Digi tanscd 2017 _ infonomics

Flexibility of Infonomics
in the Industrial Production
of Machines and Plants
− Knowledge Management in the Industry 4.0 –
DigiTrans CD
funding code 01DO16006
Prof. Dr.-Ing. Michael Schaffner

2Prof. Dr.-Ing. Michael Schaffner | Flexibility Infonomics in the Industrial Production …21.02.2017
Our vision of Industrie 4.0

Our vision of Industrie 4.0
© Graphscape
© Bosch
© Festo
© VW

Today's reality is
in best case „Industry 3.0
As a result:
The implicit knowledge of the technicians
provides the flexibility of infonomics
in „Industry 3.0“.

Agenda
Flexibility of Infonomics in the Industrial Production …
1. Problem Settings
2. Research Gap and Scientific Approach
3. Findings (general view of intermediate status)
4. Outlook

Infonomics in research landscape
 is primarily focussed on process data stream to control linked manufacturing systems
 but the operation and service of machines and plants must be not ignored
Research interest: technical information for handling the equipment
1. Problem Settings
Motivation for the Topic
design drawings risk analysis
supplier documentations
spare part information
approval documents
handling context
manufacturing processes
illustrations
pictures
Technical Communication
(technical writing and translating)
Input Output
instruction manuals
maintenance manuals
service literature
video clips
training material
© Luis Louro - Fotolia.com

Scenario of “predictive maintenance”
 relevant components of machines and plants are equipped with sensor technologies
 these embedded systems are monitoring the wear conditions
 if needed, an OPC-UA-event triggers different digital (cloud-)services, e.g.
 HR database: searching a technician with specific experiences
 HR workforce database: booking this technician
 ERP service department: ordering spare parts
 ERP material store: allocate specific tools
 Content Management: delivering knowledge artifacts
(maintenance instructions)
in various multi-media formats
exactly fitting the
- mobile device capabilities
- education & experience level
 ERGO: the knowledge of working behavior migrates to integrated business processes
 in traditional factories human actions and decisions is 75% based on implicit knowledge
 in smart factories these knowledge has to be transformed into smart services by digitization
1. Problem Settings
Case Study Bosch
(Ferber 2013, 3 Perspektiven 2016)

Degree of Digitization of Value Chains (PwC 2014, n=235)
 significant increasing (from 20 to 80%)
 over all sectors
BUT: Where does the digital data come from?
 in some industries up to 99% of all data was lost
before reaching operational decision makers (McKinsey 2015, n=300)
 no capturing
 no transfer
1. Problem Settings
Wish and Reality of Digitization
20192014
Mechanical and Automotive Process Industry Electrical Engineering, Information and
Plant Engineering Suppliers Electronics Communication Industrie
 no analysis
 no synthesis
 no infrastructure
 no structured data
© PWC 2014

Agenda
1. Problem Settings
4. Outlook

Digital Transformation in context of technical communication requires
How will the work organization in technical communication change
in context of Industry 4.0
a) along the end-to-end value chain of suppliers, manufacturers
and commercial users (horizontal integration)
b) within the cross-functional IT-Systems of a company (vertical integration)?
(Schaffner 2016a)
Research Question
digital product lifecycle logbook
(collecting tank for
information artifacts)
sensitive working with the
sector „technical communication“
1 3
standardization of processes
and binding standards
2
semantical structures for
context-sensitive compilation
of artifacts are missing
but bad reputation
and poor investments“
on official sites – by now – only
rough ideas about
standardizations and norms

Scientific Approach
Research, Development & Support programmes
“intelligent information for Request &
Delivery Standard” (iiRDS)
sponsorship: International Association of
Technical Communication e.V.
project management: Prof. Dr. M. Schaffner (since 3/16)
„TecCOMFrame“ - European Academic
Competence Framework for Technical
Communicators
sponsorship: Erasmus+ program, European Union
silent partner: Prof. Dr. M. Schaffner (since 1/17)
“unternehmenswertMensch” in the
program “future of work”
sponsorship: ESF, BMAS, BMBF
accredited partner: Prof. Dr. M. Schaffner (since 10/13)
“Curriculum 4.0 - consequences of
digitization for study reformations at
german universities
sponsorship: Stifterverband
applicants: Prof. Dr. R. Jerrentrup
Prof. Dr. M. Schaffner (07/16)
"Technology-based service systems“ – in
research program "Innovations for
tomorrow's production, service and
work"
sponsorship: BMBF
concept creation: FOM-KCT, Prof. Dr. M. Schaffner (02/16)
ofher fields of empirical observations
continuous evaluation of academic studies official institutions in Industry 4.0 (DIN, Fraunhofer, VDI/VDE,VDMA)
field studies based on qualified vocational network
mid-sized and large enterprises with activities in Industry 4.0
(e.g. ABB, Bosch, Empolis, Festo, B. Krone, KUKA, Leitner, SAP,
Siemens, Trumpf)
active cooperation in the FOM Competence Centre of
Technology and Innovation Management (KCT)
as a member and co-opted scientist

