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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.

With the recent release of the Manufacturing in 2030 Project survey A Lens on the Future, MLC assembled an expert panel of speakers to discuss the results and bring context to the survey findings.

Moderated by David R. Brousell, the MLC’s Co-Founder, Vice President and Executive Director, the panel included Dennis McRae of West Monroe, Greg Wagner of EY, Chirag Rathi of Infor, and Joe Zakutney of NTT DATA.

Here are ten key takeaways from the discussion:

1. 84% of survey respondents expect an increased pace of digital adoption in the next decade

Dennis McRae, West Monroe’s Senior Partner and Practice Leader, Consumer & Industrial Products, noted that the acceleration rate depends on the size of the company, but he said the biggest thing is if you haven’t started your Manufacturing 4.0 journey in a meaningful way, now is the time to do it to maintain competitiveness.

“One of the first things you can do is really establish a team focused on digital with the right leaders, the right innovators, and also the right disruptors who can really challenge and do what leadership needs to get done,” McRae said.

2. 58% of survey respondents have autonomous factory operations on their radar by 2030

Chirag Rathi, Senior Director, Industry and Solution Strategy at Infor, pointed out that the desire for autonomous operations is not new and that General Motors was talking about this in the 1980s. Citing deep-learning and self-learning algorithms in machine learning, digital twins, blockchain, and autonomous transportation, he sees autonomous operation as a game changer, but he cautioned that full autonomy is unlikely in many circumstances.

“The cost of doing full autonomy in most industrial manufacturing processes might be too high,” he said. “So you will have part autonomy in several manufacturing arenas where the business case makes sense, but it will be a decision made on a case-by-case basis.”

3. 76% believe manufacturing should adopt an AI code of ethics

For Joseph Zakutney, NTT DATA’s Vice President, Manufacturing Industry Consulting and Digital Transformation, thinking about AI’s future means protecting against biases and cyberattacks, while accounting for safety.

“Procedures will need to be put in place to make sure that we’re complying to [a code],” he said. “We need to make sure that the software that we are releasing is fair, reliable, explainable, takes data protection and government regulations into consideration, and is focused on the well-being of society.”

4. Almost half of respondents indicated they expect workforce shortages to continue through 2030

Traditionally, manufacturing doesn’t have the best image according to Greg Wagner, EY’s Data Driven Manufacturing Leader. It is considered dirty, loud, and can be physically intense at times, but Wagner pointed out that those seeking purpose-based work should be attracted to manufacturing. The old adage of “being a cathedral maker and not a bricklayer” fits here, according to Wagner.

“If we change the paradigm and what we’re looking for, the types of job experiences we can give people, and use automation to get rid of some of those menial tasks that people don’t enjoy and free up their capacity to focus on bigger problem solving, it will mean more impactful types of roles,” Wagner said. “That’s going to really start to attract people and start to soften some of that gap we see right now in hiring.”

5. 81% of manufacturers are looking for greater speed and flexibility

When we think about speed and flexibility, what people really want is responsiveness, according to Wagner.

“If we really want to be able to respond quicker, we need to know what’s going on and we need to invest in better end-to-end visibility of what’s happening within our factories and what’s happening across our network so that we can be more adaptive and have the right insights to drive that change,” he said.

McRae added, “There’s a big opportunity for manufacturers in terms of connecting with their customers, building that client experience, and really monetizing a lot of the data that’s already in the business.”

6. By 2030, 50% of respondents believe digital adoption will be a game changer.

For Rathi, we’ll be closer to Industry 5.0 by 2030 with hyper-customization, responsive and distributed supply chains, and business model innovations. In fact, Rathi said we already have the building blocks to make this a reality.

“We have certainly got a lot of the raw materials to make that transformation happen,” he said. “So we will have a lot of transformative changes by that time period.”

7. Digital acumen is important across functions and at various leadership levels

One challenge McRae sees is getting everyone on the same page using the same language so that data assets are understood across company levels by all who manage data and products in the business.

“It’s not just around different levels, but also across functions,” added Wagner, noting that there is a wide array of digital understanding and how those technologies can be applied.

8. Hiring for a digital background versus a subject matter expert depends on the project

“I think we’re seeing the rise of data scientists and citizen data scientists at some organizations. At the same time a lot of data DIY products are becoming available, and they will become more prevalent by 2030, meaning that people with subject matter expertise will be able to basically design and develop their own data science projects,” Rathi said. Because of that, he believes subject matter experts will be in higher demand in most cases vs. data scientists.

