By Valentijn de Leeuw. Vice President, ARC Advisory Group.

1. The Contribution of New Data Storage and
Analytics Strategies to Smart Manufacturing
and Economic Growth
Internet of Things Cologne with inmation
Sept 10th, 2015
Valentijn de Leeuw
Vice President
ARC Advisory Group
vdeleeuw@arcweb.com

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© ARC Advisory Group
What ARC Does
t ARC helps Suppliers
• Accelerate Revenue Growth & Manage Costs
• Bring Products & Services to Market Faster and more
Effectively
t ARC helps Industrial Companies
• Understand the Value of Emerging Technologies
• Choose Appropriate Suppliers for their Unique Needs
• Implement Operational Best Practices
Blog: Newsletter:
http://industrial-iot.com http://industrial-iot.com/subscribe-to-newsletter/

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© ARC Advisory Group
Contents
1. Why do we need Innovation (and Industrial IoT)
2. New approach to Industrial Big Data (Analytics)
3. Where does industry stand
4. Innovator’s IIoT application examples
5. How to get started

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© ARC Advisory Group
vo•cab•u•la•ry (vō-kăbˈyə-lĕrˌē)
t Smart Manufacturing
• Advanced Manufacturing
• …
• Smart Manufacturing Technologies
• Industrial Internet of Things (IIoT)
• …
t Smart Manufacturing Initiatives

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© ARC Advisory Group
Smart manufacturing: the right strategy?
t Getting lost in initiatives and technologies?
• Defining, distinguishing and mapping?
• Missing the boat?
The question is do we pursue the right strategy?
• Which innovation impacts manufacturing growth most?
• What to focus on?
• Quick wins? Short payback?
t Time to ZOOM OUT and REFOCUS

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Manufacturing growth and competitiveness
Manufacturing
Resilience
Competitiveness
Growth
High degree of
Technology intensity
Technology/
manufacturing
complexity
Quality
DE
Complexity index 2010 versus 1995
SE
UK
FR
IT
ES
Picture: Airbus SAS S. Ramadier

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Manufacturing and R&D / Innovation
t We need innovation …
• Product innovation
• Process innovation
• Productivity innovation
t … and …
• Lift technology content, complexity and quality
• Create positive price and demand effects
t … for manufacturing …
• Competitiveness
• Output growth
• Downturn resilience

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1b
Data Points
Unmodified Picture from https://en.wikipedia.org/wiki/Petrochemical under license CC BY 3.0 (freely reusable)

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Industrial Data
Is
Big Data

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Your Grandfather’s BI & Analytics…
Operational
Systems
(ERP, MES, SCM,
Financials etc.)
Data
Warehouse
12
6
39
1
2
5
4
7
8
10
11

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Add Velocity, Volume and Variety…
Operational
Systems,
M2M Data,
Partner
Data, Public
Data, Textual…
Data
Warehouse
12
6
39
1
2
5
4
7
8
10
11

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…Has Too Much Latency for IIoT
Operational
Systems
(ERP, MES, SCM,
Financials etc.)
Data
Warehouse
Events Insight

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Cutting Latency
Operational
Systems,
M2M Data,
Partner
Data, Public
Data, Textual…
Data
Warehouse
1. Merged
Database

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Cutting Latency
2. Stream Processing (CEP)
3. Predictive Analytics
Operational
Systems
(ERP, MES, SCM,
Financials etc.)
Data
Warehouse

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What Predictive Analytics Isn’t…
3834
5117
6448
7908
9181
11497
10788
10021
8341
Dow Jones
Industrial Average

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Value from Variety (Unstructured Data)
Operational
Systems,
M2M Data,
Partner
Data, Public
Data, Textual…
Data
Warehouse
4. Text Analytics

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Unstructured Brings New Perspective

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The Cloud
t Industrial Data Analytics
• Smart manufacturing technology
t In the Cloud
• Industrial IoT application

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Is Industry Using Big Data…?
3%
“Big Data is
Irrelevant for Us”

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Is Industry Using Big Data…?
16%
“Projects Live,
or Near Live”

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Is Industry Using Big Data…?
38%“Don’t Understand
Big Data
or Why it Matters”

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Hybrid Architecture Emerging
Plant Operations
CorporatePurchasingEngineering
XYZ Chemical XYZ Chemical XYZ Chemical
Enterprise
Maintenance
XYZ Chemical
Device buses
Production Management
Logic &
Motion
Discrete ControlProcess Control
Infrastructure (Networks…)
Wireless
HMI /
Workstations
Fieldbus
Application
Specific
Appliances
Safety
XYZ Chemical
Machine
Mfr.
3rd Parties
Service
Provider
Physical asset with
sensors, actuators
Local IoT Compute and
Communicate module
Smart Machine
IoT Smart
Module
Emerging Option: Connect
Assets Using New Technologies
New IoT
Analytics and
Applications
Purdue
Hierarchy
IIoT Hierarchy
Enterprise

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IoT at Intel: asset, production & quality analytics
http://www.intel.com/content/www/us/en/internet-of-things/white-papers/industrial-optimizing-manufacturing-with-iot-paper.html
t IoT solution as add-on on top
of MES
t Case 1: predictive asset
analytics 9M$
• Reduce non-genuine off-
spec (losses -25%)
• Predictive maintenance
(spare cost -20%)
t Case 2: Reduce yield losses
of soldering process
t Case 3: Image analytics for
conformity testing

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Major benefits using process analytics at SABIC UK
Tim Sharpe, Energy management at Sabic UK, Sabisu, EIF 2015
t Cloud-basedAnalyticsat
SABICUK
• $100mbenefitsatlevel4
• $27mbenefitslevel3
• $12mbenefitsatlevel2
• PartnerSabisu.co.uk

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Manufacturing Analytics at Dow
t Culture change
t Plant
performance
improvement
t From post-
mortem analysis
to preventive
action
t Next: roll-out
Source: Lloyd Colegrove, Dow Chemicals, ARC’s European Industrie Forum 2015

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Example: North Sea Oil Rig
t Problem
• Lost production from unplanned
downtime
t Solution
• Predict component failure in
advance
t How
• Predictive Analytics
• Cloud
• Outsourced monitoring
t Benefit
• $7.5m revenue saved thru timely
change of water pump seal
© Richard Child

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Refocus and get going
t Target radical efficiency improvements
• Start small
t Choose areas of innovation in line with business strategy and sector needs
• Per production type, process or plant type
t Set goals, define KPI’s
• Improve product, material, substance performance if possible
• Innovate business models (e.g. circular) and value creation ecosystem
• Sustainability
t Assessment methodology and Roadmap
• Maturity model, business case, roadmap
• Feasible roadmap, with regular updates

29. Acknowledgement
David White
Senior Analyst
ARC Advisory Group
dwhite@arcweb.com
@addicted2data
IIoT Newsletter:
http://industrial-iot.com/
subscribe-to-newsletter/
Thanks to David for the analysis and survey
on IIoT, big data and analytics