Mind + Machine: Changing the Business of Manufacturing

shake 2This 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.

“New” is Here to Stay: Make it Work for You

Night blooming cactus

I was glad to be a part of Supply Chain Insights Global Summit last month as it gave me a good chance to connect and reconnect with the people who share my passion for manufacturing and the supply chain. The conversations I had and the presentations I sat in on reminded me, once again, that “right” in manufacturing and supply chain is an always-evolving target. And if through hard work, smarts and some providence, you do get it right, it won’t be long before you need to recalibrate.

One of the things I find fascinating about this space is our never-ending pursuit of ways to make it better. The attendees I talked to are ready to wrangle, wrestle and wrap their hands around a lot of possible ways to make it happen. Artificial Intelligence, the Industrial Internet of Things, Cloud Robotics were just some of the topics and trends that these leaders are looking at to transform their businesses.

Another thing I admire: the pragmatism that imbues our thinking. It’s not that leaders in the supply chain are conservative or hardened skeptics. It’s just that they know just how hard transformation is to achieve. They’ve seen enough and learned enough to know that whatever’s making the headlines is worth exploring but won’t be the silver bullet to their challenges. In its own way, that takes courage.

So, there in the high mountain desert, I was reminded that there are tried, true and “old” ways to bring “new” change to fruition and they are worth repeating. When it comes to “game-changing innovation”

  • Start small. Find a place in your operation to test the way it works, what you have to change about your process, and what you’ll measure.
  • Recognize that with anything “new”, there will be glitches and gotchas. Engage with your partners and revise, repeat, and measure as often as needed.
  • Expand only when you have the results YOU want. Incremental change is more likely to stick and deliver the transformation you desire.

With all the energy and excitement around the space, it can be easy to get swept up in the hype.

But we’ve been here before, so I don’t have any doubt that we will tame this latest iteration – applying what we learn along the way.

Originally published on Beet Fusion.

Robots with Grit: Redefining Manufacturing

Aerial view of hedge mazeIn 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 JabilGE 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.

Supply Chain 2030: Closer than You Think

Supply Chain 2030

2030. That is only 13 years, 4 months away. For manufacturers – and their supply chains – that time horizon is barely a blink of an eye when you think about the pace of innovation today.

We all know that manufacturing is on the brink a significant transformation as information becomes as critical to production as man and machine are today. And so, too, will we see significant changes in the way supply chains are built and run. And it will happen much sooner than most of us think.

In fact, I believe we’re seeing the signs of meaningful change now. Manufacturers in all segments see consumer behavior changing and the need for shorter, more flexible supply chains and more frequent innovation cycles. One of my customers, Jabil Electronics, is on the forefront of building supply chains that can support the new model for manufacturing. The company is focusing on smaller operations, that can ramp up and scale back in much shorter timeframes and operations that are closer to the end market.

What’s happening technology-wise that makes this possible? Today, we’re in the heart of the perfect storm of low-cost sensors, devices, processing power, data storage, connectivity and ways to handle big data that will allow manufacturers to sense and respond in real-time to shifts in demand, market conditions, and risk.

When information on everything from quality metrics and marketing feedback to demand updates is available to inform decision-making on everything from design changes to sourcing to marketing strategies, supply chains will not only be flexible, they will be nimble. Supply chains will be designed to support local customer needs and expectations. They will be able to optimize innovation and value. In other words, supply chains will finally become the engine for success in manufacturing that we have all been working for them to become.

Originally published on Beet Fusion.

It’s a Jungle Out There…The Best Advice I Ever Got

11143769 - amazonian rainforest in ecuador with many bromeliads in foreground

Remember Tarzan? Whether you know the Disney version or the old black and whites with Johnny Weissmuller, the iconic image of Tarzan swinging through the jungle is something most of us know. How was it that a vine was always right where he needed one? That those vines would create a perfect pathway to take him where he wanted to go?

