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It’s time to think way outside the proverbial box, according to the Manufacturing Leadership Council, the NAM’s digital transformation arm. In fact, as we get closer to 2030, manufacturers are creating entirely new boxes—including new digital business models, products and services, revenue streams, ways to serve customers and opportunities to increase competitiveness.

Collaborative innovation: By 2030, metaverse technologies will provide rich virtual environments for the collaborative development of new ideas. These shared virtual spaces will enable contributors from multiple remote locations to collaborate in real time.

• These collaborations may include manufacturers, partners, academic institutions and research institutes.
• New concepts can be tested in a virtual world before moving to physical prototyping or production.

Outcome-based products and services: As digital platforms mature and products become increasingly smart and connected, the decade ahead may see a boom in more outcome-based services. This is where the customer doesn’t buy a physical product, but instead signs up to pay for the guaranteed outcomes that product or system delivers.

• This shift will require manufacturers to establish new infrastructure rich in predictive analytics, remote communications and consumption monitoring.
• It also requires a mindset change for traditional manufacturing, from a focus on units and costs to product lifecycles, performance levels and usage.

Blockchain networks: By 2030, blockchain could be leveraged for most world trade, helping to provide the secure traceability and provenance needed to prevent physical product counterfeiting, grey markets in medicines and even the adulteration of the global food supply chain.

• A blockchain is an electronically distributed ledger accessible to multiple users. Blockchains record, process and verify every transaction, making them safe, trusted, permanent and transparent.

• Blockchain technologies promise to be a viable solution to manufacturers’ need to automate, secure and accelerate the processing of key transactions across industrial ecosystems.

E-manufacturing marketplaces: Digitally empowered production-line adaptability, such as the kind that emerged during the pandemic, will provide a foundation for companies to offer spare production capacity to other companies in different sectors.

• This maximizes the return on a company’s production-line investments and can generate new revenue streams for the future.
• Combined with e-commerce, e-manufacturing will enable designers, engineers and/or smaller companies to more easily connect with a large pool of qualified producers to deliver and scale a final product.

Manufacturing in 2030 Project: New Boxes is just one of the industry trends and themes identified by the Manufacturing in 2030 Project, a future-focused initiative of the MLC. For more details on megatrends, industry trends and key themes for Manufacturing in 2030, download the MLC’s new white paper “The Next Phase of Digital Evolution.”

Now that 2023 is here, we’re looking back on 2022’s top tech trends in manufacturing. The NAM’s digital transformation arm, the Manufacturing Leadership Council, and its innovation management division, the Innovation Research Interchange, gave us an overview.

AI everywhere: From automatically responding to shifts in production demand to anticipating breakdowns in the supply chain, artificial intelligence showed up more than ever before throughout manufacturing operations.

• More than two-thirds of manufacturers are either using AI now or will be doing so within two years, according to MLC research.
• Current use cases include predicting needed maintenance for equipment, forecasting product demand and monitoring performance metrics such as productivity and efficiency. Future use cases could include fully autonomous factories that run continuously with minimal human intervention.

Training on demand: Training for technicians and frontline operators used to mean time in a classroom with a live instructor. In 2022, more manufacturers turned to virtual, on-demand learning tools that allowed workers the freedom to learn at their own pace.

• This ran the gamut from video content libraries to immersive augmented reality/virtual reality experiences that guide and correct trainees.
• In 2023 and beyond, this type of learning experience will be essential to attracting and retaining younger workers who are familiar with digital learning and want the latitude to gain new skills on their own schedules.

Digital twins: Manufacturers used digital twins—virtual models designed to reflect a physical object, system or process accurately—to create design prototypes and test their performance.

• Digital twins will continue to allow for new levels of design optimization, improved product development and performance and significant waste reduction for manufacturers.

Robotic collaboration: Once confined to steel cages and bolted to floors, industrial robots took center stage in 2022.

• No longer limited to repetitive tasks and kept far from human workers, new-generation robots are safe enough to work alongside employees, can be moved quickly around shop floors and are programmed easily to do multiple tasks.
• Since they’ve also become more affordable, they’re an economically feasible investment for companies of all sizes.

Cybersecurity as safety: A rise in connected factories also meant a rise in cyberattacks on manufacturers. In an industrial setting, a cyberattack can be very dangerous, as it can cause equipment to malfunction.

• Last year, more companies began addressing the threat with cyber drills, tabletop exercises for simulated attacks and other training exercises designed to keep businesses—and workers—safe and secure.

