The NAM recently released its Top 8 Manufacturing Trends for 2023—a guide to the opportunities ahead and the resources that the NAM can offer. Here is what to look out for this year and beyond.
Advanced and emerging technology: Manufacturers are investing in a multitude of new technologies, including artificial intelligence, virtual reality, machine learning and more. Automation and robotics are enhancing workers’ abilities but will also require many more high-skilled employees. Though the workforce shortage is a challenge, digital technologies will help manufacturers become more resilient, efficient and profitable.
- NAM resources: How do you maximize these opportunities? The NAM has resources for you, including the Manufacturing Leadership Council (the NAM’s digital transformation arm), the Innovation Research Interchange (the NAM’s innovation division) and the MLC’s Manufacturing in 2030 Project.
Supply chain resilience: As manufacturers face long lead times, increased costs and a scarcity of raw materials, they are taking steps to boost supply chain resilience through reshoring, cybersecurity, increased supplier pools and more.
- NAM resources: Manufacturers can benefit from resources like CONNEX Marketplace, which helps connect nearby manufacturers and suppliers; the NAM’s Supply Chain Hub—a continually updated collection of webinars and policy documents focusing on supply chain issues; and useful case studies highlighting best practices.
Talent disruptions and opportunities: Manufacturers are confronting a range of challenges around the workforce, including labor shortages and skills gaps, while also figuring out how to take advantage of previously untapped talent pools.
- NAM resources: If you are searching for ways to enhance your employee benefits, The NAM Manufacturers Retirement 401(k) and Savings Plan offers manufacturing employees secure benefits for the future, while Innovation Management Workshops give manufacturing leaders the skills to build innovative and creative teams. Meanwhile, the Manufacturing Institute—the 501(c)3 nonprofit workforce development and education partner of the NAM—promotes a range of events and initiatives designed to expand and diversify the manufacturing workforce as a whole.
Cybersecurity: The threat from bad actors is real, and strong cybersecurity has become critical to manufacturing operations up and down the supply chain. At the same time, manufacturers will have to be on the lookout for new cybersecurity reporting requirements.
- NAM resources: The NAM can help, with support like the NAM’s complimentary Cyber Risk Assessment. NAM Cyber Cover offers cyber insurance and risk mitigation, and you can check out these videos from manufacturing executives laying out best practices for cybersecurity defenses.
Post-pandemic growth and expansion: Long-term goals shouldn’t be downgraded, despite an uncertain economy. Manufacturers should keep pursuing technological advances, navigate government incentives and stay open to mergers, acquisitions and other investments.
- NAM resources: The NAM Incentives Locator helps manufacturers find funds and tax credits to help their business, while the MLC offers networking opportunities for manufacturing leaders.
Tough economic outlook: There’s no doubt that manufacturers face economic headwinds. That means manufacturers need to look for ways to be nimble and responsive to changing realities and able to work more efficiently than ever.
- NAM resources: Tools like NAM Shipping & Logistics give manufacturers discounts on shipping and freight, while NAM Energy offers conversations with energy advisers who can help adjust energy use strategies. IRI Coffee Houses promote virtual conversations with innovation leaders to discuss new developments and opportunities.
Sustainability: Manufacturers are committed to strengthening operations and maintaining a healthy planet at the same time. More than ever, manufacturing companies are looking for ways to reduce carbon emissions.
- NAM resources: The NAM provides resources that can help manufacturers with innovating for sustainability, as well as rethinking end-of-life technology value. Manufacturers can also learn about how digital solutions drive sustainability in manufacturing.
Looking ahead to 2030: Changes in the manufacturing industry and in the world around us—from population growth to the rise of a new middle class to increased interconnectivity—have manufacturers planning for big changes in the next decade.
- NAM resources: The IRI offers a forum for manufacturers to connect with R&D leaders, while the MLC’s Next Phase of Digital Evolution report shows how manufacturing leaders can plan their long-term futures.
Learn more: Take a look at the full guide for more details and to find out more about the NAM resources that will help manufacturers deal with these key trends.
AI is changing the way manufacturers do business—from the production line to the back office and across the supply chain. At the Manufacturing Leadership Council’s Manufacturing in 2030 Project: Let’s Talk about AI event last month in Nashville, Tennessee, panelists discussed how those sweeping changes would alter, and enhance, the manufacturing workforce.
A collaboration between the MLC (the NAM’s digital transformation arm) and the MI (the NAM’s 501(c)3 workforce development and education partner), the event provided key insights for manufacturers into how technology and workforce trends interact with each other. Here are a few key takeaways.
Net positive: “The history of technology adoption is about improving the job quality of individuals on the shop floor. AI helps them to do the job better, provide them with better tools, gives them greater authority and ultimately increases the value-add of their jobs. All of that is a net positive for those individuals,” said MI Vice President of Workforce Solutions Gardner Carrick.
