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How industrial manufacturing gets smarter with sensors

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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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Don’t forget the human factor in IoT’s service intelligence equation

Overlooking the human element of IoT can leave money on the table.

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Automation is a powerful lure for businesses investing in the Internet of Things (IoT). Smart devices feeding real-time data to algorithms can find hidden problems, identify efficiencies and circumvent human error. In short, smart automation can save companies a lot of money. But the IoT conversation shouldn’t focus exclusively on automation. 

Overlooking the human element of IoT can leave money on the table. Empowering employees with effective access to intelligence can improve customer service and differentiate a company from its competitors.

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

For Phanibhushan Sistu, good service intelligence relies on a robust data infrastructure for employees. Sistu is AVP of engineering and IOT solutions at Cognizant. He says that while many companies have already invested in connected devices, “not all of that information is available to the person who is going to a location from the service point of view.”

To illustrate his point, Sistu uses a telecommunications provider as an example of what’s possible. 

This type of business often relies on a fleet of full-time and contracted service technicians who prioritize a daily list of house calls. A pre-IoT business may provide these technicians with a description of a problem as called-in by the customer, but little else. Diagnosis doesn’t really start until the truck pulls up, and anyone who’s heard “I don’t have the right part for this” knows the flaws in this system.

“Their front-end employees cover multiple locations, which comes with a cost,” Sistu says. 

“Somebody goes in to fix a problem or install something, then doesn’t learn until they arrive that they don’t have the right equipment or that a problem was misdiagnosed.”  

[Download]: Real Estate Manager Goes Digital

A modern telco with properly managed data can track how customers are using their hardware, index common complaints and analyze how its different hardware products perform. Put into the hands of front-line staff, this becomes a competitive advantage.

A connected employee can “dynamically manage situations as they change,” Sistu says. Smart data can tell service techs whether other customers in an area have had similar complaints or how a customer’s usage might have affected the product. Even seeing other technicians nearby through real-time tracking can make getting parts easier. By bringing the right diagnostic tools and replacement components, service calls can be resolved faster and more effectively.

[Download]: A New Approach to PLM

And accessible data infrastructure can do more than save costs, Susti says. It can also be a revenue generator. 

“Maybe as an enterprise, I have different levels of services I provide — diamond, gold, platinum or whatever. On the fly, I may decide to redirect my technician to attend to a diamond customer because my [service-level agreement] for them is more rigorous. It’s about dynamic planning, dynamic optimization.”

Of course, Sistu says these principles extend to a wide range of business sectors that have front-line staff dealing with customers post-purchase — from manufacturing to medicine. 

Now that IoT has extended customer success management further beyond the date of purchase, companies must ask how customers are experiencing a product’s “life service.” With proper data infrastructure, long-term service agreements can shift from cost centres to selling points.

“I believe this kind of experience always commands some premium,” Sistu says. “People probably don’t mind paying a few extra pennies or dollars for a better experience.”

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5G investment key to untethering IoT intelligence for manufacturers

5G’s lighting-fast speeds will reshape consumer expectations for entertainment, shopping and social connectivity.

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Manufacturers are starting to understand just how much business intelligence is possible with the Internet of Things: Connected devices streaming reams of valuable data to algorithms that, in turn, learn how to spot trouble before it happens. Every step of the process — from manufacturing to product service — can benefit from smart devices communicating in real-time.

But even businesses using the fastest 4G networks are starting to question that oft-used term: “real-time.” 

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

4G can support approximately 2,000 devices per square kilometer, and as mobile devices proliferate those boundaries are under stress.

But there are promising solutions on the horizon. The cutting edge, often-hyped 5G network tech currently being rolled out and tested by global telcos is poised to become essential to leveraging business intelligence. 

Its technical details are complex, but 5G is, simply put, faster and better. It’s projected to support one million devices per square kilometer. Downlink speeds are spec’d at 20Gbps, and latency (how long it takes data to travel from A to B through a network) is expected to max out at four milliseconds versus 4G’s 20 milliseconds. 

[Download]: Real Estate Manager Goes Digital

Even though widespread 5G connectivity is still a few years away, Sharath Prasad says many manufacturers are trying to gauge their investment in the space. As Cognizant’s connected products portfolio lead, Prasad says “the pervasiveness of 5G, the cost of 5G and its adoption rates can all drive operational intelligence.”

Vivek Diwanji, senior director of technology at Cognizant, says this shortened latency is the real potential benefit to IoT-enabled businesses. “5G and edge devices are where the overall story is going to change in terms of the way data will be consumed, analyzed and leveraged,” he said.

So what does this mean for manufacturers? A number of things:

If a connected manufacturing device senses a problem on the line, for example, getting shut-down instructions in four milliseconds instead of 20 could save thousands of dollars in faulty product coming through the pipeline. 

The value of IoT doesn’t always end inside the factory walls. Once some connected products leave the factory — an automobile for example — and deploy into the field, 5G connectivity can feed product engineering teams with more data and insight on how a product functions on the — traditionally — dark side of the moon.

The list of benefits of 5G is long.

“I think that’s going to be the bigger impact of 5G overall,” says Diwanji, “not only as a backbone for infrastructure, but from the overall customer experience standpoint.”