Low-code/no-code development platforms: In 2022, more manufacturers embraced the use of mobile and web apps to build applications quickly. Using these platforms, enterprise and citizen developers can drag and drop application components and connect them to create apps—without line-by-line code writing.

• Business teams with no software development experience built and tested applications without any knowledge of programming languages, machine code or the development work behind a platform’s configurable components. We can expect to see more of it this year.

Smart glasses move beyond the pandemic: Many manufacturers kept up their pandemic-era use of smart glasses, which they had used to troubleshoot issues on the ground when travel was restricted and engineers and technicians couldn’t reach sites.

• They also expanded smart glasses’ use to include scanning sensor data so users can see visual data “mapped” onto equipment to better identify issues and fixes.

Interested in learning more? Check out the MLC and IRI for more insights into manufacturing’s exciting, high-tech future.

Manufacturers are pursuing sustainability like never before.

That’s according to recent polling conducted by the Manufacturing Leadership Council, the NAM’s digital transformation division. The annual Sustainability and the Circular Economy research survey seeks to determine the progress made in sustainable manufacturing.

Competitiveness: There has been a surge in the number of manufacturing executives who view sustainability as critical to the future of their businesses.

• 58% of respondents in 2022 believe sustainability is essential to future competitiveness compared to 38% in 2021.
• 68% of executives say they are implementing extensive, corporate-wide sustainability strategies. That’s up from just 39% in 2019.

What’s driving change: The motivations go beyond regulatory compliance and cost savings.

• 78% say sustainability is about better alignment with corporate values.
• 68% believe in creating a cleaner, healthier environment.
• 66% seek to improve company reputation with customers and investors.

Top corporate goals: More than half of survey respondents reported having specific sustainability goals and metrics across almost all key functions in the company.

• Goals were most apparent in manufacturing and production (79%), supply chain (69%) and product design and development (67%).
• Additional goals were cited in transportation and logistics (56%) and partner compliance (51%).

Energy efficiency is No. 1: The primary sustainability focus of manufacturers, according to survey results, is energy efficiency and reduction, combined with the transition to renewable energy sources. These efforts are linked intrinsically to meeting net-zero emissions goals.

• 45% of respondents report having announced formal net-zero goals.
• 30% aim to hit net zero by 2030.

Digital tech, employee training play a role: Also on the rise is the number of companies that recognize the importance of digital solutions in their sustainability efforts.

• These tools are being used to manage and monitor materials and energy consumption, optimize operations to improve efficiency and report sustainability progress.
• Respondents also say meeting sustainability targets must include engaging employees through education and training, as well as greening their supply chain.

The last word: An overwhelming 90% of all respondents agree that manufacturing has a special responsibility to society to become more sustainable and accelerate the transition to a future circular industrial economy.

Interested in putting some renewable energy solutions into action, including solar power, battery storage and LED lighting? Programs from utility companies and other entities enable efficiency upgrades with little or no upfront capital. Connect with NAM Energy to explore your options!

If you were looking for a dose of optimism to counter the troubling reality of the post-pandemic world, you could do a lot worse than turn to the start-up community. Even in the best of times, the odds are stacked ruthlessly against anyone considering starting a business. And these are hardly the best of times. Yet new ideas and the magic combination of hope and conviction that supports them, continue to pour forth in a torrent. According to the U.S. Census Bureau, Americans started 4.3 million businesses in 2020, a 24% increase from 2019, and by far the biggest number in a calendar year in the previous decade and a half.

As an investor, and a mentor for Creative Destruction Labs (CDL) I meet a lot of founders, and I watch a lot of introductory pitches. And while the enthusiasm is ever-present, it is not uncommon, after the founder has left the room, for those who have just watched the pitch to turn to one another and say something like: “I still don’t know what they actually do.”

The effective communication of a new product’s value and function is, I believe, the biggest challenge facing any start-up founder. This is about knowledge transfer. It is a prerequisite of every progressive step the company hopes to take. And it is particularly difficult for companies that are bringing to market – either as a core product or as part of a wider service or solution – a complex mechanical object (CDL focuses on science and technology start-ups).

These founders have to convince investors to fund their project; they have to explain defensible intellectual property to patent attorneys and granting authorities; they have to communicate requirements to sub-component suppliers and manufacturing partners; they need to convince buyers and users that the product can deliver; they must ensure anyone responsible for maintenance and repair knows exactly what’s required to keep it operational.