Although a fictional character, it’s a great metaphor for trusting our gut instinct. That’s what allowed Tarzan to trust his choices, accept the risk that it might not all go as hoped and to trade the safety of what he knew and go for it anyway. I like to believe, too, that if he lost his grip on the vine and fell, he’d get up and go on. It’s that advice that has influenced many of the choices I’ve made, and I’m grateful for it.

Because of this advice, my career has turned out to be a series of exciting, challenging and rewarding opportunities because, like Tarzan, I reached out for a vine and it was one that led me into new and uncharted markets. I could not possibly have known when I left Hewlett Packard that I’d be part of teams that blazed trails in e-commerce, supply chain management, data and analytics, and now, robotics. These start-up environments have been fertile ground for learning – much more so, I think, than had I stayed with the safe-bet of HP. Some of the best lessons will always be with me:

  • In emerging technology markets, you can’t fake it. You’ve got to believe in what you’re doing and bring that commitment and passion to work every day.
  • You have to surround yourself with bright, talented people; you have to treat them with respect and you have trust that they will do their best.
  • You have to move quickly and again, like Tarzan, trust your gut that the choices you make will get you where you want to go.

When I look back at where I’ve been, and how each stop along the way turned out to be the right one for that time, I’m amazed. No doubt, they’ve all had their unique twists and turns. Some days it was exhilarating – like a roller coaster ride. Some days I wondered if it really was all worth it. But in the end, every vine I grabbed took me somewhere I could learn new skills and become a better leader, cultivate new ways of thinking, and adapt to the constant evolution of business and technology. I just had to trust that when I was ready, the vine would be there for me to take that next step.

Originally published on Beet Fusion.

Robots on a Mission: Agents of Change in Manufacturing

Robot, illustration

When Henry Ford introduced the assembly line, manufacturing took a major leap forward. Productivity advanced in ways never before possible. It took 50 years for the next breakthrough to hit the factory floor when Unimate came online at GM. We’re seeing another breakthrough now as robots evolve to be more than simply machines that can lift heavy objects and perform repetitive tasks over and over and over again. The convergence of muscle and “mind” – in the form of information technology – makes automation more than a productivity enhancer and that changes everything. These robots will act as agents of change – for the better – better products, margins, and working environments.

The evolutionary path for robots is underway. The innovations on the horizon will change forever how robots perform and what they are able to do.

Robots as More than Machines

Robots have come a very long way already. Smart, collaborative robots are safecan work in imperfect environments and are able to perform more than a single task. These advances in robotics technology are making it possible to chip away at the nearly 90 percent of tasks that until have been beyond the reach of automation in manufacturing.

These robots are driven by software, which makes it significantly easier and much more cost-effective to deliver new innovation, and expands the universe of opportunities for work to be done by robots. Right now, these robots work on specific tasks, in work cells, alongside humans, increasing productivity and enabling greater flexibility.

Soon, robots will do more. The integration of hardware and software will raise the robots’ ability to understand what needs to be done and execute the physical steps required to make it happen. They will direct activities and equipment in the workcell. They will learn from their work – and the work of robots globally, collect information on their performance and provide data analysis that can inform continuous process improvement.

The advances we’ll see that make this possible in robotics technology include:

  • Sensors that collect data in ways similar to humans – seeing, touching, engaging
  • Behavior-based artificial intelligence – innovation in intelligence will make it possible for robots to integrate and interpret the information gathered by the sensors and then formulate and direct the appropriate action, overcoming the limitations set by “programmed-only” responses
  • Actuators that can execute the required action – advances in the hardware take shape as robot hands and arms that work much more like human appendages – more flexible, dexterous and sensitive to the environment and the situation

More than 100 years after the automated assembly line, it’s time for the kind of change that robots can bring. In future posts, I’ll look more closely at how these operations will be organized and what it will take to realize the potential. I welcome your thoughts on where you see robots evolving and how that evolution will drive change – tweet me @jim_lawton.

Originally published on Forbes.

