What draws the next generation of leaders to a career in manufacturing?

While the specifics may vary from person to person, it’s the challenge, and the satisfaction, of seeing a product through from design to being in the hands of satisfied customers in the best, fastest way possible while continuously learning all along the way, according to members of the Next-Generation Panel session at the MLC’s 2021 Rethink Summit this week.

The three 2021 Manufacturing Leadership Award Winners on the panel — Kat Duggan, Coatings Business Learning Leader at Dow; Kasia Karimee Garcia Bracho, Supply Chain Lead at IBM; and Katia Valenzuela, Communications and Design Association, MxD — had so much enthusiasm for their chosen career path that the audience at the virtual event couldn’t help but cheer them on.

Duggan said her experience so far has “really been a joy,” while Valenzuela added, “It’s such a wonderful, innovative world…it was like [I discovered] a treasure trove of opportunities I didn’t even know existed within manufacturing.”

To thrive in that continuously innovating world as it moves into the future, next generation leaders will need some hard and soft skills that perhaps their predecessors did not, such as how to quickly analyze data to make critical decisions, let go of past traditions, and have the flexibility to be open to new ideas, new tools, new technologies, and the new M4.0 culture. Future leaders, they said, must be open and empathetic, able to listen and contribute back to their communities, and able to collaborate with all the people on their teams.

To attract the next generation of leaders, manufacturers also need to ensure that their workforce, especially at the upper echelons, are diverse. As Valenzuela said, “It’s very important to see people who look and act and think like you do in positions of leadership, not just because they bring their own diverse set of perspectives, experiences, and knowledge, but also because they can give someone like me a role model to look up to.”

Bracho also emphasized the importance of fostering a culture where everyone feels welcomed and respected. “Let’s be active and proactive” when it comes to hiring from the outside and promoting from within, added Duggan.

Sustainability is also important to the next generation, they added. New technologies such as blockchain can increase transparency and trust in a company’s ability to maintain standards at every stage of manufacturing. While local or global regulation may drive some sustainability efforts, consistent consumer pressure is ultimately what’s going to change business attitudes and how money is spent.

Bracho cited an IBM survey of more than 414,000 people in nine countries that found environmental responsibility to be a key factor for consumers. “The trend toward sustainability is growing, and it’s something that companies should focus on,” she said.

As to what we’ve learned from the pandemic? Digital is going to be the biggest winner for manufacturing, they said. And with that increasing focus on digital technology comes adaptability, flexibility, a culture of continuous improvement, and the need for an increased focus on cybersecurity.

Manufacturers are generating more data, faster, and from more aspects of their operations than ever before. The key to harnessing all that data to produce higher quality products more quickly and efficiently, and to speed up the decision-making process, is having an intelligent platform and good data governance strategies, agreed Sid Verma, General Manager of the Manufacturing/IIoT Division at Hitachi Vantara, and Mike Lashbrook, Vice President of the Esys Division and Digital Solutions at robotics automation company, JR Automation, during an Executive Dialogue at the MLC’s Rethink 2021 Summit this week.

An M4.0-ready intelligent platform should have several key components, they said. It must enable operators to understand the data being generated and present it in a form that enables users to create analytics or decision models. It must also be able to provide intelligent output based on those models.

To make the system work enterprise-wide, it must also be able to talk to both the OT and enterprise sides, said Verma. And it must be scalable, fault-tolerant so it can self-correct, and the user interface must be consistent with the way people naturally work and think. It  should also be flexible and easy to maintain.

This all sounds good, but how does it work for manufacturers who are still in the process of automating their legacy systems? The increasing need to improve data quality across all the key performance indicators is driving the push toward intelligent platforms, said Lashbrook. “We have an enormous amount of data and intelligence being collected from connected equipment and smart sensors…the system needs to be able to ensure that, if there are small changes in the system, you can adapt on the fly and still get good quality.”

The future, he added, will be a completely integrated digital twin system that can quickly enable the operator to come up with the production model they need to move forward without disrupting the system.

There are challenges to scaling these platforms to where they need to be to achieve a full M4.0 operation, they acknowledged. “It’s a journey for us as a platform company to learn and adjust to be able to provide that value that the OT world needs,” said Verma. IT companies like Google make it look easy, because everything was IT-enabled and the protocols are clean. When you get to the OT side, however, it gets more complicated, depending on the age of the assets and the volume of data involved. While internet companies can just collect all that data and scale it, it gets too costly and difficult to follow their example on the plant floor.

