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Distributed Manufacturing: Next in line for blockchain innovation

Blockchain has already disrupted business processes in the financial sector, and is poised to impact companies across industries.

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By: Jagmeet Singh

Blockchain has already disrupted business processes in the financial sector, and is poised to impact companies across industries. Because the technology can provide an immutable digital record of contractual interactions and transactions across an ecosystem, we believe that manufacturing is likely next in line.

Blockchain is a mutually shared ledger of all transactions in a given transactional relationship. Combined with its consensus mechanisms and use of public key infrastructure (PKI) to verify and authenticate all changes made to the ledger, blockchain can enable the network itself to ensure trust among participants. The result: a whole new way to support distributed manufacturing across the value chain.

The Importance of Trust

Consider, for example, the ways in which blockchain can simplify how trust is developed within a manufacturing ecosystem. In the traditional manufacturing world, parties transacting with each other spend considerable time and money on establishing external mechanisms to ensure trust, in the form of contracts, service-level agreements, quality checks, inspections, audits, scanning, escrows and regulatory compliance reviews, to name a few. As the number of parties increases, so does the complexity. Reconciling separate ledgers, enforcing contracts, ensuring supply chain transparency and protecting intellectual property when multiple entities are involved are all laborious and burdensome processes, prone to error and vulnerable to fraud.

Related: Blockchain in Manufacturing: Enhancing Trust, Cutting Costs and Lubricating Processes across the Value Chain

Research shows that companies that build a culture of trust can fuel stronger performance by enabling departments to interact better and perform better across multiple dimensions. Establishing trust betweencontracted parties has similar positive effects. All these measures, however, amount to a costly “trust tax.”

For participants in a blockchain network – product designers, production shops, 3-D printers, logistics partners, sales and customer service  – that tax is greatly reduced. A secure, distributed ledger infrastructure accessible to multiple parties enables a new level of real-time transparency and efficiency for transactions involving the transfer of anything of value – whether that means ideas, money or ownership.

In our recent global study that included 281 manufacturing professionals, in fact, “trust” was a top driver for blockchain adoption.

Distributed Manufacturing Next in Line for Blockchain Innovation

Ensuring Transparency, Security, Auditability

Blockchain ledgers are:

  • Shared: Separate entities share a common source of truth.
  • Distributed: Blockchain relies on peer-to-peer collaboration, with no central ownership.
  • Secure: Cryptographic algorithms verify, authenticate and secure transactions.
  • Time-sequenced: Data is written consecutively and is time-stamped.
  • Immutable: Once written on the blockchain, data cannot be changed, tampered with or deleted.

Through smart contracts with supply chain partners on the blockchain network – programmed agreements that are independently verifiable and automatically executed when predefined conditions are met – companies can minimize human intervention and ensure performance transparency, transaction certainty and auditability.

[Download]: Blockchain in Manufacturing: Enhancing Trust, Cutting Costs and Lubricating Processes across the Value Chain

Within industries and even across interlocked, tiered manufacturing sectors, distributed ledger systems allow companies to develop new, platform-based process flows. A user might execute a smart contract for a custom-configured order, for example, combining designs from multiple sources. The encrypted design data would be recorded on the shared platform; materials and services could be autonomously sourced; and a shared factory could produce the customized product. Payments, including royalties to designers, would be issued when the product is delivered. A record of all transactions, from design selection to payment, remains on the blockchain.

A Rising Tide Lifts All Boats

Blockchain technology thus enables distributed manufacturing, offering participants unprecedented opportunities to develop new product and service lines, create new customer segments, enter new markets and find new ways to use and share assets:

  • Through supply chain transparency. All parties transact on a common platform, gaining real-time visibility into processes in the value chain, and simplifying materials sourcing and the interaction of design, manufacturers and other service providers. Supply chain processes, including payments and trade finance, can be streamlined and automated using smart contracts.
  • Through digital product memories. Immutable records of asset provenance, materials, production data, ownership and other data ensure authenticity and minimize transaction risk.
  • Through secure digital intellectual property. Parties to a transaction can be assured that their intellectual property is protected. Using blockchain to manage a contracted production run from a 3-D printer of ceramic components, for example, would allow a manufacturer to encrypt proprietary 3-D print files from end to end while creating an immutable history of the transaction. Similarly, escrows and royalty accounting would protect designers and other owners of IP.

There are many more circumstances in which adopting blockchain technology can deliver value. Participants can slash inventory costs and service times. They can eliminate reconciliation, and automate and speed financial and process flows. They can reduce manual interventions and reduce fraud. And they can create new ways to extend the lifecycle of products and optimize the use of assets.

What’s Next? Evaluating Readiness

As manufacturers move toward a shared and distributed model, business leaders can consider four questions when evaluating readiness:

  1. Where in the value chain, internally and externally, are we paying the highest “trust tax” in terms of excess cost, effort or lack of agility?
  2. How would the availability of a digital product memory drive value for our company, our customers and our business partners?
  3. Which types of partners, in what geographies and with what expertise, could we work with if transaction costs and efforts were lower?
  4. Which information assets (e.g., manufacturing, maintenance, operational and usage data) about our products could we monetize if there were a secure way to do so?

