Nih ce-presentation-05272016(for approval)

Unrestricted © Siemens Healthcare GmbH, 2016
Configuration
Engineering for Invitro-
Diagnostic (IVD) Product
Development
Prepared for National
Institute of Health
Author: Arnold Rudorfer
Date: May 27, 2016
Status: 1st draft

2016-02-20Page 2 HC xxx – xxx
Unrestricted © Siemens Healthcare GmbH, 2016 HOOD05162002380020
Abstract of this Talk
This talk on Configuration Engineering (= Configuration Management for
Platform development) will discuss challenges, solution approaches and
engineering experiences in invitro-diagnostic (IVD) product development.
CE is an emerging discipline in various industries (such as medical devices,
automotive, avionics/ space, …) which has developed from Configuration
Management practices for single products. Further, examples presented
will highlight the underlying CE concepts as well as address tool issues
including observed benefits over the introduction.

Table of Contents
Business pressures, Configuration Engineering overview 6-122
Goals, Siemens Healthcare Laboratory Diagnostics 3-51
Appendix 24-275
Page
Challenges, approaches, engineering practices 13-213
Key takeaways 224

Goals of this Presentation
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix
 Provide an overview
on configuration
management
challenges for
platforms and its
solutions in a practical
context.
 Share engineering
practices and
benefits observed.

Siemens Healthcare Laboratory Diagnostics
A Global Leader in Key Market Segments
Largest Installed Base of Analytical Automation
Chemistry
Diagnostics ITLab Automation Molecular Point of Care
Hematology Hemostasis Immunoassay
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Business Pressures for IVD Product Development
Need to
industrialize
product
development
Cost down
Product
variety
Cycle time
down
Complexity
growth
Configuration
Engineering
Platform-based
development
Focus of this talk
ALM
PLM
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Providing Context “An Invitro-Diagnostic Instrument” …
A lab
instrument is a
highly complex
mechatronics-
based system:
hardware,
software,
firmware
producing test
results.
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Configuration Management Defined
A disciplined, efficient workflow for evolving a product including its data
and associated procedural information from cradle to grave with
increasing precision and maturity.
Controlled
Input(s):
Product Needs:
 Feature/ function
 Problem reports
 Enhancements
 …
Product data:
 Product structure
 Product configuration
 Product documentation
 Design data
 …
Output(s):
New approved product
data:
 Product structures
 Product configurations
 Product documentation
 Design data
 …
Change history:
 Audit/ traceability
 Verification
 …
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Impact of Variety in IVD Product Development
 Infinite variety is not manageable (cost, timeline,
quality, …)
 Variety in product development needs to be
consciously managed.
Evolving discipline: Configuration Engineering
= Variant Management (what) + Configuration
Management (how)
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Concept End-to-End Configuration Engineering Workflow
(1)
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix
Coordinate
and assess
Product Data
Setup
(1&2)
Establish
initial eBOM
structure
(3)
Plan track,
and review
and Track
product
release
(4, 5, & 6)
Configuration
Build
Management
(7)
Configuration
Change
Management
(8, 9, 10)
Prototype
Modification
Management
(11,12)

(2)
(per PDP phase gates)
 gBOM
eBOM
mBOM
Feature 1 Feature 2 Feature 3 Feature N
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

(3)
eBOM
 gBOM
Feature 1 Feature 2 Feature 3 Feature N
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

