My response to automation and robot dystopian writers is that for the most part these technologies have removed humans from dangerous and monotonous manufacturing work. Humans are freed to do things using their heads as well as their hands. This report from A.T. Kearney and Drishti further contradicts hype about accelerating factory automation; demonstrates the need for greater investment in the human workforce.
According to new data released today by A.T. Kearney and Drishti, humans still perform 72 percent of manufacturing tasks. This data, from a survey of more than 100 manufacturing leaders, suggests that despite headlines about robots and AI replacing humans in factories, people remain central to manufacturing, creating significantly more value on the factory floor than machines.
Respondents also noted that there’s an almost universal lack of data into the activities that people perform in the factory. This analytical gap severely limits manufacturers’ ability to make informed decisions on capacity planning, workforce management, process engineering and many other strategic domains. And it suggests that manufacturers may overprioritize automation due to an inability to quantify investments in the human workforce that would result in greater efficiencies.
“Despite the prominence of people on the factory floor, digital transformation strategies for even the most well-known, progressive manufacturers in the world remain largely focused on machines,” said Michael Hu, partner at A.T. Kearney. “This massive imbalance in the analytics footprint leaves manufacturers around the globe with a human-shaped blind spot, which prevents them from realizing the full potential of Industry 4.0.”
While manufacturing technology has seen increasing innovation for decades, the standard practices for gathering and analyzing tasks done by humans – and the foundation of holistic manufacturing practices like lean and Six Sigma – are time-and-motion study methodologies, which can be directly traced back to the time of Henry Ford and have not been updated for the digital age.
“The principles underlying these 100-year-old measurement techniques are still valid, but they are too manual to scale, return incomplete datasets and are subject to observation biases,” said Prasad Akella, founder and CEO of Drishti. “In the age of Industry 4.0, manufacturers need larger and more complete datasets from human activities to help empower operators to contribute value to their fullest potential. This data will benefit everyone in the assembly ecosystem: plant managers, supervisors, engineers and, most importantly, the operators themselves.”
Additionally, the survey respondents noted the significant overhead needed for traditional data gathering methodologies: on average, 37 percent of skilled engineers’ time is spent gathering analytics data manually.
“Humans are the most valuable asset in the factory, and manufacturers should leverage new technology to extend the capabilities of both direct and indirect labor,” said Akella. “If you could give your senior engineers more than a third of their time back, you’d see immediate gains. Instead of spending so many hours collecting data, their attention and capabilities would remain focused on the most critical decisions and tasks.”
The survey also revealed the flip side of human contributions to manufacturing systems: Survey respondents noted that 73 percent of variability on the factory floor stems from humans, and 68 percent of defects are caused by human activities. Perhaps as a result, 39 percent of engineering time is spent on root cause investigations to trace defects – another manual expenditure of time that could be greatly reduced with better data.
“The bottom line is that better data can help both manufacturers and human operators across the board,” said Hu. “Data illuminates opportunities for productivity and quality improvements; simplifies traceability; mitigates variability; and creates new opportunities for operators to add even greater value. Humans are going to be the backbone of manufacturing for the foreseeable future, and the companies that improve their human factory analytics are the ones that will be best positioned to compete in Industry 4.0.”
To view the full report, click.
A.T. Kearney is a leading global management consulting firm with offices in more than 40 countries.
Honeywell released three announcements while I am still recapping the ARC Forum. There are one or two more to go. Thèse regarded maintenance management, simulation, and safety under the umbrella of Connected Plant.
The first is a new offering as part of Honeywell Connected Plant that allows customers to more effectively manage the maintenance and operations of their industrial equipment. The new Honeywell Connected Plant Asset Performance Insight connects the customers’ assets and equipment to the cloud, and applies analytical models from Honeywell and its partners, so that customers can avoid unplanned downtime and unnecessary maintenance.
“In today’s competitive business climate, in which asset capacity is often sold out, equipment performance is key to increased profitability,” said Richard Shaw, general manager, Honeywell Connected Plant. “With operational and maintenance-induced equipment failures accounting for most of the unplanned downtime, industrial companies are looking to digital transformation and IIoT to make sense out of huge amounts of data. Honeywell Connected Plant and our new Asset Performance Insight will help our customers operate more strategically and effectively.”
