Reconf2012 V4

Model-based Engineering
in Medical Product
Development

ReConf 2012
March 14, 2012

Munich, Germany

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

Contents

 Goals

 Brief look on Siemens Healthcare

 Business challenges

 Model-based Engineering: Issues & Solutions

 Recommendations

 Further Information


Contents

 Goals



 Model-based Engineering: Issues & Solutions

 Results and Summary



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



 Model-based Engineering: Issues &
Solutions




Siemens Healthcare

In vivo diagnostics (imaging)

X-Ray Computed Magnetic Molecular Ultrasound Oncology
Tomography Resonance Imaging

IT Solutions
In vitro diagnostics (laboratory systems)

Immunoassay Molecular Clinical Chemistry Hematology Urinalysis Lab Automation Point of Care


Vector Consulting Services
Your Partner in Achieving Engineering
Excellence

 … offers a comprehensive consulting, tools
and training portfolio for optimizing technical Automotive
product development
 … serves industries such as automotive, Aviation &
Defense
aviation, IT and telecom, energy and
environment, medical and railway
IT &
Telecom
 … is supporting clients worldwide on
efficiency improvement, requirements
engineering, ALM/PLM, systems Energy &
Environment
engineering, product management, interim
management, and organizational change
Medical &
 … as a group serves companies across the Healthcare
world with over 1000 employees and sales
of well over 150 Mio € pa Railway &
Transportation
 www.vector.com/consulting


Contents

 Goals

 Brief look on Siemens and Vector
Healthcare

 Project syngo.via
Business Challenges

 Business challenges Issues & Solutions
Model Management:

 Lean Requirements Engineering
Results and Summary

 Results Information
Further and Summary



Business Challenges in Medical Device
Industry

Focus of this talk

Platforms
Sources: [1, 2, 5]

Application Life-cycle Model-based
Management Tools Globally Integrated Engineering and Reuse
Engineering
Systems


Typical Large-Scale Medical Device
Projects

Project Context

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


Business challenges

Model-based Engineering: Issues & Solutions

Results and Summary

Further and Summary



Industry Issues and Pain Points

Pain Points Business Impact
 Intransparent product Technology-driven product platform, no link to business
structure, domain drivers
model partially incomplete  Non-transparent relationship between problem & solution space
 Re-scoping sessions with customers on basis of many specs.
 Ambiguity and lack of Textual-based specifications are subject to interpretation
accuracy in specifications  Textual use case descriptions work only for smaller projects
 Natural language subject to interpretation, inconsistent, incomplete
 Growing architecture Redundancy of architecture components due to lack of
complexity understanding of problem- and solution space
 Business needs not consistently linked to features
 Too much variability in software architecture
 Insufficient verification and Test specifications in natural language are
validation efficiency executed in a manual way only
 Thousands of pages of requirements to transform
 Test cases manually created


Overview:
Solutions along the Life-Cycle

A) Requirements Meta-
Model
B) Feature D) Architecture Model E) Model-based
Model Mapping System Test
C) Graphical Modeling of
Clinical Workflows
Source: H IM


Pain point 1: Intransparent Product
Structure

Solutions:
Selected issues:
 Non-transparent relations A. Requirements Meta-model
between problem- & solution B. Feature Model
space
 Re-scoping sessions w/
Source: H IM

customer on basis of many
engineering specs.


Solution A:
Requirements Meta Model

Problem Space DB Characteristics:
Stakeholder  Provides needed artifacts, their
Business Plan Request
Market Analysis, attributes and relationships to each
SW Platform Roadmap,
Business Case, etc.
input for other.
input for  Using meta-model, it is also possible to
prescribe the way how / which data are
MRS
SW Feature
Analysis captured .
Market analyzed Use Case Specifications,
Requirement by Load Profiles, Benefits:
Concept Papers
 Lean artefact infrastructure, no
redundancy
SW Req.
SWRS
(Problem)  Guidance for engineering tasks
SW Req. with structured input
(Solution)
 Established link between business
Source: H IM

Specification/
Structural Element Content
Mapping or drivers, requirements, design and
Document Input
test


Solution B: Feature Model

Characteristics:
Highest Level of Feature Model  Hierarchical tree to describe the
structure, dependencies and
commonalities
 Lays out the basics for variant
management and impact analysis

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)
Graphical View
 Reduction in time to understand
Source: H IM

Hierarchical View
aspects of the system


Solution B:
Feature Model & Its Relations (1)

Stakeholder Requests Application Use Cases
How can I manage
huge amounts of
Requirements?