The main challenge is the explosion of data being generated, which session moderator, MLC Co-Founder, Vice President, and Executive Director David R. Brousell called “the 400-pound gorilla in the room.” According to MLC survey data, manufacturers expect up to a 500% increase in data volumes over the next two years as they become more connected.

“Just collecting data on the OT side does not work for us” in the same way it works for a Google, said Verma. “We have seen horror stories where people spent their entire IT budget just collecting data because they didn’t know where to start.”

“Step one has to be stepping back and working with the operational focus. What are those KPIs whose operational efficiencies you want to improve? Then we have to make sure that we collect data around those, not just collect everything,” Lashbrook said. The approach is to focus on the value you’re hoping to create, then collect data associated with that value and figure out which aspects of the legacy systems need adjusting. “In the future, we can look at creating connected systems from day one. But for now, we have to work through these challenges.”

Verma agreed that companies should work upfront to develop a business priority, and a business use case that has an associated ROI, then bring in the engineering expertise. “If you are looking for predictive maintenance, let’s target the most critical failure that can happen. Then let’s try to collect the data to address just that particular failure mode. That way we limit the cost of the solution and the value goes back to the business.”

Many companies don’t have data scientists on staff to help analyze the data, but that shouldn’t stop them, said Verma and Lashbrook. “The first phase of deployment for industry 4.0 is to get that expert knowledge from people in quality and maintenance using older systems and automate that information,” said Verma.

For example, if a technician hears a noise when a motor fails, put in an acoustic sensor that can be alerted when the tech hears that noise. Once your models start showing more accuracy, then companies can begin to layer in data science on the areas that are most business-critical. “That has been our recipe for giving incremental value and industry 4.0 at a much lower cost profile,” he said.

Lashbrook added that, if you don’t have the expertise in house, bring in partners that can fill the gaps. For longer term solutions, look to hire people who have the new skillsets you will need.

“Augmented Reality is definitely cool, it’s relatively easy to use, and it can have a big impact on productivity and quality,” argued Jim Heppelmann, Chief Executive Officer of PTC in an exclusive Executive Dialogue session during the Manufacturing Leadership Council’s 2021 Rethink Summit this week.

Speaking with MLC Co-Founder David R. Brousell, Heppelmann noted that most people have tended to think of digital benefits as always going to knowledge workers, or as part of connected machines and automation. The people who have not really benefited from digital transformation so far, are the frontline workers who stand and work next to those machines.

What Augmented Reality (AR) can do, he added, is to bring digital information directly into that work environment so that front-line workers can easily access and visually perceive information as they are actually doing their job.

It’s a technology that allows “bits and bytes to become sounds and sights”, explained Heppelmann.

Lots of companies have already seen the benefits of AR during the pandemic, he added, citing the example of auto company workers around the world who were able to be rapidly and remotely trained to make ventilators – a vital product which they had never made before.

Those kinds of primary use cases, involving work instructions, or training and mentoring, or remote support, are where many companies are already getting value. And Heppelmann believes there’s still lots of room for improvement. Despite all the digital investments manufacturers have made so far, he estimates that around 50% of front-line work is still not automated.

What’s more, he says that for every knowledge worker in a manufacturing organization there are around three front line workers on the plant floor or in customer facing and service roles. That’s where much of the skills gap exists in the industry today. And as experienced people continue to retire, they will continue take a lot of their domain knowledge with them, so the skills gap is likely to get even worse.

That’s why trying to digitize the knowledge of those retiring workers is also often a primary use case of AR. As companies use it, they are accumulating a large set of digital expertise that can help new workers learn their trade. And by harnessing AI and analytics with AR systems, companies can also ensure every step in a production or other process has been taken correctly and so verify the quality of the work. Over time, that helps all front-line employees to become more productive and more efficient.

“That’s why I call it a revolution,” he concluded. “We are bringing the power of the digital cloud to the front-line workforce for the first time. And that’s a big, powerful idea.”

“The next 60 years will usher in an era where robots will become useful team-mates for people, helping them in both physical and cognitive tasks,” predicted the MIT’s Dr. Daniela Rus during her keynote session on the final day of the MLC’s 2021 Rethink Summit this week. “They will have a wide range of capabilities and will come in a variety of forms and materials, inspired by nature, by our built environment, and by our imagination.”

Rus, who is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science, and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, continued: “Today we are surrounded by a world of digital opportunities. These possibilities only get larger when we start to imagine what we can do with advances in AI & robotics.”