- By leveraging data and enabling greater efficiency, AI will improve communication, increase collaboration across disciplines and stimulate innovation, according to the panel.
- In addition, “AI can even inform the workforce’s creativity by working with it to design a new product or system,” said Jacey Heuer, lead, data science and advanced analytics, Pella Corporation.
Skills needed: While you might expect that implementing AI requires workers skilled in programming, data science and machine learning, manufacturers will also need to expand their bench of critical thinkers and problem-solvers. The panelists had a few tips to help companies along.
- Invest in upskilling programs to make the AI integration process at your company smoother and develop the talent you already have.
- Update job descriptions to reflect the skill sets the company will need in the next five to seven years.
- Consider recruiting for and teaching adaptive skills—skills that enable individuals to adapt easily to changing demands and environments—which can increase the flexibility of your workforce.
- Build partnerships with local schools, community colleges and technical and vocational schools to develop talent pipelines that will meet your needs.
The human-AI collaboration: While AI will take over monotonous, repetitive tasks, the panelists predicted that the industry will continue to center around human labor.
- “You can teach AI to do X. You can teach AI to do Y. [However,] combining the two may be really difficult for AI, while a human can do it better. You’re going to continue to see humans in roles that center on making decisions and telling stories,” said Asi Klein, managing director, industrial products and organization transformation, Deloitte Consulting.
- Meanwhile, AI adoption will likely lead to an increase in available jobs, as more skilled workers will be needed to guide and inform these new processes.
The last word: “Over the last 12 years, we’ve seen a lot of technology adoption, but we have not seen a lot of job loss. In fact, we’ve seen job gains,” said Carrick. “There is a lot of opportunity to reimagine jobs to add value that AI will help to illuminate.”
Digital Transformation (DX) is a broad business strategy to solve traditional business challenges and create new disruptive opportunities using digital technology – such as maximize revenue, reduce cost, improve quality, and increase flexibility. Use cases range from asset optimization to workforce productivity to industrialization.
Why Manufacturers Need Digital Transformation
To remain competitive, DX for manufacturers is a necessity. Global market intelligence firm IDC predicts that in 2025 global DX spend among manufacturing industry companies will total more than $816 billion. Forrester Consulting found that more than 90% of manufacturing leaders believe that DX is important for their success. Clearly there is a lot at stake and developing a DX strategy is critical to capturing the most value.
The range of opportunities for DX in manufacturing is both a positive and negative. On the one hand, for whatever challenges facing an organization, there is likely a solution out there to address it. But manufacturers are faced with dozens of challenges. Such initiatives are usually driven by a scattergun, technology-driven approach. Ultimately, this results in resources being misdirected and just a small set of initiatives driving true transformation. Instead, companies must employ a laser-focused approach, that emphasizes impact, speed, and scale.
Manufacturers that have successfully adopted DX strategies are more efficient than their competition. That efficiency may be generated by greater worker productivity, asset uptime, better cross-organizational collaboration, or other DX opportunities. Ultimately, regardless of how efficiency is gained, it can be leveraged to increase revenue and/or reduce costs.
Achieving Transformation with Impact, Speed, and Scale
Regardless of the many different challenges an organization faces and the many different solutions on the market, there are fundamentally four objectives for manufacturers that have not changed: maximize revenue, reduce cost, improve quality, and increase flexibility. Impact, speed, and scale are the three key success factors for delivering transformational outcomes, and each must be tied to at least one of the objectives. Here’s how:
Impact – Focus resources on the most important constraints to drive P&L. Based on the dynamics of an industry and strategic roadmap, manufacturers should determine which of the fundamental goals are most important to improve upon and which are most likely to impact these goals in order of their criticality to the business.
Speed – With impactful opportunities identified, attention should turn to speed and scale. Quick wins can make or break a good initiative by building early, positive momentum. A quick win will generate team buy-in and can be leveraged for greater executive support. This rapid time to initial value is best achieved with proven off-the-shelf solutions.
Scale – Scalability must be considered early. No initiative should take place without a comprehensive and actionable scaling plan. If a project is slow to scale it is more likely to lose support and fold. If it cannot scale, then it is not delivering transformational value. The most reliable way to build a scalable plan is to model it after approaches that have already proven to be successful. The key here is finding repeatable use cases, that check off the high impact requirement and can be deployed with off-the-shelf solutions.
A recent PTC survey found that there is a stark difference between the companies that succeed in DX and those that do not. Companies that meet ROI goals expectations beat them by an average of 50%; those that fail miss expectations by an average of 30%.
This insight underscores the requirement for strategic DX for manufacturing organizations, and the PTC Impact, Speed, and Value Framework described here creates a foundation for DX success.
Will Hastings is Director of Product Marketing, PLM for PTC.