Honeywell designed the Asset Performance Insight solution to be rapidly deployed to customers through pre-configured templates. These templates are based on the company’s deep industry experience and real-world customer challenges enhanced with advanced analytics. The offering can also be configured and tailored to customers’ specific needs, making it extremely flexible.
The second is a cloud-based simulation tool that uses a combination of augmented reality (AR) and virtual reality (VR) to train plant personnel on critical industrial work activities. With as much as 50 percent of industrial plant personnel due to retire within the next five years, the Honeywell Connected Plant Skills Insight Immersive Competency is designed to bring new industrial workers up to speed quickly by enhancing training and delivering it in new and contemporary ways.
Honeywell’s advanced training solution combines mixed reality with data analytics and Honeywell’s 25 years of experience in worker competency management to create an interactive environment for on-the-job training. It uses Microsoft’s HoloLens, the world’s first and only self-contained holographic computer, and Windows Mixed Reality headsets to simulate various scenarios for Honeywell’s C300 controller – such as primary failure and switchovers, cable and power supply failure – that train and test personnel on their skills.
“Megatrends such as the aging workforce are putting increased pressure on industrial companies and their training programs,” said Youssef Mestari, program director, Honeywell Connected Plant. “There is a need for more creative and effective training delivered through contemporary methods such as Immersive Competency, ultimately empowering industrial workers to directly improve plant performance, uptime, reliability and safety.”
Simulating specific job activities through virtual environments, which are accessed through the cloud, Honeywell’s solution offers a natural way to interact and communicate with peers or a trainer. Similar to a flight simulator, trainees can safely experience the impacts of their decisions. This approach improves skill retention versus traditional training methods by up to 100 percent and reduces the length of technical training by up to 66 percent. Additionally, the employees’ training progress is tracked as part of a formal competency management system.
And wrapping up is a new solution for real-time safety monitoring of workers in plant and remote operations. Honeywell Connected Plant Skills Insight Personal Gas Safety helps to protect lives and enable faster response in case of hazardous leaks or worker injury.
The solution’s wearable gas detectors monitor gas, radiation and dust, and are tightly integrated with Honeywell’s distributed control system, Experion® Process Knowledge System (PKS). In case of harmful exposures, man-down or panic alarms of workers in the field, accurate, automated alarms now alert control room operators in real time. In addition, safety teams can take advantage of powerful tools embedded in Experion PKS to provide detailed trending, reporting and data analysis of the gas detectors to further ensure safe operations.
“Monitoring worker safety and ensuring proper response to emergencies are top priorities for industrial producers,” said Adrian Fielding, marketing director, Integrated Protective Solutions for Honeywell Process Solutions (HPS). “Personal Gas Safety gives plant operators eyes and ears in the field to improve their situational awareness, helping avoid potentially life-threatening conditions while also providing workers with the assurance that help will be on the way quickly if they need it.”
Looking for the source of innovation in manufacturing technology. Not only am I planning for direction in 2018, I’m in conversations about where lies the excitement.
OK, so it’s been two months I’ve been digesting some thoughts. In my meager defense, November and December were very busy and hectic months for me. Still lots going on in January as I gear up for the year.
Last November, I quoted Seth Godin:
Like Mary Shelley
When she wrote Frankenstein, it changed everything. A different style of writing. A different kind of writer. And the use of technology in ways that no one expected and that left a mark.
Henry Ford did that. One car and one process after another, for decades. Companies wanted to be the Ford of _____. Progress makes more progress easier. Momentum builds. But Ford couldn’t make the streak last. The momentum gets easier, but the risks feel bigger too.
Google was like that. Changing the way we used mail and documents and the internet itself. Companies wanted to be the Google of _____. And Apple was like that, twice with personal computers, then with the phone. And, as often happens with public companies, they both got greedy.
Tesla is still like that. They’re the new Ford. Using technology in a conceptual, relentless, and profound fashion to remake industries and expectations, again and again. Take a breakthrough, add a posture, apply it again and again. PS Audio is like that in stereos, and perhaps you could be like that… The Mary Shelley of ____.
So I asked on Twitter “Who will be the Mary Shelley of automation?
I’m sitting in a soccer referee certification clinic when I glance at the phone. Twitter notifications are piling up.