Those advances will not only fundamentally transform the human/machine relationship, she believes, but will also lead to completely new kinds of production strategies and manufacturing business models.

“We assume that robots and AI will lead to fewer manufacturing jobs,” noted Rus, “but what if they really bring better jobs that allow workers to control production lines more finely and configure them rapidly for customized production? This could meet the rising demand for customization and personalization in almost everything we buy, and at an affordable price point. It would be a world where product templates get designed by specialists, customized by people at home, and fabricated locally. This means a whole new approach to production and jobs.”

Looking back, Rus identified three waves of robotics development so far: a first wave of large, constrained, and potentially dangerous industrial robots; a second wave of more flexible and autonomous robotics systems; and the current wave of automation where we are “building machines that can perform increasingly more complex physical and cognitive tasks in human-centred environments.”

This progress is being enabled by advancements in three interconnected fields, she noted, robotics, AI, and machine learning. She also acknowledged that there are tasks that people do better, and tasks where machines are better at the job. “The sweet spot today”, she said, “is to consider teams of humans and machines working together – to view machines as “Super-tools”, or as autonomous interns running errands or pouring over data for humans to act on.“

But while the last 60 years has been marked by robots mostly inspired by the human form, the next stage, Rus believes, will be more adaptive soft robots inspired by the animal kingdom and form diversity, by our built environment, and with far broader application potential. The future of AI-enabled robotics, she says, “will be inspired by nature – with machines becoming soft like materials, and materials becoming more intelligent like machines.”

To support her point, Rus showcased multiple examples of innovative lab prototypes based on computational design and leading-edge fabrication ideas already under development, from under-water robotic fish for sub-aqua applications, to origami-inspired grippers, to micro-bots that can choose different wraps depending on the tasks they need to perform, to robots that can interpret and mirror human muscle movements, to robots that harness deep learning systems to interact with human language and even respond to some instructions via human brainwaves.

“These are a good starting point for reimagining robots for production,” she added. “Imagine a world where if you can think it, you can make it. A world where anybody can create custom tools, custom robots, and custom products – on demand.”

So, as companies continue to embrace the use of autonomy and automation in manufacturing, Rus believes they need to be prepared for a constantly evolving manufacturing landscape in the years ahead that incorporates AI, robotics, and machine learning tools, and they should strive to better understand how these tools can impact all the processes in the factory, how to take advantage of those processes, and how to use computation and data in order to improve operations.

This, she stressed, requires developing both the right infrastructure and a workforce that is re-skilled to understand how to use the new tools, “because human/machine collaboration requires both better machines and humans who know how to leverage those machines.”

And companies need to start that process now. “It is not enough just to train the workforce of tomorrow,” Rus concluded. “We need to get serious about reskilling the workforce of today and cultivate a culture of agility and lifelong learning in every organization.”

“Manufacturers do not accept that anything is impossible.”

In his opening speech for Rethink: The Manufacturing Leadership Summit, National Association of Manufacturers President and CEO Jay Timmons reflected on the world’s emergence from the COVID-19 pandemic and how digital technologies played a role in keeping factories open, keeping goods moving, and especially in keeping workers safe.

Timmons cited MLC research that “the march to Manufacturing 4.0 has become a sprint” as 40% of companies reported that the pandemic accelerated their digitization plans. Indeed, manufacturers who had robust digital operations in place were shown to be in a better position to respond to the pandemic’s disruption, and others quickly got on board with bringing in collaborative and remote operational technologies to keep production lines running.

In examining specific transformational examples, Timmons pointed to 2021 Manufacturers of the Year Dow and Hologic. Dow’s digital transformation throughout its operations eliminated 2 million hours of work in potentially hazardous environments and allowed for significant year-over-year gains in value, even during the pandemic. Meanwhile, Hologic introduced a talent management system that prepares its employees to work in factories of the future and halved the time necessary to bring new employees through the onboarding process.

In closing, Timmons hearkened to manufacturers’ unflappable determination and continuous quest for improvement despite any challenges along the way.

“We can build the world we want to see, and today, manufacturers are determined to see us through our crisis and build a better world for tomorrow.”

When it comes to making a digital transition and realizing ambitious business outcomes, Shell believes that technology might be the least important element.

During his session at Rethink: The Manufacturing Leadership Council Summit, Peter Westerink, General Manager of Digitalization Downstream Manufacturing at Shell, said that the energy company believes transformation is driven 60% by data, 30% by people, and 10% by technology.