That is a broad audience, each with a specific set of knowledge transfer needs. So to be effective, communication needs to be highly versatile, and to deliver absolute clarity through the most efficient processes. If this capability isn’t baked into the organization from the outset, the best case scenario is that the challenge scales as the company becomes successful, creating a much bigger problem which can have a direct impact on operational KPIs.

As products come to market they bring with them a host of documentation and content requirements associated with that knowledge transfer. Creating and maintaining this content is a huge task and one that can easily become a bottleneck. If the content isn’t ready, the product can’t be promoted or sold. If it isn’t completely accurate, if it’s hard to access, if doesn’t tell the full story, you could be looking at fabrication or maintenance errors and costly downtime.

Advances in manufacturing technology – the adoption of agile workflows and additive manufacturing – actually make things worse. These processes accelerate product development and iteration, making the documentation and content bottleneck even more damaging.

Macro realities compound the problem yet further. Once upon a time a new company would start by bringing a core team together at a new premises. However, full-time, on-site work looks like a thing of the past. Studies suggest 70% of the workforce will remain working remotely five days per month by 2025 with others opting to work part-time on-site and part-time at home. And, in any case, start-ups tend to rely on a distributed ecosystem of product and service suppliers from the outset, for obvious reasons.

And according to a 2020 McKinsey report, Unlocking growth in small and medium-size enterprises, SMEs have innate productivity challenges, exacerbated by lack of access to high-cost enterprise software solutions. So, to ensure effective communication – to give themselves the best possible chance of success – start-ups today must find a way to drive effective teamwork and collaboration among a distributed workforce and ecosystem, at an affordable price point, all while driving productivity, in order to become competitive.

No pressure.

But start-ups have an advantage. Their primary strength in addressing these challenges is their capacity for continuous innovation, not just in terms of products and services but also – crucially – in terms of processes. This owes a huge amount to that optimism which got them started on the journey in the first place. According to McKinsey, “Because they are unhindered by legacy systems and outdated strategies, new market entrants are often able to rethink established practices and cut through traditional industry boundaries.”

Here’s a great example: Impossible Sensing is a CDL alumnus that develops and manufactures autonomous exploration tools designed to function in extreme environments from deep ocean to deep space. Their products are used to detect valuable minerals in off-planet environments. Prior to the pandemic, Impossible Sensing’s founder used 3D-printed models to enable prospective buyers – a Mars scientist at NASA, for example – to get a tangible sense of the firm’s products.

Restrictions on face-to-face meetings put an end to that, leaving this CEO suddenly missing a key part of his sales pitch. He overcame this by using interactive 3D communication which allows customers to play with the 3D models of his product (the closest thing to handling that 3D-printed object) wherever they were located. Video calling is great for replicating the conversation, but there are a number of critical communication experiences that it simply cannot deliver.

Many people might have focused on the frustration of being unable to continue to operate as they had before. But the start-up’s optimism will always find another way.

A start-up’s Big Idea is only as good as the extent to which it can be understood by everyone whose participation is required to make it successful. Get in front of that effective communication challenge as early as possible – solve that knowledge transfer problem across the board – and not only will you be giving yourself the best possible shot at success, you’ll be future-proofing your business against problems which can undermine you as you grow.

About the author:

Patricia Hume is Chief Executive Officer of Canvas GFX.

About 100 Manufacturing Leadership Council members, associate members, guests, and staff descended on Lexington, Ky., in November for a tour of Schneider Electric’s smart factory – a 65-year-old brownfield facility that showcases artificial intelligence, augmented reality, remote monitoring, and predictive maintenance.

The factory was recognized in 2020 as a Fourth Industrial Revolution Advanced Lighthouse by the World Economic Forum (WEF) and later as a Sustainability Lighthouse, one of only ten globally and the first of two for Schneider Electric. It is one of several Schneider Electric factories to achieve this designation, and the company’s first on U.S. soil. Schneider Electric, a 180-year-old company, had E28.9 billion in revenues in its 2021 fiscal year. The company provides industrial automation and control, energy management, and building automation and control products and services.

What They Saw: During the 11-stop tour, participants experienced the complete breadth of Schneider Electric’s manufacturing process. The Lexington smart factory houses a complete, vertically integrated process including a typical assembly line, conveyance, fabrication center, paint room, and more – all connected through Schneider Electric’s Industrial Internet of Things-based (IIoT) EcoStruxure platform.

