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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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Manufacturing

What you need to know if you’re attending AVEVA World Summit

AVEVA World Summit is where the most innovative industrial executives from around the world gather for an exclusive opportunity to network with 400 global digital leaders across diverse sectors. 

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AVEVA World Summit is where the most innovative industrial executives from around the world gather for an exclusive opportunity to network with 400 global digital leaders across diverse sectors. 

The summit is an opportunity to discover how these leaders and Cognizant — a Platinum Sponsor — are transforming the entire asset and operational lifecycle.

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.

Aveva World Summit takes place September 16-18, at Marina Bay Sands, Singapore.  

One session to highlight? “Digital Transformation in Hybrid Industries,” featuring Cognizant’s VP of IoT and Engineering services, Frank Antonysamy. This session will examine the benefits of digital transformation, and addressing challenges through a sustainable platform that can adopt best practices, continuous improvements, and grow with the business.

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Manufacturing

IoT + Digital Twin = Operations Intelligence: An Equation that Delivers Useful What-If Scenarios

In the equation IoT + X = Operations Intelligence, what role does a digital twin play as the X factor?

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Measure twice, cut once. This basic premise, that it would be advantageous to visualize outcomes before you act, forms the backbone of an entity known as the digital twin. This approach is particularly useful in today’s high-stakes industries such as manufacturing, construction, mining and more. Measuring twice and cutting once allows enterprises to tweak every aspect of the production process to maximize revenue.

The digital twin enables companies to envision what-if scenarios for various operating conditions in the virtual world before it affects processes in the real world. The more fully the digital twin avatar is fleshed out, the more accurate its predictions. This means enterprises need IoT (the Internet of Things) to color in the picture completely. IoT helps the digital twin realize its full potential to deliver operational intelligence. 

The promise of the digital twin

A digital twin is a replica, described by data, of physical assets, processes and systems that helps organizations understand, dissect, predict and optimize their performance. It can combine design and engineering details with operating data and analytics about anything from a single part to multiple interconnected systems to an entire manufacturing plant.

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

If you need to describe a physical asset (say a motor running on a shop floor) through data, you need that motor to both generate data and make that data easily accessible. This is where IoT falls into the picture: it “sensorizes” a variety of physical machines and brings them into the digital twin conversations, says Vivek Diwanji, senior director of technology at Cognizant. IoT-enabled embedded devices can then transmit data about their health under a variety of operating conditions and channelize that information through an Internet connection from shop floor to enterprise resource planning (ERP) software. 

Layered possibilities

A digital twin is about different perspectives – essentially comprised of many layers that are progressively overlaid with more detailed data input. The level of detail depends on the insights you’re looking to derive. If you need to know when a vehicle tire is going to wear-out, all you need to measure is temperature and air pressure. Long-term durability intelligence on the other hand, also needs to measure ambient conditions, daily operation numbers, road type and more.

[Download]: A New Approach to PLM

A lack of common IoT standards across industries makes the data difficult to gather, but that conversation might change with the advent of 5G, Diwanji predicts. For now, digital twin is a powerful tool that enables companies to deliver field services, conduct smart operations and evaluate product development outcomes before investing millions into the pipeline.

By 2020, 30% of Global 2000 companies will be using data from digital twins to improve product innovation success rates and organizational productivity, according to IDC. They can realize gains of close to 25%. And IoT is a key player in that equation to deliver such operational intelligence.

“Digital twin is an application that leverages IoT. The very definition of a digital twin necessitates that a digital model is running in conjunction with a physical model. That connection, between the physical and the digital, happens through IoT,” Diwanji says. “IoT is really the backbone of the digital twin.”

[Download]: Real Estate Manager Goes Digital

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IoT + AI = Operations Intelligence: A new equation for a new world of data

In the equation IoT + X = Operations Intelligence, what role does artificial intelligence play as the X factor?

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A new world powered by the Internet of Things (IoT) demands a new computing paradigm and yesterday’s if-X-then-Y rules-based approach can’t handle today’s industrial complexities. 

IoT-embedded devices generate large amounts of data, but analyzing that volume of information using traditional algorithms can be overwhelming, like drinking water from a fire hose. We need more intelligent computing that can take on both volume and ambiguity — in context and in real time. Artificial Intelligence can be one of the special X factors in the equation, IoT + X = Intelligence, and it learns by example rather than by rules.

The IoT-AI dance

At first glance, it might appear that a rules-based process might work well enough for a solitary IoT-enabled device: monitor the temperature profile of a motor; if it overheats beyond a preset limit, turn it off. However, the real world in which such machines operate is much more complex and you need to parse interdependent signals at the edges to truly make sense of the data being fed to you. For example, air temperature, paint temperature, and humidity in combination may lead to warranty claims in complex combinations that exceed our ability to use traditional data science. AI can help. 

In that sense, AI is IoT’s ally. It tolerates ambiguity at the margins, meaning analysts don’t have to tie up precious capital resources just cleaning and formatting data so it can play well with existing algorithms. While it is popular to declare that the “garbage in, garbage out” theory holds true in data analytics, the good news is that AI can detect outliers and tolerate bad data up to a point, says James Jeude, Vice-President in Cognizant’s Digital AI & Analytics Strategic Consulting Group. “I believe that AI takes our best human thinking and allows us to duplicate it at scale and at low cost and push it into all corners,” he adds

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

IoT’s myriad touchpoints allow AI to prove its value, says Jeude. One of the many use cases of AI is proactive preventive maintenance. If you were to outfit every grocery store refrigerator with IoT sensors that measured current flow and temperature, AI could proactively predict compressor failure, delivering intelligence that can be acted on and saving revenues in the long run., catching failures well before the actual temperature rises and triggers an alarm.

“Humans have a limited ability to process complexity. IoT and AI are absolutely essential together to deal with that complexity challenge,” Jeude says.

Evolutionary AI

Previous iterations of AI founded on deep learning involved training algorithms on vast banks of test cases so the machines would lean on learned experiences to make informed decisions. Such AI is time and resource-intensive and doesn’t allow for flexibility at the edges. 

Evolutionary AI, on the other hand, allows for economical testing of corner cases. It factors in historical context, decision and output data before prescribing actions. “We can use evolutionary AI to drive iterations and pick the ones that are the winners and help us prune the losers,” Jeude says.

[Download]: Real Estate Manager Goes Digital

The very fact that IoT combined with AI creates intelligence is predicated on the fact that the cost of computing has decreased significantly. Equally important, Jeude points out, is that the ability to put decisions into effect has also become cheaper. Both have fallen by an order of magnitude every decade. “That IoT device can shut off a machine, call for repairs, flash warning lights, for a fraction of the cost,” he says.

IoT with AI delivers intelligence by processing volumes of data in real time and in context at complex scales humans can’t work with. With IoT and AI we are well-informed to make critical decisions right at the moment when they are needed the most. In today’s high-stakes digital landscape, that can make all the difference. Whether you’re working in retail, entertainment, manufacturing, finance, mining or countless other industries, IoT in concert with AI can deliver the transformational intelligence you need at scale.

[Download]: A New Approach to PLM

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