[Download]: A New Approach to PLM

Relying on telcos to deploy 5G at scale may be a waiting game, but manufacturers can also outfit their own facilities with 5G networks to reap benefits today.

Prasad says groups such as CBRS (Citizens Broadband Radio Service) are working to expand 5G capabilities into existing mobile network technology thanks to recently released radio spectrum

With some hardware investment, he says manufacturers can set up their own 5G-based network using the CBRS’s framework and “actually do away with dependence on a carrier … Even if factories are located in remote areas without reliable wireless connectivity, they can actually set-up a CBRS-based 5G network just to cover their factory and provide good quality connectivity there without having to shell out a huge cost to carriers.”

5G’s lighting-fast speeds will reshape consumer expectations for entertainment, shopping and social connectivity. So too will it reshape the business sector. In a world where one company’s “big data” intelligence is pit against another’s, speed will define market leadership. 

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Seeing robots and digital advancements through someone else’s eyes

When they run the highlight reel of my greatest dad moments, this weekend’s dinner conversation with my kids will definitely be left out.

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By Randal Kenworthy

When they run the highlight reel of my greatest dad moments, this weekend’s dinner conversation with my kids will definitely be left out – the look of terror in their eyes, the curious and confused look of my wife that said it all: “What are you thinking?!”  At that moment, I realized the future of robots, AI and the latest digital technology can be a scary concept – if poorly explained.

It started nicely enough, talking about how Mother Nature and natural selection are things of beauty. But I strayed a little off topic when I explained that in the not-so-distant future, parents could apply emerging technologies to design their babies – and that this was not necessarily a good thing.  When asked why, I described a future where all babies were basically all programmed preconception, and eventually we would all look like engineered humans – not unlike robots.  That’s when the tears started.

My 10-year-old daughter provided me with an escape hatch when she asked, “Are we all going to become robots?” At that point, I channeled my inner Malcolm Frank (a top Cognizant exec and co-author of Code Halos and What to Do When Machines Do Everything) to help address her fear.  I explained that robots were actually a good thing – that they weren’t going to actually replace us but rather supplement our day-to-day activities.  We talked about examples like autonomous cars.  She built on my point that not only will self-driving cars enable us to do higher-value activities but they’ll also make driving a lot safer.

[Read more: The State of the Union for IoT Intelligence]

Personalizing the Pursuit of Digitally-Enabled Productivity

This dinnertime exchange sums up what those of us at the intersection of business and technology deal with every day, whether we know it or not. Because not everyone is comfortable with advances in digital technologies, it’s essential to explain the value of technology in personal terms.  The work we do is often complicated and technical, but when you peek under the covers at the value organizations are achieving, even a 10-year-old would nod in approval.

By telling compelling stories about demonstrated business results, our industry can make the latest digital tools and techniques a lot less scary for the people who need to invest in and implement them. Consider:

  • Product intelligence: By integrating data and applying intelligent algorithms, we helped a multinational consumer goods company create a 360-degree, omnichannel product view.  Doing so helped increase customer conversations by 15%, significantly improve customer satisfaction and boost agility of global product launches by 40%.
  • Connected factories: We also worked with a global pharmaceutical company to build a predictive maintenance model for its distributed and connected manufacturing plants. This capability harmonized processes across multiple systems and provided visibility into potential process interruptions. By reducing downtime, the business realized a 20% increase in throughput while increasing safety, enabling patients to get their medications more quickly.
  • Intelligent process automation: We used machine learning models to help a global insurance provider expedite its worker’s compensation claims process. The solution determines bodily injury information with 90% accuracy, aided by human validation. It’s also integrated with existing robotic process automation (RPA) tools to navigate multiple mainframe and web applications and apply hundreds of business rules to enable timely and accurate registration of claims. The business has achieved greater claims accuracy and accelerated claims processing, enabling workers to get the money they need to achieve a speedy recovery and return to work, which improves productivity.

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

The ABCs of Clear Communication

We can all benefit from remembering some basic talking points when we engage in discussions about AI, machine learning and other digital technologies – whether it’s with our business peers and colleagues or our families. In short:

  • Keep it simple: Speak in plain terms.
  • Tell stories: Use examples and stories to explain a topic and gain alignment.
  • Stay practical: Business people often talk about technology in mythical proportions. Be pragmatic about what technology can do; avoid pie-in-the sky illustrations.
  • Don’t assume: This is a two-way street. Your own assumptions may need validation, and don’t assume your listener knows what DevOps means.
  • Repeat as needed: Technology can be complex, so repetition can help ensure that complex concepts are truly understood.
  • Break down an explanation: The human mind can better understand when information is provided in manageable, logical buckets. Minto’s Pyramid Principle is built on the concept of chunking information in manageable pieces.  The same applies here.  Take a message and break it into logical components.

With all that AI and other digital technologies have to offer, it’s essential for those with insights into its potential to diminish the fear, uncertainty and doubt that often accompanies the topic – rather than inadvertently emphasizing it. Believe me – that’s what I’ll remember the next time I bring up current events at the dinner table.

[Download]: Designing Manufacturing’s Digital Future

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