Shell has significantly increased its investment in digital adoption, including growth to 1.3 trillion rows of sensor data in its data link, significant growth in its data-focused workforce, a tenfold increase in the use of virtual rooms powered by AR, and the use of AI to monitor more than 6,000 pieces of equipment.

Digitalization and AI are driving efficiencies in Shell’s business by maximizing availability for equipment (“find small and fix small”) and optimizing production in real time while decreasing CO2 emissions. Shell integrates data into a digital twin to enhance collaboration, automation, and remote operations that has gone live in one production facility with plans underway for five others.

Shell is also using these efforts to grow its clean energy capabilities. This includes AI for optimizing electric vehicle charging stations to save money for customers and monitor the power grid. Additionally, the company is using data-driven modeling and physics-based models for hydrogen production, storage, and transport, and using AI to assist in selecting wind turbine locations and optimize windfarm design and construction.

Westerink says Shell is thinking bigger to make energy smarter and sees a brighter future ahead. “We’re excited by the capabilities and communities we’re building, excited by the impact our projects are already having, and excited by the potential we haven’t yet realized.”

Three Steps Toward Manufacturing Resiliency

The manufacturing business environment can be unpredictable. Supply chain disruptions occur, demand for products fluctuates, and game-changing innovations quickly appear on the horizon. To stay in business and remain competitive, manufacturers must anticipate and respond to both foreseen and unforeseen changes.
What’s the key to this responsiveness? Manufacturing resiliency. And the driver behind this resiliency is data-driven production execution supported by digital technologies.
Hard Lessons
Hard lessons have been learned in the wake of the novel coronavirus pandemic. Manufacturing has been particularly hard hit. Companies that were able to react quickly, retool their factories, redirect their supply chains, and take advantage of digital technologies quickly switched gears to meet crucial needs and create new opportunities

For example, clothing designers and manufacturers such as H&M, Brooks Brothers, and Hanesbrands retooled their factories to produce face masks, medical gowns, and protective aprons for hospitals. Spirits manufacturers Bacardi and Brown-Forman shifted their distillery operations to manufacture hand sanitizers for first responders. And production lines at Fiat Chrysler Automobiles, Ford, and GM are now turning out ventilator parts, respirators, and other much-needed medical equipment.[i] In addition to meeting urgent worldwide needs, these companies have created a culture of resiliency in their operations that will be valuable to them and the communities they support in both the short and long term.
Three Steps to Resilient Manufacturing 
By taking the following three steps, you can transform your manufacturing environment to become more resilient and improve operations. You can more effectively meet the needs of your customers under any circumstances while creating new opportunities for your business.
1/ Increase flexible automation to create resilient operations.
The manufacturing industry has come full circle, from the days of hyper-customized craft production before the first Industrial Age, through mass production in the early 1900s, to manufacturing as it is today. With the trend toward personalization that we’re now seeing in the marketplace, the manufacturing industry is moving back to hyper-customization, or a lot size of one.
However, in this Industry 4.0 iteration, hyper-personalization is being done at scale. Flexible automation is at the forefront of this evolving story. Robotics and artificial intelligence (AI) are the key technologies that make flexible automation at scale possible, enabled by 5G, Time-Sensitive Networking (TSN) and Open Platform Communications (OPC).