Agenda
1. Problem Settings
4. Outlook

Prof. Dr.-Ing. Michael Schaffner | Flexibility Infonomics in the Industrial Production …21.02.2017
Paradigm change in creation of technical literatur
Disruptive Business Modell in Technical Communication
from user orientation to user centering
Not the „product“ but the effect and benefits
of the service is in focus of the „product“.
„documentation“ is valuable „information“ solves a problem
extrinsic stimulated
technical writers (engineers) analyzing
realistic situations of action and writing suitable
instructions (service documentation)
(static, usually based on status of delivery: BOM as delivered)
Industry 3.0
user = humans
intrinsic stimulated
as a coming out from the situation, a remote
terminal creates an individual, context-
sensitive image of the requested information
(dynamically: based on BOM as built, wear data etc.)
Industry 4.0
user = humans + devices
© kuroksta - Fotolia.com

 working on
static knowledge
 in prevailing settings,
people perform for
these cognitive process
(implicit knowledge)
 technical writing is “easy” and just needs
to deliver non-dynamic information
 working on dynamically
evolving knowledge
 for cognitive processes
in smart devices
technical writing has
to foster metadata-structures which
allows additionally
Extended Knowledge Management
inspired by Lehner (2012)
Knowledge as a process of convenient interconnection of information
knowledge
class
definition description
situational
knowledge
knowledge of
typical, domain-
specific
situations
correct
classification and
interpretation of
the application
context (eg
operation,
maintenance,
jam-up)
conceptual
knowledge
static
knowledge
about facts,
concepts and
principles
Facts about what
is to be done in a
specific situation
knowledge
class
definition description
procedural
knowledge
acquired through
practice
extension of
factual knowledge
through
experience
(learning curves)
strategic
knowledge
metacognitive
knowledge about
an optimal
structuring of the
problem-solving
behavior
problem-solving
strategies for
problems for
which there are no
general solution
strategies
Industry 3.0 Industry 4.0

Rethinking is necessary
 no longer thinking in products (e.g. instruction manuals, service literature)
 thinking in various usability of information fragments in different situations
 in addition to humans, information users can also be smart devices
Modification of job descriptions
 80% of the daily work technical writer are creating content
 and only 20% they are creating metadata
80% content, 20% meta data 20% content, 80% meta data
creation of content creation of structures
(technical writing today) (technical writing tomorrow)
Skill Profile Updating
Thiswillreverse!

What we need is „intelligent information“
 based on gapless data capturing
 and semantical interconnections
At first we have to eliminate
digital inefficiencies:
Digital Inefficiencies in Capturing and Passtrough
(McKinsey 2015, S. 22)
digital non-captured information
is hidden knowledge
and can not be used
in automated knowledge
processes
(horizontal & vertical value chains)

How can intelligent information become a reality?
 as simple as formidable:
the idea of the International Association of Technical Communication (tekom e.V.)
Thinking backwards – based on the benefit.
 provision of usage information must be automated
 the benefit is the problem solving
 for problem solving we need a delivery
of suitable, concentrated and actual instructions
(not a confusing manual with 500 pages)
 at the very first the beginning a
hyper-accurate request is needed
 all these leads us to “intelligent information”
o a semantical structure of context and content,
which is representing the cognitive flexibility
of the human brain
o to the tekom standard
»intelligent information Request & Delivery Standard« (iiRDS)
Implementation of the Customer Centering
www.tekom.de/technische-kommunikation/iirds.html (14.02.2017)

The idea and current state of development
 flexibility infonomics in technical communication needs
iiRDS: New upcoming Standard in Technical Communication
dynamischeAnpassungandie
Person,dieRolle,die
Arbeitsaufgabeundden
Anwendungskontext
 situation-related information
 dynamic integration of assistance
information and operating
parameters
 end-to-end data management
 …
Herstellerunabhängigkeit
 normalized metadata
 for processing information
from different sources
 end-to-end data transfer
 normalized content format
 cross-media processing
 terminal-specific display
 …
logical flexibility
(user perspective)
©
semantical
modelling
format
description
intelligent information
Request and Delivery Standard
(© iiRDS is a trademark of tekom e.V., tekom 2016; Fritz/Parson/Kreutzer 2016; Schaffner 2016b)
infrastructural flexibility
(technical perspective)

Semantical Model of Technical Information 4.0 (exemplary)