Andy Robinson (@Archestranaut) got fired up and started this tweet storm:
Gary… why do you have to get me fired up on a chilly November morning! I’m not sure we have any.. at least at any scale. And the more I’ve pondered this more the more I consider the role or culpability of the customer. Buyers of automation at any scale tend to be 1/
incredibly conservative. If they are ok with technology that isn’t much more than a minor evolution of the existing then we aren’t going to get anywhere. Recently I devoured Clayton Christensen’s The Innovator’s Dilemma. I keep trying to figure out how a small player 2/
with disruptive tech can move our industry. There are pockets and potential but ultimately if there isn’t enough uptake by customers willing to take a risk then we don’t move forward. Considering all this I “think” I have figured out one potential causal factor. 3/
If you look at where the fastest innovation is happening it’s in software. Is the majority of the innovation coming from vendors or asset owners. it’s asset owners. Amazon, Netflix, AirBnB, etc. are all doing amazing things and taking risks writing new code for their systems4/
Having been an asset owner and vendor I can tell you for a fact I was way more willing to take risks when I was the owner. As a vendor I want to deliver a solution to spec with minimal risk. Fundamentally product companies are doing the same thing. Just good enough with 5/
minimum risk to supply chain, warranty repairs, reliable field operations etc. Even platforms like Kubernetes that appear unaffiliated were developed by asset owners like Google, taking risks and pushing the boundaries. The Exxon work with open automation “has” this 6/
potential but I don’t know if the willpower up and down the chain and left and right with partners is going to be there. It takes incredible willpower to take risks and accept that there will be blow back and consequences in the form of loss of political capital and failure. 7/
So maybe it all boils down to the fact that until we as an industry find a place where failure is acceptable and even celebrated on a small scale we will continue to innovate at a speed somewhere between typewriters and vacuum cleaners. 8/
is it any wonder we have such a hard time attracting young talent? Pay is good and challenges to solve real problems are there. But looking 20 years out we are still doing same things, just a new operating system, faster Ethernet, and new style of button bar on the HMI /endrant
He asks some good questions and provides some interesting insights.
I’ve had positions with companies at different points of the supply chain. He makes sense with the observation that the asset owners may be the most innovative. My time in product development with consumer goods manufacturers taught me such lessons as:
- Fear of keeping ahead of the competition
- Relentless concentration on the customer
- Not just cost, but best value of components going into the product
- Explaining what we were doing in simple, yet provocative terms
Today? I’m seeing some product companies acquiring talent with new ideas. Some are bringing innovative outlooks to companies who find it very hard to take a risk for all the reasons Andy brings up. The gamble is whether the big company can actually bring out the product—and then integrate it with existing products to bring something really innovative to market. They of course have the funds to market the ideas from the small groups.
Next step, do the innovative people from the small company just get integrated into the bureaucracy? Often there is the one great idea. It gets integrated and then that’s the end. The innovators wait out their contract and then go out and innovate again. I’ve seen it play out many times in my career as observer.
Often the other source of big company innovation bubbles up from customers. An engineer is trying to solve a problem. Needs something new from a supplier. Goes to the supplier and asks for an innovation.
I’d look for innovation from asset owners, universities, small groups of innovative engineers and business thinkers. They live in the world of innovating to stay ahead of the competition or just the world of ideas.
I’m reading Walter Isaacson’s biography “Leonardo” right after his one on Einstein. He offers insights on what to personality to look for if you want to develop an innovative culture in your workforce. Wrote about that recently here.
Walter Issacson has done deep research and written biographies of several men you could call geniuses. Benjamin Franklin, Leonardo Da Vinci (next on my reading list), Steve Jobs, Albert Einstein. I just finished the Einstein book.
Reflecting on his career while speaking at a conference I attended, Issacson said that they all shared certain characteristics–they were rebellious, they didn’t quite fit in with their contemporaries, and they could bring in ideas from numerous sources. Think of this in terms of building a great workforce.
I was probably 10 or 11 when I first read a biography of Franklin. Even then I was impressed by his wide-ranging curiosity. He seemed to learn something about everything. Yet, he grew up poor and didn’t have the perks of wealth.
The Einstein book was enjoyable, if long. My wife said she had some trouble getting through it. I can believe it. All the stories about his wives and family troubles were hard to get through. But the detailed discussion about the developments in physics–ah, suburb. OK, so maybe she liked the family stuff and I preferred the physics.
