The document discusses how exponential technological growth will impact tribological coatings. It notes that technology is advancing at an exponential rather than linear rate, as increased knowledge and tools drive further innovation. Major trends include increased data collection via sensors and the Internet of Things, allowing for predictive maintenance of coated assets. This will move surface engineering beyond passive coatings to connected, sensing surfaces integrated into digital platforms. Tribological coatings must adapt to leverage trends in data analytics, nanotechnology, and biomimetics to remain competitive in the future.

1. School of something
FACULTY OF OTHER
School of Mechanical Engineering
FACULTY OF ENGINEERING
Surface Ventures
What Exponential Growth
of Technology means
for Tribological Coatings
Tomasz Liskiewicz, Institute of Functional Surfaces
Keynote Lecture
15th International Conference on Plasma Surface Engineering
Sept 12-16, 2016, Garmisch-Partenkirchen, Germany

2. Outline
• Exponential Growth
• Global Technology Trends
• Protective and Tribological Coatings
• Summary and Conclusions
School of Mechanical Engineering
FACULTY OF ENGINEERING

3. Exponential Growth
School of Mechanical Engineering
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4. Linear
1, 2, 3, 4, 5, 6…
• 30 linear steps: end up
about 30 meter away
Exponential
1, 2, 4, 8, 16, 32…
• 30 exponential steps: billion
meters away (26 times
around the planet)
School of Mechanical Engineering
FACULTY OF ENGINEERING

5. Knowledge grows exponentially
• The more we know the greater our
ability to learn
• The greater our ability to learn the
faster we expand our knowledge base
• Growth of knowledge fuels growth of
technology
• Each new scientific discovery becomes
a tool with which novel technologies
are invented
• Technology feeds on itself
School of Mechanical Engineering
FACULTY OF ENGINEERING

6. Law of accelerating returns
• Every generation of technology stands on the shoulders of the last
generation of technology
• We use our best tools to build even better ones
• The rate of progress continues to speed up from version to version
School of Mechanical Engineering
FACULTY OF ENGINEERING
“Transcendence” (2014)“The Singularity is Near”
Ray Kurzweil (2005)

7. Technology feels like it is accelerating,
because it actually is
• Moore’s Law
• Exponential rise of integrated circuits
• Processing power doubles every two years
• Cost decreases at the same rate
• Related technologies/industries driven by
computing speed and power
School of Mechanical Engineering
FACULTY OF ENGINEERING

8. School of Mechanical Engineering
FACULTY OF ENGINEERING

9. School of Mechanical Engineering
FACULTY OF ENGINEERING
http://content.time.com/time/interactive/0,31813,2048601,00.html

10. Exponential growth of computing
based technology
• 40 years ago: one computer took up a
whole building
• Today: the computer in your cell phone
is a million times cheaper and a
thousand times more powerful
• In 20 years: what fits in your pocket now
will fit into a blood cell and will again be
millions of times more cost effective
School of Mechanical Engineering
FACULTY OF ENGINEERING

11. Human genome project
• Started in 1990
• After 7.5 years: only 1%
was completed
• Sceptics were predicting
100 years to complete
• Ray Kurzweil predicted:
15 years
• Genome successfully
sequenced in 2003
School of Mechanical Engineering
FACULTY OF ENGINEERING
singularity.com

12. School of Mechanical Engineering
FACULTY OF ENGINEERING
singularity.com

13. Internet bandwidth
School of Mechanical Engineering
FACULTY OF ENGINEERING

14. How to think exponentially
School of Mechanical Engineering
FACULTY OF ENGINEERING

15. Exponential growth surprise factor
• Exponential growth radically different from our intuition
• Intuition about the future hardwired in our brains
School of Mechanical Engineering
FACULTY OF ENGINEERING
singularityhub.com

16. Technology Trends
School of Mechanical Engineering
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17. Ray Kurzweil’s predictions in 2016
• The genetics revolution will allow us
to reprogram our own biology
• The nanotechnology revolution will
allow us to manipulate matter at the
molecular and atomic scale
• The robotics revolution will allow us
to create a greater than human non-
biological intelligence
School of Mechanical Engineering
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18. The industries of the future, Alec Ross (2015)
• Explores the next waves of innovation in robotics,
genetics, coding and big data and how they will
affect our world
• Trends covered:
• Robotics
• Advanced Life Sciences
• Code-ification of Money
• Cybersecurity
• Big Data
School of Mechanical Engineering
FACULTY OF ENGINEERING

