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How industrial manufacturing gets smarter with sensors

Cognizant

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Today’s manufacturers are on the cusp of a fourth industrial revolution, in which internet-connected sensors (aka, the Internet of Things, or IoT) make physical machines and objects more intelligent. To realize the promise of industrial IoT, however, companies must combine operational technology with enterprise IT, and collect and analyze data across the entire manufacturing ecosystem to generate actionable and valuable insights.

By doing so, manufacturers can better manage production, address customization requirements and add value. In turn, they can more intelligently manage their businesses, improve response time, promote innovation, reduce costs and boost revenues. In our view, here’s how forward-thinking executives should be thinking about the opportunity.

The Future Has Already Arrived

Rolls-Royce has built engines since 1915. Today, however, the fabled company sells a whole lot more than just engines. In an industry where fuel savings can add up to millions each year, Rolls-Royce now provides airlines with information to help optimize routes, altitude, airspeed, weight and freight – this in addition to supplying the engines themselves. Along the way, Rolls-Royce engineers learn how its engines perform in a range of conditions, which they then use to inform the design of their next generation.

Related: Stepping into digital with IoT – 14 Case Studies

In short, Rolls-Royce exemplifies the opportunities and benefits of industrial IoT. And this iconic company is not alone. Shell Oil is pioneering simulation technology to help oil and gas operators manage offshore assets, improve worker safety and better predict maintenance. Stanley Black & Decker is already adding digital technologies to its entire line of customer tools, hydraulics, fasteners and electronic security devices.

All told, the list is long and diverse, covering equipment manufacturers, pharmaceuticals companies, medical device manufacturers and many other sectors. According to a recent MPI study, which surveyed 350 manufacturers, almost two-thirds (63%) believe IoT will have measurable impact on their business in the next five years. By 2020, IDC predicts that 50% of the Global 2000 will depend on digitally enhanced products.

This is because industrial IoT promises a single view of analytical data to operate with real-time agility and quickly respond to adverse events within the plant or supply chain. This requires integrating and consolidating enterprise and operational applications, however, which have largely remained isolated from one another. Until now.

[Download]: Stepping into digital with IoT – 14 Case Studies

Beyond connecting devices to a network where they interact and exchange information, the real value of industrial IoT lies in the data generated from these important relationships. Unlike traditional software applications, industrial IoT is rooted in physical space — integrating data from digital devices and systems in factories and supply chains with enterprise assets. It enables enhanced monitoring, data gathering and integration, role-based information presentation and situational awareness reports for operators. The objective is to convert operational data into insights that inform decision-making, drive innovation and realize greater efficiency.

Getting Started with the Right Questions

That said, many manufacturing leaders already recognize the need for industrial IoT. They struggle, however, with the complex and siloed landscape of their manufacturing landscape, including processes, IT and operational technology. To that end, we advise decision-makers to conduct a self-assessment and organizational readiness analysis by answering the following questions:

    • What changes do we need in our business processes, operations, people and business models to respond to rapid market changes, new developments and emerging technologies?
    • What kind of talent do we need?
    • Where can our organization benefit most from a deeper understanding of operations and efficiency?
    • How can we assess our readiness for an IoT transformation, and how should we benchmark our peers?
    • What budget should we set for additional computational capacities, and for security and storage capabilities?
    • What is preventing us from a transformation? Legacy systems? Cost pressures?
    • Besides cost, what internal barriers do we need to overcome?

To help with those answers, leadership must compare approaches, examine the readiness of its technical architecture, understand the organization’s capacity to change, and review available case studies. They must also engage with partners with the required domain expertise as well as hands-on experience in deploying industrial IoT technologies. In our experience, successful journeys take manageable steps such as designing and installing sensor technology; implementing faster and more efficient interconnectivity between the enterprise, business units and production facilities; developing analytics; and piloting use cases that not only demonstrate the promise of the industrial IoT but also realize its value at scale. In proceeding this way, manufacturers develop and grow the talent, skills and tool-sets necessary to build a connected ecosystem that seamlessly integrates digital, operational and information technology.

[Download]: Stepping into digital with IoT – 14 Case Studies

Organizations that align both IT and operational technology to create a “system of systems,” instrumenting every device in the extended manufacturing ecosystem, will be best positioned to harvest meaningful data at every touchpoint. Only then will manufacturers be able to benefit from the improved yields, additional value and greater efficiency that industrial IoT can produce.

This article originally appeared on Cognizant.com

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Manufacturing

Improving working conditions with blockchain

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Blockchain is more often spoken about as an external tool for businesses to help secure supply chain. In a new pilot, blockchain is to be used to help improve health and safety within the workplace – at a Levi Strauss factory.

The testing out of blockchain as an internal health and safety auditing tool is being run as a collaboration between Harvard University’s public health graduate school, U.S. think-tank New America and the U.S. denim jeans company Levi Strauss & Co. The three have declared a project to design, build and operate a blockhain-based system for health and safety at work.

The new technology will be designed to augment outside auditors of factory health and safety with a system that will allow factory workers to self-report issues of concern. The factories that will test out the technology are based in Mexico, where three manufacturing sites in total employ 5,000 workers.

