Industry 4.0

K. RajaramanDirector, Entrepreneurship Development Institute, Tamil Nadu

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Industry 4.0Industry 4.0

Manufacturing : 5Ms

Materials Properties & Functions

Machines Precision & Capabilities

Methods Efficiency & Productivity

Measurements Sensing & Improvements

Modelling Prediction, Optimisation, Prevention

Industry 4.0

Industry 4.0

Mass customisation

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.

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.

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.

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

Definition

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.

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.

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.

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.

Adidas : SpeedfactoryProducing your own shoes

Active Semantic Product Memory

Smart services based on active digital product memories

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.

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.

Smart components:Autodiagnosis & configurabilityThe 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

Internet of Things

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.

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.

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

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”

Digital Compass of

Options for

Manufacturers

Emerging standards

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?

Industry-Academia- Government platform

Participating in development and dissemination of emerging standards

Joint R&D for Technology & Product development

Hi end skilled manpower training

Thank you...