf

8. Arnold Rudorfer: Model-based Engineering in Medical Device Development – Issues & Solutions, INCOSE Workshop, Phoenix, AZ, USA, January 31, 2011, http://www.omgwiki.org/MBSE/lib/exe/fetch.php?media=mbse:2011iw_incose_modelmanagement_rudorfer.pdf

9. Brian Berenbach: Comparison of UML and Text based Requirements Engineering, http://www.cs.helsinki.fi/u/vjkuusel/docs/Comparison%20of%20UML%20and%20text%20based%20requirements%20engineering%20Brian%20Berenbach.pdf

10. Christian Denger, Raimund Feldman: State of the Practice in Software Development for Medical Device Production, Fraunhofer Institute Experimentelles Software Engineering, February 2007


Arnold RudorferProgram Manager System PlatformSiemens Healthcare Diagnostics62 Flanders-Bartley RoadFlanders, NJ, 08736 (U.S.A.)

Phone: +1 973 927 28 28 ext. 4732Cell: +1 609 954 2384

Email:[email protected]


Dr. Christof EbertManaging DirectorVector Consulting Services GmbH

Ingersheimerstrasse 24D-70499 Stuttgart

Phone: +49 711 – 80670-1525Fax: +49 711 – 86070-444

Email:[email protected]


Documented Experiences and Best Practices from various Industry Projects

Link to web site McGrawHill

English language:

Software & Systems Requirements Engineering: In Practice

2009

McGrawHill

German language:

Systematisches Requirements Engineering

Fourth edition, 2012

Dpunkt.verlagLink to web site Dpunkt

Documents

Reconf2012 V4