The Future of Work: At Last, the Right Resource for the Right Job

Telephone operators

It’s hard these days to not hear about the impact that robots, artificial intelligence, and other technological innovations are going to have on “work”. Self-driving cars, robots that cook and serve meals in the home and devices that can anticipate what we want to do almost even before we do are going to make us – some doomsday pundits predict – obsolete. But let’s be realistic. Right now, we have only the smallest window into understanding all it takes for any task to be done, and figuring out how we can apply technology to do the kind of work that humans do almost instinctually will take time.

That said, I have no doubt that these advances will change what it means to work and how work gets done. Almost every day, I talk with manufacturers about the ways in which they expect today’s smart, collaborative robots to help them meet the challenges they face – and it’s not about replacing their human labor force. In fact, across our customer base, the loss of jobs when a robot is introduced to the production floor is negligible. How is that possible, you ask? Simply put – our customers are finally able to match the right resource to the right job. Robots do the repetitive work best suited for automation that, until now, had been out of reach for heavy, industrial robots. The people train the robots, monitor the work, and are free to focus on ways to improve processes, products and solve problems. It’s a model that allows people to do what they do best even better. In the long-term, it repositions manufacturing as a field where the jobs truly are good ones for people, where wages are aligned to support a strong middle-class again and where innovation and creativity become the true drivers of sustainable value and competitive advantage.

It won’t happen overnight. As I said at the start, there’s a lot of learning and experimenting that has to happen. It will happen in waves. We’ve seen the first wave with the innovation in robotics that allows robots to perform more sophisticated tasks, change tasks frequently and to be deployed without significant reconfiguration of the production floor or flow.

Manufacturers like Jabil are already on leading edge of the next wave, recognizing that manufacturing needs to be closer to the centers of design and innovation and closer to end markets. The factories of the future will be smaller, nearer to customers and operated by local talent. These operations will rely more heavily on technology and will need skilled workers, with certifications and a very different kind of education than what’s currently available in most high schools in the country.

Beyond that, we’ll see changes in the ways products are designed, marketed and delivered. Increased innovation cycles, more refined customization and supply chains that are able to respond immediately to fluctuations in demand as well as economic variability will become the characteristics of market leaders.

Before all that happens though, there’s a lot of work to be done. We’ve got to figure out the mechanics of tasks, how to apply automation to those tasks, what’s missing and how to create innovation to overcome the gaps – the list is long and so then, are the opportunities. It will require cognitive skills and creativity; it will create jobs that contribute to product innovation and competitive value.

For me – a firm believer in the true and lasting value that manufacturing offers the economy and maybe even society as a whole – the most exciting part is this: other industries are depending on manufacturing to show the way. The lessons learned in manufacturing will lay the groundwork for other fields to adopt these innovations for making work better as well.

Now all that’s left is to roll up our sleeves and get to it.

Originally published on Beet Fusion.

3 Challenges for Manufacturing’s Innovation Age

Sawyer and JimThere 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.

Mistakes I’ve Made: What My Son Taught Me

Mistakes Image Jim Lawton_0“Father knows best” goes the old saying. After all, fathers – and mothers – are older, and the corollary then is also wiser. We’ve seen more, done more, and know more. We have our children’s best interests at heart, and the decisions we make for them are designed to help them achieve all that is possible.

But sometimes we make mistakes. Big ones. And the lessons we learn have relevance in nearly every aspect of our lives. That’s what happened to me when my son entered 7th grade and his experience was not what my wife and I had envisioned. Our son is smart, hardworking, and has that native curiosity that shapes a life-long thirst for learning, all the while thinking about the world in different and profound ways. But something wasn’t working. There were a lot of little things that ultimately added up – at least in our minds – to warning signs that the school he attended wasn’t the right one for him. So, my wife and I set out to find something different. We talked to other parents, did our homework on all the options, made a short list of those we felt would be the “right” fit, and set out on the interview circuit. It wasn’t until one interview, when asked why he wanted to attend this particular school and our son honestly replied that he wasn’t sure he did, that we realized we’d left out the most important part of the process: engaging the one person most affected by the change and getting his input on what was really going on and what would be the best solution. So we went back to the drawing board – this time with our son at every step. Regardless of the outcome, the result will be exactly what it should be – best for him.