How do I scope a
product version
efficiently?

Architecture Model
Source: H IM


Solution B:
Feature Model & Its Relations (2)


How do I manage
Architecture Model
stakeholder requests
from different
businesses most
effectively?
Source: H IM


Pain point 2: Ambiguity and Lack of
Accuracy of Specifications

Level Requts. Manually Manual test
Object Embedded graphs case creation
Issues:
 Textual use case descriptions work only
Document Req. 1 Picture / diagram
for smaller projects < ~ 100
(text)
requirements
 Natural language subject to Features Req. 2 Picture / diagram
interpretation, usually inconsistent, (text)
incomplete with incorrect version (and
conflicting) Paragraph Req. 3 Picture / diagram
(text)
Root causes:
 Textual requirements engineering do not
scale for platform projects Solutions:
 Missing versioning
 No direct access to single requirements C. Graphical Modeling of
 Lack of product structure Clinical Workflows
 Inconsistently executed change
management process
Source: H IM


Solution C:
Graphical Modeling of Clinical Workflows (1)

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
Source: H IM

needs from the customer‘s point of view


Solution C:
Graphical Modeling of Clinical Workflows (2)


How can I analyze a Model
Architecture
feature or a
stakeholder request?
Source: H IM


Pain point 3: Growing Architecture
Complexity

Selected issues: Solutions:
 Business needs not consistently
linked to features/ requirements; D. Architecture Model Mapping
dependencies between features not
easily visible
Source: H IM

 Too much variability in software
architecture


Solution D:
Architecture Model Mapping

F Feature Model Characteristics:

F F F
 Identifies links between features and their
implementation
SWF SWF SWF SWF SWF SWF SWF
 Explicit modeling of variability in the architecture
S Architecture Model

Benefits:
SS SS SS

 Architectural decisions motivated by features
C C C C C C
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
Source: H IM

 Reduction of number of scoping sessions


Pain point 4: Insufficient Verification and
Validation Efficiency

Issues:
 Test cases often manually Solutions:
generated from prose use cases
 Cycle times for system test too E. Model-based System Test
long
Source: 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
Source: H IM

(*) Based on experience from other projects


Solution E:
Model-based System Test (2)


Architecture Model

Which application
use case is covered
by which test case?
Source: H IM


Contents

 Goals


Business challenges


Results and Summary

Further and Summary



Major Changes to Development for
Model-based Engineering

A) Requirements Meta-
Model
B) Feature D) Architecture Model E) Model-based
Model Mapping System Test
C) Graphical Modeling of
Clinical Workflows
Source: H IM


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 Processes
for model-based engineering is
mandatory to maintain sponsorship.

Model-based
Engineering
Tools Persons


Contents

 Goals


Business challenges


Results and Summary

Further Information



References

1. US Food & Drug Administration, Design Control Guidance for Medical Device Manufacturers; March 11, 1997
2. 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=0071605479
4. Renate Loeffler: Formal Scenario-based Requirements Specification and Test Case Generation in Healthcare
Applications, Diplomarbeit, Univ. Paderborn, 10/2009
5. Medical Device & Diagnostic Industry 101, Carey Smoak, Roche Molecular Systems Inc., Pleasonton, CA, Pharma SUG
2010, Paper 1B01
6. 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.pdf
7. 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%20engi
neering%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 Rudorfer
Program Manager System Platform
Siemens Healthcare Diagnostics
62 Flanders-Bartley Road
Flanders, NJ, 08736 (U.S.A.)

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

Email:
arnold.rudorfer@siemens.com


Dr. Christof Ebert
Managing Director
Vector Consulting Services GmbH

Ingersheimerstrasse 24
D-70499 Stuttgart

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

Email:
christof.ebert@vector.com


Documented Experiences and Best Practices
from various Industry Projects

English language:
Software & Systems
Requirements
Engineering: In Practice
2009
McGrawHill
German language:
Systematisches
Requirements
Engineering
Fourth edition, 2012
Dpunkt.verlag
Link to web site McGrawHill Link to web site Dpunkt


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