The Manufacturing Leadership Council recently partnered with EY for a two-day event focused on preparing for the future of manufacturing. Hosted at MxD in Chicago, Ill., the event focused on data-driven manufacturing and included a tour of EY’s Digital Operations Hub, several discussion panels and presentations, and a collaborative workshop.
Diving deep into manufacturing at EY’s Digital Operations Hub: Day one featured a round-robin visit to a selection of experience modules within the EY Digital Operations Hub. Participants had the option to visit five of the hub’s 31 modules where they heard about topics including workforce upskilling, intelligent demand forecasting and planning, digital performance management, digital worker enablement, edge computing, and more.
As participants made their way around the Digital Operations Hub, led by EY’s Mark Heidenreich, who leads the Digital Operations Hub, EY’s expert team and partners shared a deep dive into each topic, demonstrating the latest technologies and thinking on this important array of manufacturing topics.
Focusing on the future: The second day of programming kicked off with a conversation between David Brousell, MLC’s Co-Founder and Executive Director, and Scott Dixon, EY’s Managing Director – Advanced Manufacturing Technology Leader. The topic at hand was MLC’s latest white paper, The Next Phase of Digital Evolution and what it tells us about the future of manufacturing.
The two focused on data and its important role in manufacturing. While data may be difficult to get to – particularly on-demand – it is an important driver of decisions and value. However, they cautioned that data collection doesn’t equal success. Instead, Brousell and Dixon urged organizations to balance resilience while adding complexity. Brousell recommended that organizations not focus on data’s ability to “knock down silos.” That phrase, he warned, can be scary for subject matter experts. Instead, he recommended weaving silos together so that systems are integrated and domain expertise can be maintained.
Becoming data-driven: Next up, the event covered the top challenges for data-driven manufacturing with a presentation by EY’s Sachin Lulla and Amy Burke, the Americas Consulting Sector Leader – Advanced Manufacturing & Mobility and Advanced Manufacturing & Mobility Markets Leader, respectively. With a survey of 400 manufacturing companies as its basis, the presenters shared how only 10% were experimenting with digital, while only six percent were tackling digital at scale.
Throughout the conversation Lulla and Burke emphasized the need to put humans at the center of any transformation, building digitization and operational excellence around that core. For Lulla, the purpose of technology is to augment human intelligence. The pair agreed that starting with an end goal in mind is important when formulating a data strategy. The organization and employees need to know “the why” behind the data collection and use.
Further, Burke and Lulla recommended that organizations should not just look at gaps in their current workforce, but at what employee skills exist on the team and how upskilling and a learning environment can cultivate a fertile ground for data to be used successfully.
Driving digital with data: Pfizer’s Vice President of Digital Manufacturing, Mike Tomasco, was on hand to share how the pharmaceutical and biotechnology company uses data-driven decision making to create value. Tomasco shared how the company’s initial failures with capturing and using data led to significant successes and allowed Pfizer to move beyond pilot purgatory to large-scale transformation.
Moving beyond: The idea of moving beyond pilot purgatory was explored further to start the final panel discussion moderated by Brousell. Panelist Jim Fledderjohn, Dell’s Manufacturing Vertical Field Director, advised organizations to align pilots to the bigger strategic vision and fail fast. According to fellow panelist Terry Davenport, Rheem’s Executive Vice President, Global Operations, leaders should use the scientific method to learn from pilot projects and prove the value before scaling. From a collaboration standpoint, Microsoft’s Americas Regional Business Lead – Manufacturing, David Breaugh suggests that cross-functional teams help keep an eye on the big picture and unlock insights faster. Meanwhile, James Zhan, PTC’s Vice President, Market Development, IoT Solutions cautioned the audience not to focus solely on pilot purgatory and to be sure to keep an eye on workforce skills purgatory.
The panel also tackled the topic of data measurement, with Fledderjohn urging organizations to be selective about what data they collect – a proactive strategy that will help ensure the data is used and useful. Any process should have a metric that makes things faster, safer, eases worker burden, and offers higher quality and cheaper outputs, added Davenport. To that end, panelist Steve Pavlosky, GE Digital’s Vice President of Product Management, shared that GE shifted its technology roadmap to help customers move data into a single system so operators could make decisions quicker.
Capping it off with idea sharing: The event was capped off by a series of collaborative breakout sessions during which participants brainstormed go-forward ideas and feedback around the topics covered throughout the course of the entire event. Beyond the content that participants absorbed throughout the event, the breakouts gave them a chance to add their own two cents to the discussion, share their own experiences, and take away new perspectives that can be applied to their organizations.
Visit https://www.mxdusa.org/partners/ey/ to learn more.
All photos courtesy of EY.
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.
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.
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.
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 25th iteration, AI learns how to regulate the variation. By the 30th 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.