Jim Lawton

This space has been dedicated to exploring the ways in which robots are acting as change agents – of the category and of manufacturing. There’s a lot to be said for the ways in which those transformations are taking place now, and it’s all good. There’s a case though, that what lies ahead for robotics in the Industry 4.0 or the Industrial Internet of Things (IIoT) is where real excitement takes place. In the IIoT, robots that combine mind and machine change the ways in which goods are produced, and the entire business of manufacturing.

In the IIoT, agile factories are driven by “big data” – including quality metrics, market feedback, and real-time demand signals. In these factories of the future, the production floor is linked to the back office which is linked to the customer and suppliers. The flow of information between these centers will make business move more quickly, efficiently and profitably, because they will sense, respond and act more quickly to shifts in market conditions, customer demand and internal variability.

Achieving the aspiration is daunting. It can be disrupting – and not in a good way. We know of one company that invested $1 million in IIoT and then came to realize that they were collecting the wrong data. Another shared that his executives were very excited and pressing hard on the effort to deploy “big data” but when asked what they planned to do with the data, the response was a shoulder shrug and a quiet “I don’t know.” That won’t fly. For companies who make things, the manufacturing process is the lifeblood of the business. It needs to run every day and deliver results. Manufacturers must have a risk-mitigated way of leveraging modern technologies and smart, collaborative robots are the answer.

Building the IIoT from the Bottom-Up

This is where behavior-based robots come in. Capitalizing on the perfect storm of low-cost sensors, devices, processing power, data storage, connectivity and ways to handle big data, these robots make it possible to start with a single work cell, without needing to make significant changes to the environment. The model is based on organic growth; manufacturers can add more to the work cell, and then add more work cells. Once a work cell is running, manufacturers can use native performance and task data collection and introspection to provide on-the-fly task tuning and Cloud-based cognitive insights. It starts small with localized awareness, such as “the part isn’t there anymore, do something smart.” It will grow, enabled by the Cloud’s connectivity, process computation at a vast scale, deep learning and other advanced analytics to aggregate data with other structured and unstructured data and share learning with other robots within and across other factories.

By design, it allows an organization to safely deploy new technology, learn from the experience and modify the subsequent actions based on the learning. There is no big bet required. This is good. Manufacturers can’t wait for the end of huge implementation to see value – it has to be created all along the way.

Building the IIoT from the bottom-up represents a huge departure from the top-down, multi-year, multi-million dollar implementations of traditional industrial robots. More importantly, it allows manufacturers to build operations where productivity and capacity increase and costs are lower. As robots grow “smarter” they will accelerate our ability to drive more from every aspect of the business because we’ll be more agile and more able to meet customers where they are. Where do you see robots adding value to the business overall? Share your ideas with me @jim_lawton.

Originally published on Forbes.

In my last post on robots as agents of change, I looked at the ways in which collaborative robots are changing industrial automation. But changing automation is only the beginning.

Robots will transform manufacturing in ways that have not been seen since the last industrial revolution. And they will do more than just play a part in the changes that are coming. They will, in many ways, be the catalysts and enablers of a new age in manufacturing: the agile factory.

Manufacturers need these robots and the changes they make possible. Why? For the past 100 years, factories were designed to efficiently execute a plan. Make a plan. Execute the plan. But the real-world of the factory floor never works like the plan expected it to – suppliers miss delivery deadlines, equipment fails, yields fall short of the target. In any plant, there are scores of people who spend their days addressing all of the deviations from the plan. This system is flawed. It is hugely wasteful. I know. I lived it for years.

What’s needed? Lora Cecere, a friend and one of the brightest influencers in the supply chain space, has been writing and talking about supply chain response for many years. Her LinkedIn Pulse post addressed the future state of supply chain excellence where supply chains are able to sense and respond to fluctuations in demand. She’s onto something and I’d take her argument one step further. The ability to sense and respond – not just to demand shifts, but also to potential “gotchas” like process variations, quality issues or production bottlenecks –needs to be part of factory DNA as well.

Breaking Through: Robots with Grit

There’s a lot of talk today about “grit” – a simple word that conveys tenacity and perseverance. We recognize it as a characteristic that enables humans to succeed. As robots take their place in the workforce, grit will be essential for their success as well.