By the way, it’s not true that he failed arithmetic as a boy. But his genius was not in math. He had friends who helped out on the math side of the theories.
Einstein didn’t accept all the common knowledge about physics of the day. As he pondered the influential experiments and thoughts of the late 19th century, he performed thought experiments. That is, he used his imagination.
In fact, one saying attributed to him concerns the importance of imagination over rote learning.
He said later in life that one doesn’t attend college to learn facts. You go to college to learn to think.
I was no doubt influenced by that statement many years ago when I formulated my description of an educated person (note that it says nothing about degrees)–you learn how to learn, you learn how to think clearly, you learn how to express yourself.
In fact, while I respect the tenacity of those who have advanced degrees, I got that out of my system early. The university shut down the program I was in. After getting accepted at a couple of other universities, I looked at the curriculum and decided to study what I wanted. I’ve always viewed a degree as a certificate that entitles the bearer entry into a club.
In that respect, I’ve always sided with the greater Marx philosopher–Groucho. “I don’t want to join any club that would want people like me as a member.”
Workforce tip: You’re going to look for minimum capability, of course. Don’t hire a programmer who thinks Java is something you drink. However, look for people who are curious, who challenge things as they are, who can balance individual work with team work. Cultivate a workplace where ideas (not personalities) form the foundation of lively and challenging discussions.
Digital transformation professional services companies provide value to owner/operators and manufacturing companies. But their services are often expensive. I have done some work on platforms such as MIMOSA’s OIIE (which is still in development) that are designed to use standards and interoperability to help these customers reduce their expense and dependence on these firms.
It’s sort of a “good news, bad news” thing.
At any rate, the PR firm representing Cognizant contacted me toward the end of December with an opportunity to interview an executive. The purpose of this interview would be to update me on the company and talk a little about digital supply chain, workforce, and other manufacturing innovation topics.
Anxious to get something done before the end of the year (billable hours?), they even offered times between Christmas and New Years. Prasad Satyavolu, global head of innovation, manufacturing, and logistics practice, talked with me shortly before Christmas.
When I laid out the conversation on a mind map, the map was huge. So I thought about it off and on for the past couple of weeks. These thoughts reflect about half of the conversation. There is a lot to think about.
Cognizant was a very familiar name, but I couldn’t place it. “We are familiar with SCADA and plant floor,” Satyavolu told me. “We acquired Wonderware’s R&D operations. In fact, we still work with Schneider Electric. We also work with Rockwell Automation.”
Core Manufacturing services include:
• Transportation/Material Handling
• Process industry
• Energy/Oil & Gas
• Aerospace (some)
• Utilities/Smart Grid/Smart Meters
When Cognizant evaluates a customer’s processes and lays out a plan, it includes everything from incoming supply to manufacturing to shipping to customer. The demand and supply chain.
One opportunity Satyavolu sees considers more instrumentation leading to additional sensing of movement of materials and workers in order to capture better decisions and enable efficiencies.
Then consider the confluence of changing workforce and technology. “Consider reality on shop floor. 5-10 years ago a maintenance engineer listened to a machine, diagnosed the problem, and fixed the machine.
The next generation doesn’t have that knowledge. Today the time to fix has gone from 15 minutes to 4 hours. How can we tackle knowledge gap? Further, is the next generation even interested in this sort of work?
Looking ahead, by 2025 we will be short 8 million people with manufacturing skills. How does this impact global mid-sized companies? How can we further leverage robotics to help solve this problem? Would robotics technology even make the work more attractive to a new generation of workers from the world of gaming and drones?
Huge opportunities exist with visibility outside the plant to planning and execution. It’s the Amazon effect—velocity so high that you almost have to produce on demand. Predictive maintenance systems enable managers to manage schedules and demands. This leverages infastructure such as cloud, digital technologies. These improve scheduling, reschedules lowering carrying costs; aids risk management / mitigation; global organizations bringing parts from around the world, global demand/supply increases uncertainty.
On shop floor, plant has fixed schedules / horizons. Scheduling systems and a lot of modeling bring stability and improve effectiveness. You can simulate production quickly, get status of inbound parts, changes in demand side, sync with labor requirements. With better scheduling, you get better visibility—you can save 12-13% of costs with sync. You can track supply chain, transportation, and change schedules in advance improving risk management.