The tour showcased how Schneider Electric’s digital transformation increased energy efficiency and reduced downtime. AVEVA and Schneider Electric partner on integrated digital transformation solutions that bring together energy management and automation tools with industrial software. In Lexington, the company utilizes both its EcoStructure and AVEVA platforms throughout the facility. For example, at tour stop nine participants saw how the EcoStructure Lean Digitization System calculates true labor efficiency with e-performance and e-andon — digital data-sharing and production monitoring of performance and defects for immediate response. Meanwhile at stop seven in the paint room, the group learned how AVEVA Edge processes data and populates the company’s dashboards in real-time.

In a fascinating application of AI and machine learning, the company has set up a 5G networked camera to photograph and analyze every link in the mile-long conveyer chain. The photos are then automatically compared to thousands of images of broken and unbroken chain links, and the AI-powered system identifies broken and breaking links that need to be repaired and relays this information to the operator.

Insights from Digital Subject Matter Experts: Beyond the smart factory tour, participants joined breakout sessions where they heard directly from Schneider Electric experts about hardware and software tools used in the company’s digital transformation journey to help breakdown data silos and empower employees to make effective decisions at the gemba – the real place where they do their work. Breakout topics included Smart Factory Execution, EcoStruxure Deep Dive, EcoStruxure & Industry Automation, Cybersecurity and Operations, Advanced Analytics in Supply Chain, and Supply Chain Sustainability.

Unfettered Access to Company Leaders: The day ended with a discussion panel during which Schneider Electric leaders answered questions from both the audience and moderator, Jeff Puma, MLC’s Content Director. The panel featured Greg McManaway, Business Process Leader; Fabrice Meunier, Vice President, Industrial End User, System Integrator and Software Business; Anand Varahala, Environment and Sustainability Manager; and Bharat Virmani, Vice President, Supply Chain Performance and MTS/MTO Cluster. The panelists shared their insights on topics including the factory’s digital transformation journey, the WEF Lighthouse process, setting priorities, and scaling digital advances.

A Chance to Rub Elbows: In addition to witnessing the innovations and smart factory implementation at Schneider Electric’s Lexington facility, the tour offered an opportunity to interact with nearly 100 industry leaders in attendance including digital pioneers from both the host company and other MLC member companies. Like all MLC tours, the formal and informal networking opportunities allowed participants to ask questions, discuss hurdles, and seek solutions from other participants on the digital transformation journey. These relationships are invaluable to members’ efforts to expand their connections and Manufacturing 4.0 understanding.

Learn more about upcoming MLC plant tours

All photos by Ian Wagreich; Copyright: capitolhillphoto.com

When toddlers learn to stack blocks, they learn by trial and error — often with immediate feedback from a parent or other adult. It is a model-free learning process, or reinforcement learning, that does not require them to learn Newton’s equation to figure out how to stack the blocks.

For Dr. Hiroaki Kanokogi, Yokogawa Digital Corporation’s President and CEO, reinforcement learning (RL) in artificial intelligence (AI) has direct uses in a manufacturing environment. In fact, as Kanokogi shared during the Manufacturing Leadership Council’s Manufacturing in 2030 Project: Let’s Talk About AI event, RL was a building block when Yokogawa used AI to autonomously control a Japanese chemical plant for 35 days earlier this year.

In his presentation at Let’s Talk About AI, Kanokogi shared that there are serious challenges to applying RL to real world manufacturing. First, he said, traditional RL takes 1 million to 1 billion trials to go beyond human learning, and second, manufacturers must include safety assurances.

To overcome the first of these challenges, Yokogawa and the Nara Institute of Science and Technology developed scalable reinforcement learning called Factorial Kernel Dynamic Policy Programming (FKDPP) specifically for plant control. FKDPP allows for faster learning (typically in about 30 trials) and robust protection against disturbances. Yokogawa was able to demonstrate that FKDPP can autonomously stabilize water levels in a fundamental three tank level control experiment significantly quicker than traditional proportional-integral-derivative (PID) control.

At Let’s Talk About AI, Kanokogi shared four videos that chronicled FKDPP’s iterative attempts to stabilize the water. In the first iteration, AI does not know anything yet, so when the valve is opened the water level goes all the way up. In the 20th iteration, AI can control the water in a somewhat stable manner, but it varies and resembles a human’s performance on the task. For the 25^th iteration, AI learns how to regulate the variation. By the 30^th iteration, the FKDPP perfects the process. Kanokogi pointed out that this final iteration demonstrated that once AI finds a good way, optimization of this process is AI’s strength.