19. School of Mechanical Engineering
FACULTY OF ENGINEERING
What Technology Wants, Kevin Kelly (2010)
The Inevitable, Kevin Kelly (2016)
• Technology in a wider context of human evolution
• Human evolution with technology has been a trend of
improvement
• Technology is like a living organism
• Technology has its own needs

20. Deloitte: Tech Trends 2016
(Innovation in the Digital Era)
• Right-speed IT
• Augmented & virtual reality go to work
• Internet of Things: From sensing to doing
• Reimagining core systems
• Autonomic platforms
• Blockchain: Democratized trust
• Industrialized analytics
• Social impact of exponential technologies
School of Mechanical Engineering
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21. Biomimetics – trend towards ideality
School of Mechanical Engineering
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22. Biomimetics – friction in nature
School of Mechanical Engineering
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10-6
(1μm)
10-7
(100nm=0.1μm)
10-5
(10μm)
10-4
(100μm=0.1mm)
10-3
(1mm)
10-2
(10mm)
10-1
(100mm=0.1m)
100
(1m)
101
(10m)
102
(100m=0.1km)
103
(1km)
104
(10km)
a
b
c
d
e
f
g
h
i
j
k
l
m
n
o p s
r
T Liskiewicz et al, Friction in Nature, WIT Transactions on Ecology and the Environment, 2008

23. TRIZ
• TRIZ: Theory of Inventive Problems Solving
• Teoriya Resheniya Izobreatatelskikh
Zadach
• TRIZ message: Innovation Can Be Codified
• There are universal principles of invention
that are the basis for creative innovations
that advance technology
• If these principles are identified and
codified, they can be taught to make the
process of invention more predictable
School of Mechanical Engineering
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24. TRIZ
• Using the knowledge and experience of former
inventors
• 2m patents studied by Altshuller’s team
• 5m (?) patents studied up to date
• Problems and solutions were repeated across
industries
• Patterns of technical evolution were repeated
across industries
• Innovations can use scientific effects outside the
field where they were developed
School of Mechanical Engineering
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Genrich Altshuller

25. TRIZ trends
• Prediction where the systems will evolve in the future
• Indication of the most likely successful future direction
• Assessment and development of intellectual property
School of Mechanical Engineering
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Immobile
system
Joint
Multiple
joints
Completely
elastic
Liquid/
gas
Field

26. TRIZ – surface specific trend
School of Mechanical Engineering
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27. Protective & Tribological Coatings
in the context of Exponential
Technology
School of Mechanical Engineering
FACULTY OF ENGINEERING

28. Protective & Tribological Coatings in Exponential Technology
Outline:
• Big Data
• Internet of Things
• Sensors
• Maintenance Monitoring
• Platform Economy
School of Mechanical Engineering
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29. Big Data
• Land was the raw material of the agricultural age
• Iron was the raw material of the industrial age
• Data is the raw material of the information age
90% of the world’s digital data
has been generated over the last two years
Big Data term describes how these large amounts of data can now be
used to understand, analyse, and forecast trends in real time.
The industries of the future, Alec Ross (2015)
School of Mechanical Engineering
FACULTY OF ENGINEERING

30. Smart Manufacturing Enterprise
These three operational environments will set
the stage for the smart manufacturing
enterprise:
• Smart Enterprise Control: tight integration
of manufacturing assets with the wider
enterprise
• Asset Performance Management:
improved asset performance by wireless
sensors, easy cloud connectivity and data
analytics
• Augmented Operators: increased
productivity by use of mobile devices, data
analytics and augmented reality
School of Mechanical Engineering
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31. Industrial Internet of Things
• Connected assets operate as part of a larger system that make up the
smart manufacturing enterprise
• The assets possess varying levels of intelligent functionality (from simple
sensing and actuating, to control, optimisation and full autonomous
operation)
• Consumer IoT: moderate value so far (nice to have solutions)
• Commercial IoT: real business value
School of Mechanical Engineering
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32. School of Mechanical Engineering
FACULTY OF ENGINEERING
http://www.visualcapitalist.com/industrial-internet-things-next-big-growth-driver/

