Lean Manufacturing in a Digital World
Mar 12, 2020
Operational excellence never goes out of style, and done right, smart technologies enable better decisions, faster.
It’s a question that crops up with amazing regularity: What’s next after lean manufacturing? It’s an odd inquiry, really, because it implies that you “finish” lean or toss it aside in favor of the next big thing. It suggests that the idea of removing waste, improving flow and maximizing customer value is out of vogue. It nearly proposes that lean—a term coined in the ancient past, meaning more than 30 years ago—is an old-fashioned notion with no current relevance.
And now it’s 2020. Smart technologies are sweeping across the factory floor, promising to provide manufacturers with more and better data for smarter decision-making, as well as faster responses to potential downtime events. They are descriptive, predictive and prescriptive. They can do it all.
Are smart technologies “what’s next” after lean manufacturing? Is now perhaps the time to give lean the boot? Move aside, lean manufacturing? Step away, one-piece flow? Exit stage right, value-stream mapping? Alternatively, how does lean fit into this increasingly digital manufacturing landscape?
All good questions. And for some manufacturers, the answer is obvious.
“I think if you look at lean, a lot of the fundamentals of it are timeless,” says Zohair Mehkri, XR and simulation engineering manager at Flex, a global electronics manufacturing services provider. “They really don’t ever expire. They never really become obsolete. From a technology perspective, it is very important for Flex or any company really to have a lean foundation.”
Hence, lean doesn’t go away. In fact, just the opposite becomes true.
“Lean manufacturing really is about making problems visible, addressing problems and solving problems. Anything that can help you do that more efficiently is good,” says Bob Argyle, chief customer officer at Leading2Lean, a technology solutions provider that supports lean implementations. “Smart technologies, used correctly, have really enhanced or accelerated companies’ ability to implement lean manufacturing and drive improvement in a big way.”
Argyle is in somewhat of a unique position to consider both sides of the lean/smart technologies equation. He’s a 30-year veteran of manufacturing. He’s worked at auto supplier Autoliv, a manufacturer with strong ties to lean manufacturing, and been mentored by Toyota, the epitome of a lean operator as well as a company that embraces technology where it makes sense.
Then there’s Samuel Bouchard, CEO and co-founder of robotics manufacturer Robotiq. Bouchard has gone well beyond suggesting lean and technology work in concert. He wrote an entire book – Lean Robotics – that spells out a methodology for simplifying robotic cell deployments via lean principles. How much more tightly can lean and technology intertwine? As Bouchard notes early on, lean robotics isn’t about the technology, per se. “The end goal – as with everything you do in your company – is to create value for your customers and drive business results,” he writes. Sound familiar?
Equally interesting is the reason Bouchard wrote Lean Robotics. As he explains it, a little root cause analysis into why he was having difficulty making sales pointed to a problem with which potential customers struggled: Integrating robotic systems was simply too complicated. The methodology Bouchard’s team developed set out to reduce that complexity.
Here’s the Rub
There’s a saying that boils down to this: Technology won’t fix a bad process, it will only speed up a bad process. Similarly, smart technology’s ability to enhance a lean implementation depends a lot on the proficiency of the lean team. For example, MIT Sloan senior lecturer John Carrier notes that the first major impact of the digital transformation “is providing real time visibility into parts of the system that were previously invisible.” The new visibility, he says, “provides clarity into which problems should be solved next, and the value they will produce.”
In theory, those words are terrific news for a lean organization whose aim is to create an organization populated by problem solvers. In practice, few organizations are at that level of lean. So, while smart technologies may ultimately enhance the pursuit of continuous improvement, initially they could add a layer of complexity that a lean implementation may not be mature enough to handle.
Indeed, “I see that many companies have not made the connection between the first phase of the digital transformation (it uncovers problems rather than solves them) and the lean/six sigma functions, which often are training organizations rather than problem solvers,” Carrier notes.
Similarly, the introduction of smart technologies can’t substitute for the challenges lean manufacturing has always faced on the leadership front. Namely, without commitment by leadership to lean—or really, any other continuous improvement initiative–it withers on the vine at worst and delivers only pockets of excellence at best. Smart technologies cannot substitute for committed leadership.