(4)
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Structure of the Challenges, Approaches, Engineering
Practices Employed
1 Managing product
variants
How do I structure, assess
and control product
variability?
2 Structure an efficient
and reliable change
management workflow
What is the best approach
for executing change
management?
3 Managing changes
across engineering
disciplines
What do you do to manage
and control product data
across development
projects?
4 Coordinating design
changes across
Engineering and
Manufacturing
How do I consistently
synchronize Engineering
and Manufacturing to
become faster and less
costly?
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Structure of the Challenges, Approaches, Engineering
Practices Employed (2)
Coordinate
and assess
Product Data
Setup
(1&2)
Establish
initial eBOM
structure
(3)
Plan track,
and review
and Track
product
release
(4, 5, & 6)
Configuration
Build
Management
(7)
Configuration
Change
Management
(8, 9, 10)
Prototype
Modification
Management
(11,12)
Product
Variants
1
Manage change across disciplines
Efficient change management workflow
2
3
Coordinate change beyond
Engineering
4
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Structure of Selected Challenges, Approach & Engineering
Practices
Challenge, define a solution strategy
For each solution strategy, share ideas on
engineering practices
Illustrate benefits with supporting data
Challenge Approach
Engineering
Practice
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Solution Strategy Map for Configuration Engineering
# Challenge Approach Engineering Practice
1 Manage product
variants
 Provide transparency on variation
points in product structure
 Proactively manage variation points
in a configuration model
 Generic platform
product structure
 Modular product
architecture
 Frontend configuration
engineering
2 Structure efficient
and reliable change
management
workflow
Deploy end-to-end change management
workflow to provide always accurate,
actionable data (as automated as
possible)
Standardized change
management workflow
3 Manage change
across engineering
disciplines
Integration of product and configuration
data, change can be synchronized
accurately across discipline
Integrated cross discipline
change management
4 Coordinate change
Beyond Engineering
Enable manufacturing to obtain accurate
engineering data to plan & execute
Manufacturing
Synchronized data
exchange of engineering to
manufacturing product data
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Manage Product Variants (1)
 Explicit modeling of a generic product structure
defining commonality & variability
 Consistently manage variation points in a product and
a configuration model for product variants over time.
 Automate creation and update of product &
configuration model using PLM tool(s).
Approach: Frontend Configuration Engineering
Benefits
 Explicit modeling of product variants provides precision
for product scope.
 Improve design speed and reuse supporting a modular
product architecture.
 Enabler for a configure to order manufacturing model.
Customer needs drive
product variants
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Structure Efficient & Reliable Change Management
Workflow (1)
 End-to-end bill of material handling (from a
generic BOM, engineering BOM to a
manufacturing BOM.
 Handling of BOM baselines according to the
level of design maturity and product lifecycle
Approach: Standardized change management workflow
Benefits
 Accurate controlled changes in a single
product data repository.
 Reduced change cycle time with less
defects.
 Increased engineering productivity
 Audit proof documentation needed for
medical devices.
Change management workflow
needs to cover different phases of
lifecycle.
gBOM eBOM mBOM
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Structure Efficient & Reliable Change Management
Workflow (2)
 Workflow supported change management
integrated for hardware, software and
firmware.
Approach: Standardized change management workflow
Benefits
 Synchronize an emerging change with
prototype configuration data.
 Change requests are integrated with
emerging problem reports and/or
enhancements.
 Automation support for processing of change
requests (pre-defined, templated, internal
quality checks).
For use in simple to more
complex change requests
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Managing Change Across Disciplines
 Integrated ALM/PLM tool provides
access to product data by engineering
disciplines, changes are synchronized
quickly across disciplines.
Approach: Cross-discipline change management workflow
Benefits
 Open access to prototype configuration data
for all disciplines (HW, SW, FW).
 Knowledge on design changes are
systematically captured and are made
retrievable.
 Reduced errors, rework by having all product
data in a single database.
Sample for an integrated
change in a sub-system
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Managing Change Across Disciplines
 Apply concept of continuous integration
of upgrades into instrument prototypes
(similar to software).
 Interface between ALM/PLM tool chain
to MRP system allows synchronization
and transparency for design changes.
Approach: Collaborating on Change Beyond Engineering
Benefits
 Instrument prototype generation matures
earlier by means of controlled
deployment of upgrades.
 Synchronization of eBOM and mBOM
structures, traceability.
Design changes are identified early
and are continuously integrated
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Key Takeaways: Establishing Configuration Engineering in
Your Organization
 Lay out an end-to-end vision for where CE can add value and
has to lead the path.
 Development of CE needs diverse engineering perspectives
along the product development lifecycle (up- and down-stream).
 For a multi-disciplinary domain such as IVD, select a ALM/ PLM
tool-chain which allows as many stakeholders as possible to
collaborate within the same workspace.
 CE based on my own experiences needs to grow over time
delivering short-term gains to build credibility while keeping the
grand vision in place.
What you need to consider when developing CE
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Appendix
 Reference documents
 Contact details Arnold Rudorfer
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Reference Documents
 Arnold Rudorfer, Alexander Evers: Configuration
Engineering workflow, August 2015
 Siemens Healthcare Laboratory Diagnostics:
Company overview, 2016
 Goals,
Siemens LD
 Business
pressures,
CE overview
 Challenges,
approaches,
engineering
practices
 Key
takeaways
 Appendix

Contact Details Arnold Rudorfer
Arnold Rudorfer is a Senior Engineering Leader Instrument
Development at Siemens Healthcare Laboratory Diagnostics. He has
more than twenty years systems development experience with a focus
on medical devices and enterprise platforms. His research interests
include requirements and systems engineering, organizational change
management, software technologies, innovation- and business
strategy. Mr. Rudorfer holds an MS in software engineering and
business administration from the University of Technology Graz,
Austria. Further, he is a INOCSE member and PMP/MSP certified.
Siemens Healthcare Laboratory Diagnostics
62 Flanders Bartley Road
Flanders, NJ, 07836
Cell: +1 609 954 2384
E-Mail: arnold.rudorfer@siemens.com

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