This is a slideset of a webinar held by Dr. Dirk Ortloff from Process Relations. The webinar elaborated on the challenges and solutions addressing the problem of effectively managing the growing amounts of digital process development data. He introduced approaches that address the “heap” challenge. It has been explained how new software tools and methodologies can be leveraged to convert raw data from diverse source into usable information and especially how to recreate the context the data is generated in. The metrology capabilities of today’s high-tech R&D generate an increasing amount of digital data. Subsequently process engineers are flooded with this - partly structured but mostly unstructured - data. To organize, manage and evaluate this data requires a major effort. Engineers spent a significant portion (20% – 35%) of their time just administering this data rather than evaluating it. Using the tools and methodologies introduced in this webinar results in structured and context aware information which can reduce the amount of repeated experiments and speed up developments. The recording of the webinar can be downloaded from: http://www.process-relations.com/english/services/publications-mainmenu-90/webinars/323-free-webinar-high-tech-rad-drowning-in-data-but-starving-for-information

1. Webinar:
High-Tech R&D: Drowning in data but starving
for information
Dortmund, 9th of January 2013

2. Agenda
 Brief Company introduction
 Definitions
 Situation Today / Problem
 Requirements
 Converting the data and using the information
 Summary
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Process Relations GmbH

3. About Process Relations GmbH
Dortmund, 9th of January 2013

4. Process Relations’ Mission
…is to enable you to…
 Expedite your R&D with flexible Software solutions
 Next generation recipe and DoE management
 Virtual manufacturing data management
 Automated data collection from various sources
 Experimental data management, analysis and extraction
We deliver the easy to use, unique, world class Process
Development Execution System (PDES)
and consulting services.
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5. History and Key Milestones
2000 2004 2008 2010
Bosch XperiDesk Entering
Project Launched new
markets
2002 2007 2009 2011
CK Process First First
Project Relations XperiDesk Marque
Founded Customers Customer
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6. Definitions
Dortmund, 9th of January 2013

7. Definitions
 Data: symbols
Data is raw. It simply exists and has no
significance beyond its existence (in and
of itself). It can exist in any form, usable
or not. It does not have meaning of itself.
In computer parlance, a spreadsheet
generally starts out by holding data.
 Information: data that are processed to be useful; provides
answers to "who", "what", "where", and "when" questions.
Information is Data that has been given meaning by way of
relational connection.
 Knowledge: application of Data and Information; answers "how"
questions. Knowledge is the appropriate collection of information,
such that it's intent is to be useful.
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Process Relations GmbH Following the DIKW model: http://www.systems-thinking.org/dikw/dikw.htm

8. High-Tech R&D – Yesterday
Decisions
Evaluation
Knowledge
Behavior (Interpretation)
Engineers
Dependencies / Patterns
work time
Relations spent
Data and Parameters
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Process Relations GmbH

9. Situation Today / Problem
Dortmund, 9th of January 2013

10. Some citations
 “Because most organizations seem to be
drowning in data but starving for
information, there is a growing need for
enterprise manufacturing intelligence
software”
ARC Group
 “Nevertheless, several studies in the past
five years point to significant ROI for
improved access to information. ROI figures
range from 38%to over 600%, depending on
whether the new information or content
management system is an incremental
improvement over an existing one or is an
entirely new system replacing previously
manual processes.”
IDC
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11. CONFIDENTIAL Reused from: http://blog.mindjet.com/wp-content/uploads/2011/11/Drowing- Slide 11
Process Relations GmbH in-Data-Infographic.jpg

12. The challenges
 25% development projects reach the market
 of those 66% fail their original expectations
 20% of projects take too long and miss their market
window
 35% of companies experience runaway projects
 40% of R&D experiments are repeated
CONFIDENTIAL Source: IDC “Accelerating Science-Led Innovation for Slide 12
Process Relations GmbH
Competitive Advantage” Feb. 2012

