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Leveraging a Digital Lean Approach

Digital transformation is top of mind for many manufacturing companies, but to achieve results manufacturers should begin their transformation with a digital lean approach. In the classic sense, a LEAN approach means using the absolute minimum number of resources to convert raw materials into finished goods. 

When it comes to digital lean, that approach is expanded to include data and the tasks of capturing, storing, and contextualizing this data. However, capturing data for data’s sake is not exactly LEAN, as LEAN requires a focus on value creation. Manufacturers who leverage a digital lean approach focus on how they can use advanced technologies and data to minimize waste most efficiently in their operations. 

Anything beyond the necessary amount required is considered waste. The forms of waste in manufacturing processes and facilities include complexity, labor, overproduction, space, energy, defects, materials, idle machines, transportation, and time. 

“In LEAN methodology all these forms of waste are removed from the process. Whereas digital lean is the ability to actually see the real-time data that characterizes all of those forms of waste in their duration and their respective occurrence rates, where they happen. Beyond that, we must be able to put contextualization around that data,” explains Patrick Gaughan, a managing partner at Axiom Manufacturing Systems, a digital manufacturing consultant agency and solutions provider. “Utilizing digital lean methodology enables manufacturers to use a digital replication of their processes and operations to identify all the forms of waste.”

Manufacturers often don’t focus enough on how data will provide value to their organization. The highest value data oftentimes comes from aggregating or associating data from disparate data sources. An example of this is the ability to see all the WIP on the shop floor, which tells manufacturers how much working capital they have tied up in non-value-added material, as it’s not a sellable product, and represents a liability. 

A better approach is to tie WIP to marketing, procurement, and supply chain data and use it to calculate service levels, safety stocks, and reorder points, thus using that data to automate replenishment. When combined with artificial intelligence (AI), data enables manufacturers to look at trends and start to augment those critical calculations and anticipate how those values will change at different times of the year, or trends year-over-year. Manufacturers need to focus less on data and focus on solving actual business problems from the very start of the process, as that is what today’s manufacturers need most.   

Consider this stark reality: of all the Fortune 500 companies from the year 2000, only 48% of them are viable businesses today. If that doesn’t incentivize manufacturing businesses to be mindful of technology and markets, nothing will. History repeats itself, over and over. It’s clear that manufacturers who want to stay relevant and competitive in the future of industry must learn how to leverage digital lean methodology in their operations. 

The very things that made a company successful in the past can be the cause of failure in the future. For well-run organizations, the one that builds last, builds best. A strong spirit of continuous improvement and a focus on LEAN digital design will enable anyone to remain competitive.

The Advanced Technologies of a Digital Lean Approach

Digital lean is a methodology manufacturers must carry with them while working to advance their operations. But this approach is more than just a mindset—it should be at the forefront of technology implementations within manufacturing facilities.  

Given that digital lean is centered around data, it incorporates a lot of these advanced technologies that make it easier to collect, analyze, and act on this data. This includes a technology that is heavily involved in data collection at manufacturing facilities – sensors. 

“Sensors have evolved significantly over the past few years,” says Gaughan, “now they have edge computing capabilities. Modern-day sensors can take machine data, conduct a high-level analysis, and alert operators when something needs to be acted on based on this information. Edge computing is a really exciting capability in sensor technology.”

Sensors can quickly collect and analyze data while utilizing minimal energy, helping to eliminate both time and energy waste in a facility. Other technologies that rely on sensors, such as vision systems and cobots, expand on these capabilities to improve efficiency in manufacturing operations. 

This data analysis component has not only been added to sensor technology, but also to programmable logic controllers (PLCs). Today there are PLCs with manufacturing execution system software built-in, which adds the data analytics component. This enables easy extraction of Internet of Things (IoT) data in the manufacturing sector. 

With these advancements, technology in the manufacturing industry is now designed with improved functionality and usability. Gaughan elaborates: “Modern day systems must work well for the casual person that steps into a role in manufacturing. So, you’ll see that there's a lot of IoT systems out there now with contemporary designs that are fully scalable all the way from your cell phone, through tablets, and human machine interfaces (HMIs). So, if you're going to be in business, you must be able to run it from a phone, even in a manufacturing environment.” 

As facilities move to wireless networks completely, it’s much faster to adjust processes and operations to minimize waste than it was in the past. This wireless connectivity is also driving the adoption of even more digital technologies, including virtual and augmented reality (AR) and AI, all of which enable more responsive behavior and optimized usage of labor. 

Manufacturers may not be ready for AR across the board, but some industries have leaned into it because it helps minimize time and labor waste. For example, employees often have to leave their work and walk around a facility to find experts to help solve their immediate problem, so they can continue working, be that operations or maintenance. Businesses must recognize, however, that these employees are using valuable company resources (people’s time) to perform the “task” of walking, and that can result in an incredible amount of waste. 

Unfortunately for some businesses, it’s the most common form of labor use, because of poorly designed processes. However, once distance is dead due to AR, this waste can be readily overcome. The best process designs are the ones that keep people’s feet planted in one place, and everything needed within arm’s reach, unless a single person is operating multiple devices within a single cell structure.