Yes. Robots will need grit and here’s why. Consider what it takes to give walking directions in a large city: you’re not likely to know every obstacle they might encounter – closed sidewalks, deliveries blocking the path, etc. Your instructions won’t include “jog left at this doorway to go around the pallets of produce” or “step to the right to avoid an open manhole.”

Like that person trying to navigate Manhattan, robots that work in manufacturing need to be able to persist in the face of obstacles. But since traditional robots need “a map” that programs every step they need to take in order to do even the simplest of tasks, they can’t operate in the ways manufacturers need them to.

Everything they need is gleaned from the input of the robot’s sensors; the robot uses that information and cognitive computing to adjust its actions according to the changes in its immediate environment. Robots driven by behavior show more biological-appearing actions than their rules-based counterparts. It will recognize a flaw in the process – a misaligned part for example – and adapt to ensure that the workflow continues. That’s a robot with grit.

This new generation of robots – self-configuring, self-optimizing and self-healing – will be able to identify anomalies and adjust manufacturing processes in real-time. With these robots, manufacturing operations will become more agile and less brittle in the face of normal variation. They will make it possible for manufacturers to quickly understand what’s happening, accommodate change and variation, and keep the production lines running every day to deliver results.

We’re just at the beginning of this transformation, but it’s picking up speed. Companies like Jabil, GE and Wasion are demonstrating the potential and documenting the results. How do you define the agile factory? What are you doing to build your factory of the future? Share your experiences with me @jim_lawton.

Originally published on Forbes.

There is a lot of hype about how the Industrial Internet will transform manufacturing. At its simplest, the vision comes to life at the intersection of connected sensors and machines and software-enabled intelligence. The combination promises to deliver what manufacturers care about most: greater productivity, lower costs, faster innovation cycles, world-class quality and more flexible and responsive supply chains.

Today’s factories are already filled with equipment — including robots — that monitor and collect all kinds of data. Manufacturers love to measure things: productivity, cycle time, pass/fail rates, the list goes on. Increasingly, there’s data coming from other sources as well, including unstructured content like social media, images, and customer support call transcripts.

What is needed are reliable and cost-effective ways to listen for that crystal clear note that resonates above the cacophony. I see three significant changes taking shape today that are heading us in the right direction:

1. The world’s not perfect — and robots have to be able to operate in spite of imperfection.

For the longest time, robots would only work if everything around them was fixed. You essentially designed the workspace around the robot — which works in some factories, as we have seen in the automotive industry. But it doesn’t work for the majority of tasks being performed in most factories. And it certainly doesn’t work in our homes. What we need are more general purpose robots that work in the environments we have.

2. Robots have to get smarter.

Robots over the years have not been known for being particularly smart. You program a robot to take a series of steps, and it performs those steps. You can build in if-then-else statements, but essentially, the robot is executing a program. Not a smart robot.

This is where we are seeing major breakthroughs and innovations. We now have better robots — robots that can work in environments that are imperfect. Automation of the physical task is innovating rapidly. But where we are also seeing rapid innovation is in the automation of the cognitive task, with advances in artificial intelligence — including machine learning and deep learning.

Where this gets really interesting is when you bring the two together — the new ways of automating the physical with the new ways of automating the cognitive.

3. Putting advanced analytics and big data to work for innovation in manufacturing requires that we replace “humans or robots” with “humans and robots.”

So, where do people come into the picture? In my mind, there are two major shifts taking place in the area of human-robot collaboration.

First, for the vast majority of robots traditionally, the way you got a robot to do something was to have an expert program it. As we think about democratizing robots, this isn’t going to work. There are not enough roboticists or computer scientists in the world to program all the robots we’ll need on all the tasks we want them to do. The robots coming on-line today are trained by someone showing them what to do. In the future, humans will tell them what to do, and eventually the robots will simply watch and learn — from humans and from one another.

Second, we need to embrace the value of agency — or free will — that only humans bring to the equation. The new frontier in manufacturing combines robots that can deliver real-time, sensor-driven telemetry data with software and data platforms that can aggregate structured and unstructured data. Organized, categorized, prioritized and presented, humans can then do what they do best: understand the information, interpret it and make smart decisions about how to improve processes and ways to drive continuous innovation.

When placed side-by-side in the work stream, robots and humans will finally be able to work together on problem-solving, process improvement and much more.

At the intersection of physical and cognitive automation — that’s where manufacturing’s age of innovation lives, and why there’s never been a more exciting time than now to be a part of it.

Originally published on GE Reports.