A blockchain-enabled, collaborative database is optimal for ensuring agreement between all participants in a value chain. It’s time for manufacturers to examine the implications for their business model. Organizations that gain hands-on experience with blockchain technology thorugh pilot projects will have an advantage as consortia start to form, and will be better equipped to lead the effort and make key decisions around structure and governance, prepare for the corresponding cultural shift, build skills and capabilities, and understand how it will impact business strategy going forward.

Get in the blocks. The race starts now.

[Download]: Blockchain in Manufacturing: Enhancing Trust, Cutting Costs and Lubricating Processes across the Value Chain

Olesya Gorbunova, a Senior Consultant in Cognizant’s Blockchain & Distributed Ledger Practice, contributed to this blog.

This article originally appeared on the Digitally Cognizant Blog

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Manufacturing

What you need to know if you’re attending MWC Los Angeles 2019

MWC Los Angeles 2019 is one of the newest and fastest growing events in the U.S. that brings together leading companies and influential experts from all sectors within the mobile technology industry to advance Intelligent Connectivity – a fusion of 5G, IoT, AI and Big Data.

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MWC Los Angeles 2019 is one of the newest and fastest growing events in the U.S. that brings together leading companies and influential experts from all sectors within the mobile technology industry to advance Intelligent Connectivity – a fusion of 5G, IoT, AI and Big Data.

The event is an opportunity to discover how leaders like Cognizant are looking into the future of connections, content and commerce.

To help you prepare, here is a selection of articles, case studies, ebooks, and clips from Cognizant, discussing digital transformation:

  • Learn Cognizant’s 4 key success factors to Industry 4.0 transformation. For starters, lead with strategy, not the technology. Watch the video here.
  • AI, Machine Learning, and IoT are ensuring the efficacy and efficiency of one of the most demanding engineering projects in the world. Learn how Cognizant helped Norwegian offshore engineering firm Kvaerner adopt these digital technologies.
  • The promise of Industry 4.0 is compelling, but for many traditional manufacturers, the reality is less than ideal. In this new Cognizant report, find examples of manufacturers that are navigating the shift.
  • It’s all about speed: Insight from Cognizant on how 5G will transform the business sector and create a leadership race for data intelligence.
  • Not all smart factories are created equal: Cognizant takes stock of the state of IoT intelligence, and what industrial organizations need to ensure both digital maturity and success. Read more here.
  • The many touchpoints of IoT connectivity allows AI to really shine, and prove its value to manufacturers in the form of proactive preventive maintenance, says James Jeude, VP in Cognizant’s Digital AI & Analytics Strategic Consulting Group, in this piece.
  • The human factor in IoT intelligence is key: Connected employees can “dynamically manage situations as they change,” explains Cognizant’s AVP of engineering and IOT solutions Phanibhushan Sistu.
  • The leap to IoT is a necessary one for your organization. This Cognizant ebook looks at 14 such businesses that jumped confidently into the digital future.
  • It took less than 12 weeks for Cognizant to implement an IIoT platform for a leading global industrial manufacturer. Get the case study here.
  • Without the duo of IoT and the Digital Twin, your organization is living in a black-and-white outlined world, in terms of operational intelligence. Color it in, get more accurate predictions, and fully realize potential.

One session to highlight? “5G and IoT – Understanding the Relevance to Your Business,” featuring Senior Director, Cognizant Digital Business, Prashanth Bhushan. This session will examine how the impending mass availability of 5G networks is set to mark a major step forward in extending 5G applications to various vertical industries and fields beyond traditional telecom and mobile internet.

MWC Los Angeles 2019 takes place October 22-24, at the Los Angeles Convention Center. 

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Manufacturing

IoT + PLM = Product Intelligence: An equation that delivers monetization opportunities

In the equation IoT + X = Intelligence, what role does product lifecycle management play as the X factor?

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Consumers are fickle. 

Today’s hot must-have can easily fade into obscurity tomorrow. Most products don’t even make it out to the playing field, and instead languish on the sidelines. The B2B world is not much different. Thanks to the Internet of Things (IoT) however, manufacturers are gaining a better peek at the product lifecycle beyond their distribution warehouse and leveraging that intelligence to their advantage.

Case Study: Advancing Smart Manufacturing Operations Value with Industry 4.0 Platform

PLM matters

More often than not, manufacturers make educated guesses at what consumers want. Sure they rely on surveys and calibrated focus groups but too often they’re still skating on thin ice with data snapshots. Product manufacturers rely on past sales records, future trend forecasts and hope design comes up with a nifty new gadget. They then execute strategic marketing and finally keep fingers crossed for best outcomes. 

The problem with such an iterative pattern is that the process is more or less opaque once the product leaves the manufacturer. Today’s product lifecycle management delivers much-needed transparency to the trail a product follows not just from concept and design and sales but on to how the consumer actually uses and disposes of it. 

