Industry 4.0 promises to create new customer value in the market place by unleashing a combination of new technologies, data analytics, new generation cyber-physical production systems and newer methods of human machine interfaces. What does a developing country like India need to do to join the race?

1. Industry 4.0
K. Rajaraman
Director, Entrepreneurship Development Institute, Tamil Nadu
Www.editn.in

2. Manufacturing : 5Ms
Materials Properties & Functions
Machines Precision & Capabilities
Methods Efficiency & Productivity
Measurements Sensing & Improvements
Modelling Prediction, Optimisation,
Prevention

3. Industry 4.0

4. Industry 4.0
Mass customisation

5. Definition

Industry 4.0 as the next phase in the digitization of the
manufacturing sector, driven by five disruptions:
 the astonishing rise in data volumes from machines and
processes, computational power, and connectivity,
especially new low-power wide-area networks;
 Emergence of analytics, esp. predictive
 Advanced process and business-intelligence
capabilities, such as IOT;
 new forms of human-machine interaction such as touch
interfaces and augmented-reality systems; and
 improvements in transferring digital instructions to the
physical world, such as advanced robotics and 3-D
printing.

7. Similar Goals : different flags

Smart Manufacturing Leadership Coalition

Industrie 4.0 in the EU

Made in China 2025

Manufacturing Innovation 3.0 in the East

Share a common pursuit:
Smart & advanced manufacturing.

8. Expected Outcomes – I4.0

Agility : Agile processes responsive to fluctuations or new trends in
customer demands and mass customisation up to Batch size 1.

Broaden the Innovation Base : Open architecture will stimulate
entrepreneurs to develop manufacturing hardware and software that
can be plugged into the SM platform for access by multiple users.

Next-generation workforce : A manufacturing workforce with
advanced skills and talent will be able to more fully take advantage of
manufacturing intelligence.

Promote Global Competitiveness : Pervasive application of data
driven modeling and simulation, and to build continual improvements
in manufacturing intelligence, performance, and competitiveness.

Resource efficiency : Usable manufacturing intelligence on
operational inputs (energy, water, materials, labor, and time) will allow
factories to run more efficiently and minimize the use of precious
resources.

9. Expected Outcomes - SMLC(US)

Demand-driven efficient use of resources and supplies in more highly
optimized plants and supply
 80% reduction in cost of modeling and simulation
 25% reduction in safety incidents
 25% improvement in energy efficiency
 10% improvement in overall operating efficiency
 40% reduction in cycle times
 40% reduction in water

Product safety
 Product tracking and traceability throughout the supply

Sustainable production processes for current and future critical
industries
 10x improvement in time to market in target industries
 25% reduction in consumer packaging

12. Definition

13. Digital-to-physical transfer.

Local Motors builds cars almost entirely through
3-D printing, with a design crowdsourced from
an online community.

It can build a new model from scratch in a year,
far less than the industry average of six.

Vauxhall and GM, among others, still bend a lot
of metal, but also use 3-D printing and rapid
prototyping to minimize their time to market.

14. Platforms

“Platforms,” in which products, services, and
information can be exchanged via predefined
streams. Think open-source software applied to
the manufacturing context.

For example, a company might provide
technology to connect multiple parties and
coordinate their interactions. SLM Solutions, a
3-D-printer manufacturer, and Atos, an IT
services company, are currently running a pilot
project to develop such a marketplace.

15. Platforms: Manufacturing as a Service

‘Uber’isation of manufacturing: SMEs can perhaps
setup their own cooperative cloud manufacturing
platforms. It is known that SMEs could suffer from low
capacity utilisation cycles. Manufacturing as a service
could enable cooperative targeting of better capacity
utilisation!

For eg, the manufacturers of printing machines have
traditionally made the bulk of their revenues from
selling and servicing presses. When the presses
generate usage data, the manufacturers can become
brokers of press time, knowing when customers’
presses are available, and negotiating printing prices
accordingly.

16. Highly customised products

Customer can create her own perfume from
millions of possibilities via a web portal.