On the road to full automation, we can also expect to see more scenarios where humans work collaboratively with robots. This collaboration could take many forms. For example, workers could adapt their tasks to preconfigured robotic operations. However, with rapid advancements in robotics and AI, future production lines could also be staffed with robots that have the intelligence and situational awareness to easily work alongside humans, adjusting their behavior according to each worker’s style and speed.
The technologies that will drive this digital transformation include robotics and mixed reality, with 5G, IoT and AI serving as the digital backbone and application enablers.
2/ Introduce remote operations to ensure business continuity in adverse situations. 
Prior to the pandemic, there was a lot of industry buzz and some solid proof points for deploying augmented reality (AR) and virtual reality (VR) in manufacturing, particularly within the maintenance function. However, not everyone believed this technology would be quickly and widely adopted.
Now, as companies have been forced into embracing remote working, we’re seeing a renewed enthusiasm among executives for these technologies. There’s a heightened urgency to incorporate remote operations as an integral means of supporting manufacturing operations, whether for product quality inspection, equipment maintenance tasks, or even collaborative tasks involving product design and production planning.
Technologies that can be seamlessly integrated into work environments will quickly evolve to include key enablers such as digital twins, 3D visualization, and private 5G.
3/ Adopt a digital infrastructure that connects all parts of the supply chain. 
One of the serious manufacturing-related impacts of the pandemic and subsequent shutdowns was the significant disruption to the supply chain. Many enterprises were scrambling to source needed materials and components, and distributors were scrambling to deliver them. This situation brought home how essential digital technologies are for managing the complexity and variability of today’s sophisticated and vulnerable manufacturing supply chains.
Industrial data lakes play a key role in transforming traditional production software stacks into digital production platforms. In the manufacturing environment, data lakes enable real-time connectivity to various information layers involved in manufacturing operations, from programmable logic controllers (PLCs), to manufacturing execution systems (MES), to enterprise resource planning (ERP) systems. This end-to-end connectivity will enable a seamless information flow across the entire supply chain. In addition, it will help scale any application deployed in one plant, to any other plant anywhere in the world, improving overall return on investment (ROI).
Together, with several other emerging technologies, industrial data lakes will eventually help shape the vision of distributed manufacturing and personalized manufacturing. Additionally, industrial data lakes will play a critical role in scaling digitized accumulated know-how as we transition toward the vision of the digital worker.
Lessons Learned 
Though the manufacturing industry doesn’t always operate in crisis mode, there are valuable lessons about resiliency to be learned from the pandemic. Any manufacturer can take these lessons to heart and transform their factory into an agile, responsive environment resilient enough to weather whatever changes may come.

[i] https://www.triplepundit.com/story/2020/companies-retooling-operations-covid-19/88921

GM: Data’s Infinite Potential

Posted by Paul Tate | Oct 29, 2020 | Ideas & Insights, 2020 Virtual Rethink MLC Summit

With a vast global network of production facilities ranging anywhere from 25 to over 100 years old, and a production staff of over 140,000 people around the world, General Motors generates massive amounts of data every day.
As the cars it produces become ever more intelligent, and as new production technologies like dedicated additive manufacturing systems in all its factories, new developments in collaborative robotics on the shop floor, and specialized new metal forming innovations underway, those data volumes are growing fast.
So how does GM view the potential of all this data for the kind of products it makes and how it will make them in the years ahead?
“It’s infinite,” predicted GM’s Executive Vice President of Global Manufacturing, Gerald Johnson, in conversation with MLC Co-founder David R. Brousell during the opening keynote session of the 2020 Virtual MLC Rethink Summit this week.
As the recent winner of the MLC’s 2020 Manufacturing Leader of the Year Award, Johnson was talking about GM’s Manufacturing Vision and its own journey to Manufacturing 4.0.

“There’s no real destination to our smart manufacturing journey,” continued Johnson, “because the technology keeps growing. It’s really about grabbing and integrating what allows us to move forward from where we are today, and then looking out as we start strategizing and planning our future to make sure we are always able to incorporate what’s available to us.”
Understanding and using data more effectively is a key part of that journey. “I think the technology will help people make better decisions and help make decisions faster,” he added. “We will be able to do things better in a digital world, shrinking the time it takes to go from idea to execution, and shrinking the time it takes to move from equipment on the floor to full operation.
“It’s about understanding how much we can put into the digital world with enough accuracy that it allows us to predict better, allows us to prevent better, and allows us to move from an idea to a tangible, physical asset in a highly efficient execution faster. That’s where I think the greatest opportunity is.”
To help drive this digital ambition, GM has a rapidly expanding data analytics organization where analysts spend significant amounts of time on GM’s plant floors asking front line management and operators exactly what problems they are trying to solve. “Then they are coming back to us and saying, ‘I think we can help you with this by aggregating these sets of data’. So, it’s a marriage of the experts who understand data techniques, and the plant guys who understand the problem. Then they are collaborating together in workshops to find new ways that data can help to solve things,” he said.
But for Johnson, that’s only the beginning of harnessing the potential of all the data that GM is now collecting. “The reason I say it is infinite is because I don’t know the question that I will need to ask a year from now, or five years from now. But if I have an infinite data set, when I get to the right question, I don’t have to create all the connectivity and create all the data gathering we need. All I have to do is to find the right tools to extract that data in very intelligent ways.
“So, it’s infinite”, he concluded. “There’s millions of bits of data that we are now collecting every day that I don’t even know I need yet. But I’m grateful to IT team for finding efficient ways for us to keep it, so when I figure out the question I want to ask, it’s there so we can start manipulating it to answer questions that we aren’t smart enough to know we need to answer yet. To me, that’s exciting.”
“It’s like looking up into the universe and trying to count the stars,” he explained. “You can’t. But it’s amazing that it’s out there.