And it does so through IoT. An IoT-embedded device relays product information to the mothership long after it has left the point of sale so manufacturers can gain insight into usage patterns and other data. While PLM has always followed the trail of breadcrumbs that products leave, IoT now allows for a longer and more useful trail. 

[Download]: A New Approach to PLM

IoT + PLM

“With IoT live product feedback has become possible. The [data] gap that existed between when we have sold a product and when someone discards that product…that gap has now been connected by IoT,” says Jagmeet Singh, Director, Connected Products, at Cognizant. 

Businesses use cloud technologies to analyze the data that IoT-embedded products spit out and reap a whole host of benefits. Manufacturers access instant feedback about feature design – in an age of user-centered design, this is a big deal – and price points. Product design now needs fewer reboots and manufacturers can produce with more confidence.

The introduction of IoT and associated data analytics expanded the use of Product Data as a Service (PDaaS), where larger sets of metadata about products are now available to be harvested, right from raw materials used, to manufacturing processes to quality control and beyond.

Simply by following the IoT trail (and obtaining all-important user permission), manufacturers can monetize information about product usage to secondary vendors who might benefit from related information. A computer manufacturer, for example, can sell valuable information about the heat exchanger, the battery, the Bluetooth connection to satellite providers who can use this as intelligence for their own sales and marketing promotions.

IoT breathes new life into PLM extending the line beyond the four walls of the warehouse to the real world where live data from every user shapes future product iterations.

IoT + PLM = Customer intelligence. With sharper data based on usage patterns, manufacturers can anticipate customer needs better and deliver they want. The result is more revenue and less waste. IoT lets PLM realize its full potential.

[Download]: Advancing Smart Manufacturing Operations Value with Industry 4.0

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IoT + Big Data Analytics = Operations Intelligence: An equation that draws a better picture

In the equation IoT + X = Operations Intelligence, what role does big data analytics play as the X factor?

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Global pressures to decrease energy consumption and the speed of business are accelerating the call for new ways of delivering efficiencies. 

What if a fridge could tell us that the food it stores was going to spoil in a day? What if buildings could cut down heating costs by selectively turning down the heat depending on occupancy? For a fridge to “talk” in this way, it would need a way of measuring the parameters that indicate data spoilage. The Internet of Things (IoT) delivers just that.

Case Study: Advancing Smart Manufacturing Operations Value with Industry 4.0 Platform

With IoT, everyday “things” such as refrigerators, machines, warehouses, televisions, washing machines, broadcast data about their health through outfitted chips and sensors. So large is this data deluge, that the IoT market is expected to grow at an astonishing 24.7% and reach $1111.3 billion by 2026.

Big data analytics

We need big data analytics to harvest this torrent of IoT information in useful ways. Simply spitting out data is not enough, big data analytics help companies make sense of the data and thereby deliver intelligence.

The classic definition of big data is that it presents in three “Vs”: large volumes, variety and high velocity. So the concept of big data is not new, even if this set of parameters has evolved since the early 2000s when it first took root. The introduction of IoT, however, has increased the number of sources which contribute to the data dialog. Whether or not these data points contribute to a symphony or merely create a cacophony depends on data analytics.

Case Study: Advancing Smart Manufacturing Operations Value with Industry 4.0 Platform

“Big data provides context to a world in which IoT is working,” says James Jeude, Vice-President and Practice Leader of Cognizant’s Digital AI & Analytics Strategic Initiatives Group. “As an industry we have solved the volume problem [of big data], where today’s big data really matters is that it delivers on variety. It is variety that really matters [for intelligence] at this point.” 

Take the example of a refrigerator in a grocery store. To know when the compressor is about to break, the store can measure both the refrigerator temperature and the current input. The higher the electric current flowing to a refrigerator to maintain the same temperature, the more likely it is to fail. These two indicators might be the canary in the coal mine but IoT and Big Data allow a variety of additional efficiencies. Measuring the gases emitted by the food can be a window into when the food might spoil; measuring outside temperature and humidity might tell us acceleration patterns of food spoilage. The number of times a grocery store refrigerator is opened and closed is also a useful parameter to measure.

Case Study: Advancing Smart Manufacturing Operations Value with Industry 4.0 Platform

The promise of big data analytics is that it allows a whole new range of IoT variables to participate in the conversation. 

IoT facilitates information gathering from more sources so everyone who contributes to a situation gets a hand at the table. Data analytics leverages this IoT data to deliver a more comprehensive picture of the situation. The net analysis is more nuanced and more valuable. Indeed IoT + Big Data Analytics = Valuable Intelligence. 

With IoT and big data analytics, you no longer  have to picture an elephant by merely touching its ears and tail. You can now access more touchpoints to visualize the whole animal.

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1 download. 14 Case Studies.

Download this report to learn how 14 companies across industries are demonstrating the reality of IoT-at-scale and generating actionable intelligence.

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