33. School of Mechanical Engineering
FACULTY OF ENGINEERING
Quick adoption of internet related technologies
• 100 million people travelled by air: 70 years after invention of the airplane
• 100 million people to use telephone: 50 years
• 100 million PC users: 14 years
• 100 million Internet users: 7 years
• Facebook acquired 100 million users in 2 years

34. Sensors – the nervous system of the IIoT
• Small, cheap, many of them
• 1000’s of sensors vs. a technician with a gauge
(data resolution)
• Single performance tasks linked to complex
analytical models (temperature, vibration,
acoustics)
• E.g. fiber optic systems available collecting
spatially continuous strain and temp. data along
the length of the fiber in real time
• Towards smart sensors with autonomous
learning capability (more data more finely
tuned)
School of Mechanical Engineering
FACULTY OF ENGINEERING

35. The immediate business need (Case Study)
• ABB sensors package for low-voltage motors
• No additional infrastructure (incorporated battery &
storage)
• Technician syncs data wirelessly
• Downtime reduced up to 70%
• Preventive maintenance extends life of the motor by 30%
• Improve motor efficiency by 10%
School of Mechanical Engineering
FACULTY OF ENGINEERING
machinedesign.com

36. “Neural dust” sensor/implant (Case Study)
• 2x1mm, battery-less
• Can monitor internal nerves, muscles or organs in real
time
• Temperature, pressure, oxygen, pH
• Fit-bit like device
• Also stimulate nerves and muscles
School of Mechanical Engineering
FACULTY OF ENGINEERING
UC Bercley
ScienceNews, Aug 8, 2016

37. Maintenance Monitoring
• Maintenance 1.0: wait until it breaks
• Maintenance 2.0: monitoring
maintenance (determine breakdown
by oil, vibration, thermal analysis etc.)
• Maintenance 3.0: predictive
maintenance (asset management
along with more improved condition-
based techniques)
• Maintenance 4.0: proactive
maintenance (sensors, data analysis,
determination of trends)
School of Mechanical Engineering
FACULTY OF ENGINEERING

38. New Economy: from Product to Platforms
School of Mechanical Engineering
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Accenture, Technology Vision 2016, Trend 3: Platform Economy

39. Advanced Materials Systems Framework
• Materials technologies move beyond the
frontier of new molecules and materials
• Value creation through functional solutions
• Leveraging inventive combinations of:
• Materials
• Process technologies
• Business models
• Partnerships
• Collaborations
School of Mechanical Engineering
FACULTY OF ENGINEERING
Deloitte Touche Tohmatsu Limited Global Manufacturing Industry Group

40. Cost of missing the trend: Kodak
• 1996: $28 billion market cap and 140,000 employees
• 2012: Kodak filed for bankruptcy
School of Mechanical Engineering
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singularityhub.com

41. Summary and Conclusions
School of Mechanical Engineering
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42. Summary and conclusions
In the not-too-distant future, billions of smart things in the physical
world will be sensing, responding, communicating and sharing data
• Surface Ventures: studying engineering surfaces in the context of the
exponential growth of technology
• Moving from passive coating to connected-sensing-responsive surface
• Surface engineering progress fuelled by trends: digitalisation,
nanotechnology, platform solutions, biomimetics
School of Mechanical Engineering
FACULTY OF ENGINEERING

43. Summary and conclusions
• The potential of IoT lies in the ability to link automation systems with
enterprise planning and product life cycle systems
• Simple measurements BUT deep analytics (underpinned by tribological
models)
• Predictive maintenance, improved operational efficiency
• Businesses will pay a high cost of not paying close attention to
technology trends
School of Mechanical Engineering
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44. The future has many names: For the weak, it means
the unattainable. For the fearful, it means the
unknown. For the courageous, it means opportunity.
- Victor Hugo
School of Mechanical Engineering
FACULTY OF ENGINEERING
I skate to where the puck is going to be,
not where it has been.
- Wayne Gretzky

45. School of Mechanical Engineering
FACULTY OF ENGINEERING
t.liskiewicz@leeds.ac.uk
@tomliskiewicz
Tomasz Liskiewicz
School of Mechanical Engineering
University of Leeds
Leeds LS2 9JT
United Kingdom