For the second challenge around safety assurance, Yokogawa was able to prove AI can satisfy this need during this year’s 35-day autonomous factory operation. The company first built a good simulation model by using domain knowledge in a digital twin so the AI could learn. Step two called for simulation and evaluation using both past and live data. Finally, the company ensured safety and control in the actual plant using Yokogawa’s integrated process control system, CENTUM™ VP DCS.

For Yokogawa and its autonomous operation, Kanokogi reported that he and his team continue to look at problems in the factory where AI can be applied. While the first-of-its-kind, 35-day automation demonstration is truly impressive, he sees manufacturing working in an autonomous plan-do-check-act (PDCA) loop by 2030. This loop will run continuously, and AI will help the plant improve itself. While there is no need for human intervention during this loop, Kanokogi pointed out that AI cannot add new sensors or integrate new technologies, so human experts will maintain a defined role in manufacturing.

Like a toddler with blocks, autonomous factory operation might be in its nascent years, but with the help of AI and Yokogawa’s FKDPP technology, maturation by 2030 is possible.

Manufacturing in 2030 Project: Let’s Talk About AI was held Dec. 7-8, 2022 in Nashville, Tenn. The event was part of MLC’s Manufacturing in 2030 Project.

AI will become a key player in driving manufacturing competitiveness in the years ahead.

David R. Brousell, Co-founder of the NAM’s Manufacturing Leadership Council, called on all manufacturers to accelerate their understanding and use of new Artificial Intelligence (AI) technologies in his opening speech at the MLC’s latest Manufacturing in 2030 event, Let’s Talk About AI, in Nashville, Tenn., this morning.

“The stakes for our industry and our country couldn’t be greater as our economy becomes increasingly digital,” asserted Brousell. “Global competition for dominance in AI is underway, with manufacturing as a key player in the race. Our competitiveness as an industry at home and abroad will increasingly be defined by AI expertise, application, and experience – and in a trusted and responsible way.”

Technologically, he noted, AI is finally coming into its own after a long development period and researchers now estimate that the value of the global AI industry will rise rapidly from $93.5 billion in 2021, to a substantial $1.8 trillion by 2030.

AI is also a pervasive technology, he continued, meaning that it will be incorporated into many other technologies including semiconductors, software applications and platforms, and communications equipment. It will increasingly power the operation of  front-office applications, ERP, PLM, MES, CRM and other key operational applications. Robotic systems, too, will increasingly be guided by AI.

And although only 9% of respondents to a recent MLC study said that they saw AI and ML as a game-changer for the industry today, by 2030, 53% said that they believed it would indeed become a game-changing transformative force.

Citing a U.S. Patent Office report from October 2020 that stated, “AI is poised to revolutionize the world on the scale of the steam engine and electricity”, Brousell stressed that’s why manufacturers now need to better understand how AI may shape how they run their factories and plants, how it will influence their workforce strategies, what business benefits may attend AI use, and what challenges the industry must overcome to realize its potential in the years ahead.

However, “as with any important technology,” he added, “let alone one as unique as AI, there will be a learning curve replete with twists and turns.”

One of those twists is the fact that AI remains a controversial technology. Some see it as an existential threat to humanity; others see it unleashing a new wave of productivity and efficiency and enabling people to have better and more rewarding business lives.

Brousell also believes that AI’s unique ability to learn, and what that ability implies for predicting machine and operational patterns and behavior, qualifies it to be “in a special place among all of the technologies associated with digital transformation.”

“I can’t think of another technology that we have employed in our factories and plants,” he added, “that requires us to ask the question: do we need a code of ethics for AI use?” According to recent MLC research, he noted, 75% of manufacturing executives already believe a code of ethics will be needed in the years ahead.

Nevertheless, predicted Brousell “AI is here to stay”, and that its influence will only grow in operations, in the workforce, in the interactions across supply chains, and with customers and partners in the years ahead.

“AI”, he concluded, “is truly a force to be reckoned with” for the future of manufacturing, and manufacturers now need to act with urgency to accelerate its adoption to drive competitiveness in the years ahead.

Manufacturing Leadership Journal content and MLC resources are exclusively available to MLC members. Please sign up for an account or log in to view this content.