13. Few problems in information management?
 Excel files on file servers or desktops contain
important data and are not sufficiently searchable
 Result files are distributed / duplicated in different
versions on different systems
 Link between the data is not sufficiently visible
(only in file system structure)
 Only one-dimensional sorting / searching criteria
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14. Typical development challenges
 “Once we had a result picture …”
 What was the exact context of that experiment? Which
results were achieved, what images made?
 Which was the latest data set?
 XY left and his lab book was unreadable to anyone but
him
 How long does it take your engineers to recover
development data with context from 18 months ago?
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15. Cost increase in R&D efforts
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16. What it boils down to:
 “Fact: 80 percent of the
digitized information in
a typical company is in
the form of unstructured
data such as
documents, e-mail, and
images. “1
 “Fact: The amount of unstructured content in a typical
business grows by 50 percent every year. “1
CONFIDENTIAL 1: Oracle: Information Management – Get control of your Information Slide 16
Process Relations GmbH Picture is property of: www.yakidoo.com

17. Current Situation and
Requirements
Dortmund, 9th of January 2013

18. Current situation
 Distributed, untraceable and
undiscoverable R&D results
 Limited formalized data available
that is not interlinked
 Sometimes usage of old or
retired data
 Incomplete documentation
 Lack of access to results and timeline of former projects
 Access and transfer protection difficult
 Unmanaged data  ↑risk + ↑costs of projects
„Great ideas get lost in the sea of incomplete documentation“
(W. Wong – Editor Electronic Design Journal)
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19. Semiconductor R&D spending
45.000.000.000,00 US$ / year
(in 2007)
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Process Relations GmbH

20. Wasted for manual data management & search
4.500.000.000,00 US$ / year
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21. Meet Mr. Lumberjack …
 Lumberjack is feverishly trying to
fell a tree
 Using a dull saw
 Therefore going no where
 Bystander points out the facts
 Reply: too busy sawing to
sharpen my saw
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22. Requirements
 Repository of former and current R&D and
manufacturing data / information / knowledge
 Full audit trail for all changes & complete history
 Possibilities to manage the lifecycle of every item
 Easy access and multi-dimensional retrieval possibilities
 Low effort documentation approach to relieve engineers
from tedious tasks
 Access protection on per-item level
 Defined way to document R&D work
 Centralized, platform independent, structured and
comprehensive data repository for structured &
unstructured data
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Process Relations GmbH

23. Converting the data and using
the information
Dortmund, 9th of January 2013

24. Comprehensive Capturing of Developed IP
 All data is absorbed in the centralized
database (enterprise information platform)
 Nothing is forgotten; history is kept in
versions  compliance fullfillment
 Everything is available to anybody with
authorized access (blackboxing possible)
 All information is searchable
 Instantaneous, formalized results
 Only relevant data retrieved
 Extensive relationships maintained
between the stored data  full context
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25. – Covering the Complete Development Cycle
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26. – Covering the Complete Development Cycle
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27. – Filling with experimental data
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28. – Management of Experiment information
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29. – Management of Experiment information
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30. – Management of file data
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31. – versatile searching capabilities
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32. – versatile searching capabilities
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33. – Export tables to JMP, Excel, …
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34. – and analyze in JMP, Excel, …
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35. Summary
Dortmund, 9th of January 2013

36. Time and Cost Savings
 Reduction in the development cycle time by
 enabling the use of simulation by every process engineers
 reducing the development WIP
 Reduction in the number of learning cycles by
 Avoiding re-learning
 Reducing the number of “failed” experiments
 Improving knowledge extraction efficiency from the
experimental data
 Increasing predictability of cycle time by time-lined history
 Seamless, compliant documentation through full audit trail
 Creation of process engineer knowledge rather than
management of data
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37. Process Development – Yesterday
Decisions
Evaluation
Knowledge
Behavior (Interpretation)
Engineers
Dependencies / Patterns
work time
Relations spent
Data and Parameters
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Process Relations GmbH

38. Process Development – Today
Engineers
Decisions work time
spent
Evaluation
Knowledge
Behavior (Interpretation)
Dependencies / Patterns
Relations
Data and Parameters
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39. What means converting data into information?
 It means
 Comprehensively collected
 Collaboratively collected
 Formalized data
 Infrastructure knows about the physical quantities of values
 Easy selectively sharable data
 Information is even better than better data
 Multidimensional access and search
 Graphical assessment and navigation possibilities
 Applying the principles in process development means
 Risks ↓, WIP ↓, Costs ↓, Efficiency ↑, Moral ↑
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Process Relations GmbH

40. Information Governance principles
Process Relations GmbH applied to
Emil-Figge-Straße 76-80
44227 Dortmund, Germany
Process Development
T: +49 231-9742-5970
F: +49 231-9742-5972
info@process-relations.com
www.process-relations.com