Smart Factory can produce 36 000 Unique
Perfume Packages per day

24 hours after the order via the Internet has
been completed the individualized product is
ready for shipment.

Since the customer of an individualized
product, designed by herself, she does not
accept long delivery times, the product should
be produced close to the customer.

17. Adidas : Speedfactory
Producing your own shoes

18. Active Semantic Product
Memory

19. Smart services based on
active digital product memories

20. Pay-by-use

Pay-by-use and subscription-based services, turning
machinery from capex to opex for manufacturers.

Rolls-Royce pioneered this approach in its jet-engine
business; other manufacturers have followed suit.

Atlas Copco, a manufacturer of air compressors based
in Nacka, Sweden, is moving away from selling its
equipment directly, and, instead, is billing only for the
compressed air that is used. The machines installed at
customer sites can monitor the flow of compressed air
and adjust the output according to customer need,
who pay as they use.

21. Pay-by-use

Businesses that license intellectual property.
Today, many manufacturing companies have
deep expertise in their products and processes,
but lack the expertise to generate value from
their data. SAP offers consulting services that
build on its software. Qualcomm makes more
than half of its profits from intellectual-property
royalties.

Manufacturers might offer consulting services
or other businesses that monetize the value of
their expertise.

22. Smart components:
Autodiagnosis & configurability
The sensors integrated in the pump
record key operating data that is then
evaluated directly at the pump by
PumpMeter.
This information is used to automatically
adapt operation to changing operating
conditions and to optimise operation
through PumpDrive.
On-site displays or mobile terminals can
be used to determine the operating point
of the pump, identify optimisation
potential and adapt and reconfigure
operating modes.
This information can also be accessed in
vertical and horizontal integration setups
via a large number of field buses used in
conjunction with a cloud-based
connection, for example.
KSB: Digital pumps

23. Internet of Things

24. Advanced analytics.

Stronger analysis can dramatically improve product
development. One automaker uses data from its
online configurator together with purchasing data to
identify options that customers are willing to pay a
premium for.

With this knowledge, the automaker reduced the
options on one model to just 13,000—three orders of
magnitude fewer than its competitor, which offered
27,000,000. Development time and production costs
fell dramatically; most companies can improve gross
margin by 30 percent within 24 months.

25. Advanced analytics.

Analysis of your customers’ daily and seasonal use of
machinery can help improve production schedules.

Data about employee performance can determine
training needs and scheduling

Production data can illuminate opportunities to
eliminate downtime or speed up throughput.

Analytics can also help meet aspirations that seemed
nearly impossible before. For example, many
companies struggle to improve their eco-footprint.

Analytics can identify wasted materials and suggest
ways to reclaim them, or to use them as inputs for
other industrial processes.

27. Smart logistics
It is possible to transmit digital
information over large distances with
low energy consumption using
Bluetooth Low Energy (BLE). Many
procedures in logistics are simplified
and the efficiency of numerous
processes is improved. With their
small size, high data security and low
cost, BLE tags are universally
applicable and fulfil a wide range of
requirements. The special sensors in
the tags can produce an exact profile
of the ambient conditions during the
dispatch, transport and receipt of the
goods to enable the status and
incidents to be checked.
KSB: Digital pumps

28. Digital Compass of Options

With production data now available for the
asking, executives rightly wonder about how to
begin. Which data would be most beneficial?
Which data leakages are causing the most
pain? Which technologies would deliver the
biggest return on investment for a company,
given its unique circumstances?

To sort through the choices, manufacturing
leaders can use a “digital compass”

29. Digital
Compass of
Options
for
Manufacturers

30. Emerging standards

31. Road map

Forming an Industry-Academia- Government
platform for I4.0

Work on bottom of pyramid elements of I4.0 –
smart components, smart equipment, predictive
analytics, smart logistics. Each of these are
independent business opportunities and offers
Indian cos opportunities to feed ad collaborate
with the developed world

Complete Smart factories may be an end point
– desirability in India ? Maybe in Tiruppur?

32. Industry-Academia- Government platform

Participating in development and dissemination
of emerging standards

Joint R&D for Technology & Product
development

Hi end skilled manpower training

33. Thank you...