Embracing technologies like AR and AI will lead to manufacturing becoming more model-based, meaning if a manufacturer has 100 units of the same equipment, they’re going to run them with an identical optimal model.  Since the model has inputs and outputs that will vary, it doesn’t mean that they all run identically, all the time; but the logic that interprets the state of the machine and executes against that same model to run optimally allows a manufacturer to control everything in the same manner. “In that way, when I find a solution that does something new, novel, different, better, I can just apply it across the board to everything, at the same time,” Gaughan explains. 

The Path from Digital Lean to Digital Transformation 

Taking a digital lean approach enables manufacturing companies to leverage data to identify where and how they can minimize waste. Adopting this methodology is a precursor for manufacturers to begin a digital transformation journey. 

“With digital lean you gather data on the entirety of your process to establish the baseline for change. This data allows manufacturers to identify opportunities to remove waste,” Gaughan describes. “The great thing about data is it’s immutable, or it should be. In a properly contextualized data rendering, it tells you something that's important, and anyone that looks at that data is going to come to the same conclusion about what that data means. This also presumes clarity on ‘context’, which is critically important when it comes to data.”

Digital lean methodology gives manufacturers the data they need to know how they can improve their operations. After a manufacturer has collected data from all the interconnected processes on their value stream, then they can move to digital transformation. This data allows manufacturers to pinpoint where to start transforming their operations based on what actions will be most impactful to minimize waste and optimize processes. Gaughan recommends companies create value stream maps, which can be very helpful in this regard.

Manufacturers often make the mistake of committing to easy changes, rather than focusing on what moves the needle on business drivers. Committing to digital lean requires only focusing on the value-added changes, not the meaningless ones. Wasting time on meaningless changes that aren’t data-driven can be hard to overcome when trying to succeed with LEAN.  

“The digital lean component gives me all the meaningful data. The transformation is creating and executing the roadmap to get a manufacturing facility to the desired future state,” Gaughan explains. “If you don’t start with a digital lean approach, you run the risk of working with bad data and flawed decision making. Even worse is simply acting on the loudest voice in the room.” 

How Digital Lean Impacts the Future of Manufacturing 

Digital lean uncovers the waste in a manufacturing facility. As more manufacturers implement this approach and discover the waste in their processes and operations, the industry is going to start to change. 

Some of this change is already happening. As a result of the pandemic, lots of manufacturing companies realized the level of waste in their supply chain. This significantly increased reshoring efforts and has resulted in manufacturing operations returning and growing in and around the United States. 

“A lot of manufacturers in this country have realized they need to do better, and they’re starting to focus on how they can design the best processes and build the best equipment,” Gaughan says. “Once you have the best operation, you can be competitive with anybody globally. When all your resources are creating value at a very high rate, i.e. humans feeding many machines, the cost of labor really diminishes, and it becomes more about the throughput of the machines and the single minute exchange of dies (SMED) concept that keeps uptime at a very high level.” 

As more manufacturers work towards optimization, companies that are not focused on digital lean and digital transformation will be at risk of becoming obsolete. “Even great companies have exposed risk when other companies are using lean design principles in their core business strategy. In the future, manufacturers must be intentional about using lean from design all the way through execution. That’s going to be wildly important to long-term success,” Gaughan emphasizes. 

As adoption of digital lean principles increases, it will give rise to continuous manufacturing methods where manufacturers can produce everything simultaneously. From design to execution, once a process is implemented, the manufacturer will have a constant flow of output. Traditional manufacturing methods can’t rival this continuous manufacturing model. 80% of costs are baked in at the design phase, so if a manufacturing business has a better design, i.e. fewer moving parts, less processes, less raw materials, etc., they’ll have a significant leg-up on the competition. 

There will be manufacturers that embrace these concepts, work through the challenges, and recognize they have developed a model for any manufacturing process, and the only thing that slows down that growth curve will be capital raising. In the situation of legacy companies vs. start-ups, start-up companies don’t carry the burden of legacy systems and bloated overhead, meaning they are nimble, agile, and data rich, and are able to use design principles that cannot be matched anywhere else. 

Over time all production facilities will become continuous, lean, model-based, and AI-infused. Manufacturing companies that can’t keep up will be laid to the wayside. Gaughan expands on this thought: “I don’t know if traditional manufacturing companies can change enough to keep up with these start-ups that do IoT work that are very nimble, very rapid deployment, and have a favorable cost position. That’s going to be critical for the future of manufacturing.”

If you’re a manufacturer looking to get help in your digital lean journey, consider reaching out to the experts at Axiom Manufacturing Systems, and make sure to register for Smart Manufacturing Experience 2024

Patrick Gaughan


Patrick Gaughan worked 33 years at a Fortune 100 company in a host of engineering, supply chain and quality roles. He spent a majority of this time working on plant, process and product design, with a specific focus on root cause analysis, and developed an automation tool to support that function. His last role was working on a combination of continuous manufacturing for traditional batching processes and global MES deployment strategy. Gaughan was the first Lean six sigma black belt in the business unit in 1996, and he has trained other black belts globally, including in China, India, Italy, Germany, Mexico, Canada, Malaysia, and others. Gaughan personally led approximately 50 rapid improvement workshops globally. He is a recipient of numerous corporate awards, including PPGs highest honor of Meritorious Achievement on multiple occasions. Today, Gaughan is a managing partner at Axiom Manufacturing, a company he started with a group of brilliant engineers that share the same passion for excellence and look to upend the traditional systems integrator space.