I see this same mistake all the time in business. As leaders, we’ve seen more, done more, and know more. When we identify a new initiative or strategy to help our organization be the best it can be we, too often, lose sight of those who are in the best position to help us get there. Excluding those who understand and know the process, product, and environment where we are trying to make the change only results in delays, missteps and sometimes flat-out failure.

The mistake I made with my son’s education reinforced for me in a very clear and loud way the principles I believe are essential for successfully driving changes –large and small:

  • Understand who will be affected by the change and how it will affect them
  • Engage them at the earliest possible moment
  • Solicit their input not only on the piece of the process that they own, but on the whole effort
  • Use their experience to set goals, milestones, and measures of success
  • Empower them as champions of the effort to their peer groups
  • Provide continuous feedback on where and how their input is being applied – and if not, why not

We’re smart. What we have to remember is that by our own design, the people we work with are smart, too. Engaging them in our vision, and harnessing their knowledge to make it succeed only gets us where we all are headed – to being the very best we can be – that much faster.

Originally published on Beet Fusion.

Moving the Needle on Supply Chain Excellence: From Incremental Improvement to Exponential Value

Supply Chain Excellence - cropped

Before supply chains were called supply chains, the motto of any good supply chain leader was simple: “Don’t f*%! it up.” If you took cost out of the supply chain, you got a bonus; if you shut the line down, you got fired.

Not to say that supply chain excellence has been as simple as that. In the 20 years I’ve been part of the growth in supply chain and its role in the business of manufacturing, the definition has evolved.

Fresh from MIT’s Leaders for Manufacturing program, I worked at HP, a company known at the time for leadership in supply chain innovation. Many of our core strategies were built around the concept of design-for-manufacturing (DFM). That meant that the best place (and the biggest lever) to impact the cost, assembly, testing and source-ability for a set of products was during the design phase. Once a product had been introduced, one’s ability to impact the architecture of the product and process, the selection of suppliers and the matching of design specs to the process capabilities of suppliers was more limited. So when it came to supply chain strategy, design was where it was at. It was good.

When I begin working with innovative software solutions for improving supply chain performance, reducing cost and DFX remained a priority. The strategies changed, however: there was lean supply chain, focused on eliminating waste; supply chain design and optimization where technology enabled better service AND lower inventories through better placement and sizing of safety stocks in multi-echelon supply chains. Then, the focus shifted to mitigating the risk that had become inherent in the design of the modern supply chain – not just supplier risk, but also geopolitical risk, brand risk, the risk caused by Mother Nature and more. Also good.

Today, though, manufacturing is undergoing a transformation and as manufacturing strategies change, so then must the definition of supply chain excellence. The improvements in supply chain strategy have been good, but if I’m honest, I’d say they’ve been incremental at best. What manufacturing needs today are supply chains that deliver breakthrough change.

When I started at HP, many industries could get away with building a single SKU, millions of times over and consumers would buy. That’s not true now. Whether customers are buying a tablet or a BMW, they’re looking for a customized solution. At the same, innovation is measured not in years, but in months. That means that the rigid, one-size-fits-all supply chains of today have to evolve.

Manufacturers, like my customer John Dulchinos at Jabil, are looking to shorten the distance between innovation and production so that new products can get to market more quickly. They’re looking to establish production facilities closer to end markets so that products better reflect customer needs and reach customers quickly, reliably and cost-effectively. Mercedes-Benz recently announced that they’re deploying a new breed of robots specifically to help the blue-chip brand accelerate product innovation.

The visions articulated by Jabil, Mercedes and others make me think that we’ve reached a point when the definition of supply chain excellence will evolve again. Most certainly, the Industrial Internet of Things (IIoT) is going to play a big role in what that looks like. The supply chains that support the models and strategies of the world-class leaders in manufacturing, retail and distribution will rely much more heavily on real-time data – about supply, demand and product performance in the field. Fed by advanced analytics and artificial intelligence, those supply chains will be flexible, resilient and cost-effective, and will learn over time – in other words, more than good – they will be excellent.

Originally published on Beet Fusion.