Steps 1 – 4: Request triggering
Steps 5 – 9: Delivery triggering

Specific focus: „predictive maintenance“
Illustration of Job Profile Reform „Knowledge Architect“
knowledge class Exemplary tasks
situational knowledge
• semantical conjunction of machine-readable alarm-signals (e.g. sensor
values embedded in an OPC-UA communication protocol) and context-
sensitive content (e.g. lifecycle stage)
• metadata development to support situation decisions on user-side (e.g.
Big-Data analytic) => What situation could become critical?
• especially across supplier value chains
conceptual knowledge
• action-based matching of local framework conditions and content
(e.g. regarding language, local vocational education)
• conjunction of necessary assistance data (upstream and downstream)
regarding to the specific situation
procedural knowledge
• conjunction of the machine agents with the agents of for example
• HR Infosystem (e.g. profile database, workforce management)
• ERP (e.g. material logistics, spare part department)
• gapless feedback and digitization of service information (experience
knowledge)
strategic knowledge
• heuristic logic, data mining in Big Data for identification of error patterns,
new solution patterns, qualified experts etc.

Agenda
1. Problem Settings
4. Outlook

We are only just on the first meters
of the long way towards
flexibility infonomics in Industry 4.0.
 digitalization concepts are needed to avoid digital inefficiencies
(integration of components of the 3rd industrial revolution)
 (international) standardization is still under development, e.g. running projects
 DIN spec. 91303 (digital product lifecaclelogbook)
 Tekom-iiRDS (provisioning standard for intelligent information)
 VDI 2770 (digital manufacturers information)
 ZVEI RAMI 4.0 (reference architecture model Industry 4.0)
 affordable digital cloud-services are needed for integration small-sized companies
(cf. project “Technology-based service systems“ 2017-2020 of Federal Ministery of Education and Research)
4. Outlook

3 Perspektiven (2016): Wie implizites Wissen der Wertschöpfungskette zugeführt werden kann („How implicit knowledge can
be transferred in value chains“); www.3perspektiven.de, Handelsblatt 12.12.2016
Brynjolfsson, E.; McAfee, A. (2016): The Second Machine Age; Kulmbach 2016
DKE (2015): Deutsche Normungs-Roadmap Industrie 4.0 („German standardization roadmap“), Berlin 10/2015
Ferber, S. (2013): Bosch - Das Internet der Dinge auf dem Weg in die Fabrik („Internet of things on the way to the factory“); in:
VDMA Nachrichten, Sonderdruck, 3/2013, S. 18ff.
Fraunhofer (2013) (ed.): Produktionsarbeit der Zukunft – Industrie 4.0 („Production work of the future – Industry 4.0“),
Stuttgart 2013
Fritz, M.; Parson, U.; Kreutzer, M. (2016): Intelligent Information Request and Delivery Standard; tekom yearly conference,
Stuttgart, 08.-10.11.2016
Lehner, F. (2012): Wissensmanagement („Knowledge Management“); München 2012
McKinsey (2015) (ed.): Industry 4.0 – How to navigate digitization of the manufacturing sector, München 2015
North, K. (2011): Wissensorientierte Unternehmensführung („Knowledge-oriented Management“); Wiesbaden 2011
PwC (2014) (ed.): Industrie 4.0 – Chancen und Herausforderungen der vierten industriellen Revolution („Opportunities and
challenges of the fourth industrial revolution“), 2014
Schaffner, M. (2012): Wer soll’s machen?– Wissensmanagement als Kernkompetenz der Technischen Kommunikation („Who
should do it? – Knowledge Management as a core competemce of technical communication“), Wissensmanagement
Tage, Stuttgart, 20.11.2012
Schaffner, M. (2013): Wirtschaftlichkeit Technischer Kommunikation erhöhen – Budgets realistisch planen („Profita-bility of
technical communication – realistic budget planning“); in: technische kommunikation, 05/2012, S. 25-30
Schaffner, M. (2014): Krisen kündigen sich an – mit Wissensmanagement Unternehmenskrisen vermeiden („Crises announce
themselves - Avoid business crisis by using knowledge management“), FOM-Symposium, Berlin, 14.10.2014
Schaffner, M. (2016a): Industrie 4.0 – Neue Wissensflüsse in der Technischen Kommunikation? („Industry 4.0 – new
knowledge flow in technical communication“); tekom spring conference, Berlin, 14.-15.04.2016
Schaffner, M. (2016b): tekom iiRDS in der Anwendung („tekom iiRDS in practice“), tekom yearly conference,
Stuttgart, 08.-10.11.2016
tekom (2016): iiRDS – intelligent information Request & Delivery; www.tekom.de/technische-kommunikation/iirds.html
References of Presentation

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