Virtual Rethink: An Embrace of All Things Digital

Posted by Penelope Brown | Oct 27, 2020 | Ideas & Insights, 2020 Virtual Rethink MLC Summit

Rethink: The Manufacturing Leadership Council Summit kicked off on October 27, for the first time as a virtual event since its inception. MLC Co-Founder, Vice President and Executive Director David Brousell kicked off the event with remarks focused on the immense disruption that manufacturing has faced during a challenging year – and the ways that digital technology has helped organizations rise to the occasion.
Brousell cited MLC’s own research that demonstrated how the ability to adapt to rapid change was clearly linked to an organization’s digital maturity. In May, 67% of respondents to an MLC poll said digital technologies were important to their ability to respond to the crisis, whether it was shifting production lines, enabling remote capabilities, or mitigating supply chain disruptions.
Also noted were the challenges to developing a digital-first organization, including the mind-numbing volume of data that manufacturers can now acquire – everything from equipment utilization to product lifecycle to customer satisfaction. While acquiring that data is the first step, it is essential to have the ability to organize that data, rely on its accuracy, and make decisions based on that information. As an industry, many manufacturers still struggle to achieve this level of digital mastery.
Additionally, executive leadership is now tasked not just with needing traditional business skills but also digital acumen – an area where many find themselves still lagging.
“Perceptions change as a greater sense of urgency comes on,” Brousell said. “It seems the digital revolution is no longer in the future, but it is now.”

2020 Manufacturing Leadership Award: Winners Recognized at Virtual Gala

Posted by Penelope Brown | Oct 8, 2020 | Uncategorized, Ideas & Insights

Winners of the 2020 Manufacturing Leadership Awards were honored at the 16^th annual ML Awards Gala, hosted by the National Association of Manufacturers’ Manufacturing Leadership Council. The event took place online.
Gerald Johnson, Executive Vice President, Global Manufacturing at GM, was selected as the Manufacturing Leader of the Year for his leadership in GM’s pivot to ventilator production in a partnership with Ventec Life Systems, code named Project V.
Corteva Agriscience was selected as Large Enterprise Manufacturer of the Year for its strong nominations in multiple project categories, using data to streamline operations, boost supply chain resilience, and meet demand.
Humtown Product was named Small/Medium Enterprise Manufacturer of the Year. A longtime leader in the metalcasting industry, the company utilized 3D printing to revolutionize production, boosting its capabilities and allowing it to serve new markets and customers.
“The need for digital transformation in manufacturing is more urgent than ever, and these companies and leaders are examples of some of the best,” said MLC Co-Founder, Vice President, and Executive Director David R. Brousell. “I commend this year’s winners for their noteworthy accomplishments and for continuing to expand what is possible.”
Also honored at the ML Awards Gala was Jeff Moad, creator of the Manufacturing Leadership Awards and its director until his retirement in 2019. Since its inception in 2005, the awards program has recognized thousands of projects from global manufacturers, and Jeff was instrumental in creating its mission and leading its development.
Nine recipients of ML High Achiever Awards were also announced. The High Achiever Awards are presented to the project that receives the highest score from the judges in that category.
High Achiever Award Winners:

• Lockheed Martin in the Artificial Intelligence and Advanced Analytics Leadership category for F-35 Augmented Reality Shop Floor Mobility
• Merck & Co., Inc., in the Collaborative Innovation Leadership category for Digital Fingerprinting
• Humtown Products in the Engineering and Production Technology Leadership category for Commercialization of 3D Printing in the Metal Casting Industry
• IBM in the Enterprise Integration Technology Leadership category for Migrating Supply Chain Quality Workload to Cloud
• Cooley Group in the Industrial Internet of Things Leadership category for Cooley Group Transforms Legacy Machinery into Smart Tech
• Hologic Inc. in the Operational Excellence category for Building a Culture of Operational Excellence
• Starkey Hearing Technologies in the Supply Chain Leadership category for Starkey Supply Chain Management Transformation
• The Boeing Company in the Sustainability Leadership category for Diverting Waste to Landfill While Upcycling Excess Airplane Carbon Fiber
• Nexteer Automotive in the Talent Management category for Nexteer for m.e. Global Talent Management and Training Program