“Implementing all of the latest trends in manufacturing isn’t going to provide the expected results if the company executives are not creating a collaborative, supportive environment for the workers,” notes John Dyer, IndustryWeek contributor and author of the recently released The Façade of Excellence: Defining a New Normal of Leadership.
While he notes that real-time displays of data, for example, are a major step toward making improvement happen, they are almost worthless “if teams of employees are not empowered to make quick, decisive decisions on how to respond to out-of-control signals.”
Moreover, empowerment without proper training is a failure as well—and that’s on the leadership. “If the workers do not have the tools, knowledge, or experience of continuous improvement to do things like get to the root cause of problems or identify and break bottlenecks, even the most modern manufacturing systems will slowly deteriorate and eventually fail.”
What can leaders do? Create a collaborative culture, says Dyer, “by coaching, educating, and mentoring their teams in order to support a drive for excellence.”
Lean and Smart: A Collaborative Approach That Works
Flex is a manufacturer that favors a collaborative approach to operational excellence. It has created a structured process to problem-solving and leverages smart technologies, as well as other resources as they are needed to reach desired outcomes.
“Lean is more the methodology of problem-solving, and I see these smart technologies as being … an enabler because it makes a lot of information readily available,” explains Flex’s Prakash Subramaniam, vice president, global business excellence and corporate quality. “Lean removes waste. Smart ensures speed on the removal of the waste … enabling us to get to an optimal solution faster.”
Subramaniam and Mehkri shared an example of how lean and smart technologies work hand in hand in their organization. In this example, Flex is setting up a new manufacturing line within one of its facilities to support a new customer. The lean team engages in discussion about how to set up the manufacturing line or lines, addressing such items as the number of stations and people required, the takt time needed to meet demand, the speed at which material needs to be supplied to the lines, et cetera. As these basics are established, Mehkri’s group actively engages to provide a simulation of the proposed layout by way of discrete event simulation (DES) technology.
The ability to visually display and simulate the manufacturing concept under consideration gives the Flex team the opportunity to, well, work out the bugs before the physical line is built. Team members can test “what if” scenarios, discover potential bottlenecks and optimize production plans in a virtual environment. The ability to rapidly iterate potential solutions is one example of how lean and smart technologies complement each other, both men say.
An Education in Data at Jabil
Absent training, the potential for lean to impact an organization is limited. It’s that simple, and it explains why companies that are committed to lean train their employees on what lean is, how it works, as well as provide some explanation of various lean tools. The same thinking holds true for Six Sigma, lean Six Sigma and other continuous improvement methodologies.
Given the influx of more and more rapidly acquired data in the wake of smarter technologies, manufacturing solutions provider Jabil Inc. is taking a somewhat similar training approach to data science. The company has implemented both an executive and citizen data science program, two efforts designed to teach Jabil leaders and employees the tools and methodologies of data science, as well as how to apply that knowledge to solving problems.
The programs are open to anyone who has an interest in learning data science skills, explains Candy Mitchell, director, data science and artificial intelligence at Jabil. The leadership track is a day-long event, typically with a workshop attached. The citizen data science program, on the other hand, is three weeks of what Jabil calls “boot camp” completed over a three-month period. Students conclude the course by providing a data science solution to a problem they want to solve.
Jabil is also considering another training option, this one simply around awareness. “This would be more of a one-day type of training just to understand the language. Just like the language of Lean Six Sigma, smart technologies have their own language: machine learning, computer vision, data science,” says Mitchell. “And then people who have more interest can take more training,” she explains.
In her role, Mitchell oversees the company’s data science programs and consults on use cases across the organization. A lean Six Sigma master black belt, she also supports the adoption and use of Lean Six Sigma at Jabil.
The data science training, Mitchell emphasizes, is not just for IT personnel. In fact, the focus is on business-side personnel, with the goal, ultimately, to grow the skill set of any person who has an interest in learning.
“We want to be inclusive,” she says, because data touches people across all functions and titles. Moreover, it helps solve problems across the organization, from the back office to the manufacturing floor.
Which brings us back around to lean. Lean principles and smart technologies accelerate continuous improvement if done right, Mitchell says.
“We get the data faster. We can do analytics faster. We can do ’what-if’ analyses. It empowers people within the business to use new tools and platforms to do these things,” Mitchell says. “It’s really about the smart technology and lean working together.”
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