Mexico’s regulations for health and safety laws are exclusively federal in content. Under this legislation employers must obey standards, maintain safety programs, maintain compliance systems, ensure proper equipment and hazardous substance control. However, the level of safety is often subject to criticism (as with the International Labor Organization), such as in terms of accident rates and occupational illnesses like respiratory diseases.

The new project is designed to provide an alternate avenue for worker health and safety to be addressed, outside of periodic audit, and the mechanism enables a U.S. based company to ensure that clothes manufactured for the U.S. market are produced under conditions that are safe for workers.

The aim of the scheme is to input an annual worker survey on the blockchain. Once inputted the company’s site-based managers will be unable to alter it, and the findings will be made available to the workforce. The findings will be available for Mexican authorities to review as well as U.S.-based Levi Strauss managers. The blockchain will be provided by ConsenSys, the blockchain company founded by Joseph Lubin, once of Ethereum.

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Tesla wants its factory workers to wear futuristic augmented reality glasses on the assembly line

Business Insider

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  • Tesla patent filings reveal plans for augmented reality glasses to assist with manufacturing.
  • Factory employees has previously used Google Glass in its factory as recently as 2016.

Tesla‘s Model 3 might have “biblical simplicity” according to one Wall Street analyst, but building any car still involves hundreds of nuts, bolts, and welds.

To cut down on the number of fit and finish issues — like the “significant inconsistencies” found by UBS— Tesla employees on the assembly line could soon use augmented reality glasses similar to Google Glass to help with car production, according to new patent filings.

Last week, Tesla filed two augmented reality patents that outline a futuristic vision for the relationship between humans and robots when it comes to manufacturing. The “smart glasses” would double as safety glasses, and would help workers identify places for joints, spot welds, and more, the filings say.

Here’s how it works:

Tesla/USPTO

And here’s the specific technical jargon outlining the invention (emphasis ours):

The AR device captures a live view of an object of interest, for example, a view of one or more automotive parts. The AR device determines the location of the device as well as the location and type of the object of interest. For example, the AR device identifies that the object of interest is a right hand front shock tower of a vehicle. The AR device then overlays data corresponding to features of the object of interest, such as mechanical joints, interfaces with other parts, thickness of e-coating, etc. on top of the view of the object of interest. Examples of the joint features include spot welds, self-pierced rivets, laser welds, structural adhesive, and sealers, among others. As the user moves around the object, the view of the object from the perspective of the AR device and the overlaid data of the detected features adjust accordingly.

As Electrek points out, Tesla has previously been employing Google Glass Enterprise as early as 2016, though it’s not clear how long it was in use.

Tesla has a tricky relationship with robotics in its factory. In April, CEO Elon Musk admitted its Fremont, California factory had relied too heavily on automated processes. Those comments, to CBS This Morning, came after criticism from a Bernstein analyst who said “We believe Tesla has been too ambitious with automation on the Model 3 line.”

Still, the company seems to be hoping for a more harmonious relationship between human and machine this time around.

“Applying computer vision and augmented reality tools to the manufacturing process can significantly increase the speed and efficiency related to manufacturing and in particular to the manufacturing of automobile parts and vehicles,” the patent application reads.

 

This article was originally published on Business Insider. Copyright 2018.

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Manufacturing

Dow Chemical envisions the future of manufacturing

Dow Chemical, one of the world’s biggest chemical producers, is taking a leadership role in the digital transformation of its industry.

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Despite its foundation in the pure science of chemistry, the chemicals manufacturing industry doesn’t exactly conjure high-tech images when people think of what goes into making chemical products.

And yet, the chemicals industry is poised to be the poster child for the very high-tech Industry 4.0 revolution, which takes existing manufacturing processes, and infuses them with digital DNA, thanks to the IIoT.

Dow Chemical, one of the world’s biggest chemical producers, is already taking a leadership role in the digital transformation of its industry. “We have significant amounts of data from our instrumentation and process sensors to use with the new analytics and deep-learning technologies,” Billy Bardin, Dow’s Global Operations Technology Center director, told Chemical Engineering.

Related: Stepping into Digital with IOT – 14 Cases

Dow, like many other chemical companies, has been using sensor tech for decades, but the IIoT represents an entirely new model for how data from these sensors becomes part of the company’s end-to-end process. Not only does the IIoT offer optimization of the production process, it can improve efficiency, while reducing both energy consumption, and operational cost.

Safety — a key consideration given the stakes — can also be improved. Many chemical producers, including Dow, are still manufacturing at facilities that date back 50 years or more. Modernizing these plants is a constant effort, but with the advent of the IIoT, gains in situational awareness accompany the gains in efficiency and productivity.

[Download] Stepping into Digital with IOT – 14 Cases

Recently, the company enlisted the help of Schneider Electric to digitize its Carrollton, KY processing plant, giving teams better data visibility for pumps, valves and motors. The roadmap also includes the addition of Schneider’s HART devices to enable operations and maintenance teams to remotely view equipment health or thresholds for valves in order to manage them better, according to Automation World. The improvements in preventative maintenance this data enables are key to better employee safety, as well as protecting the environment.

Better efficiency, cost savings, and greater safety? Strong arguments for better chemistry through digitization.

[Download] Stepping into Digital with IOT – 14 Cases

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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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