9. For companies slowing down their digital projects due to the economy, focusing on specific things can help prevent losing ground

“Digital adoption is really a people play right now,” said Zakutney. “I’d stay focused on people and process, because ultimately, that’s what you’re going to end up automating [when funding comes back].”

“You can’t quit your digital investments,” added McRae. “If you don’t become digital, you’re going to be left behind. At the same time, prioritizing those digital investments specifically around areas that are going to improve your customer experience and take costs out over the next few years are going to help you win.”

10. Beyond the panel discussion, the survey report provides insightful data about the future of manufacturing

The MLC’s Manufacturing in 2030: A Lens on the Future research survey includes front-line insights from over 260 senior manufacturing industry executives, spanning multiple functional roles, and representing large-, medium-, and small-sized manufacturing companies from multiple industry sectors. Armed with this rich combination of real-world predictions and forward-thinking understandings, the MLC hopes that manufacturers can better plan their longer-term future and find ways to enhance their value, competitiveness, and contribution to society. Download the complete survey data and report.

The manufacturing industry has spent a lot of time, effort and money on making its processes more efficient over time. And now the industry is investing in the Industry 4.0 philosophy to minimize wastage and downtime, leveraging technologies including 3D printing, digital twins, and predictive maintenance. Powering all of these investments is data.

Late last year I had a number of conversations with manufacturing professionals who manage products throughout their lifecycles – from the 3D CAD design phase, through review, fabrication, sales and marketing, and even further into customer usage and after-sales. They each told similar stories of breakdowns in the processes for creating, distributing, and consuming content that transfers vital knowledge about their products. In addition, they all identified significant negative impacts stemming from these problems. Errors, delays, and missed sales opportunities were frequent complaints.

I came away wanting to know more about these problems, their outcomes, and the underlying causes. What is driving ineffective product documentation workflows and processes at organizations that otherwise appear to be investing heavily in efficiency-based initiatives and cutting-edge tech?

In a bid to find out, my company, Canvas GFX, surveyed over 500 manufacturing professionals across a broad range of verticals, including automotive and electric vehicles, aerospace and defense, new space tech, industrial machinery, and more. The results showed these challenges exist widely across the manufacturing sector, suggesting an endemic and interconnected problem.

We’ve dubbed this problem Product Communication Disorder. For many companies, Product Communication Disorder is perceived, managed – and often tolerated – as a series of departmental workflow challenges. The data suggests the problem cannot be solved unless assessed and addressed with a company-wide perspective.

Where have manufacturers gone wrong?

There are three distinct stages within documentation and knowledge transfer where problems arise, the first being the creation of product content.

As it stands, creating product communication content is time-consuming and complicated, requiring input from multiple team members across an organization. Our research highlighted how critically deficient current workflows are, with clear room for improvement. The stats lay the issue bare, with over 95% of manufacturing industry professionals reporting that projects or products at their company had suffered errors or delays as a result of inefficient workflows for the creation of product communication.

But the problem runs deeper than content simply being late or too time-consuming to create. While the data says these are both true, our survey also suggested that the processes underpinning the creation of content are themselves flawed. For more than one in three respondents (36%) workflow bottlenecks stemmed from too many people being involved in content creation. Meanwhile, the lack of skills or software needed to be able to properly visualize 3D models, the basis for many documentation illustrations, was cited by one third of respondents.

Collaboration is another area fraught with challenges. In fact, 73% of respondents in our survey said they had experienced product or project errors or delays in the past two years as a result of difficulty collaborating on content.

Just as content creation at manufacturing companies is fragmented in terms of departments, skills and software, the collaborative process also appears to want for some kind of central management. According to almost three quarters of survey respondents, a primary problem appears to be too many channels (including email, Microsoft Teams, Slack, and other voice and video calling solutions) being used to manage collaboration, review and feedback on product content. The result of this vital communication happening across a range of channels according to 3 in 4 respondents is that it is easy to miss feedback on important documentation and content.

Lastly, the survey revealed serious concerns around the ability of workers to access the most up-to-date documentation materials. For many organizations this appears to be a struggle, while the problem is aggravated by managing a range of different content formats. It’s vital to remember that consuming content is what this entire process is about.

Worryingly, 85% of respondents said that outdated documentation in circulation had resulted in errors and delays over the last four years, and over a third (36%) said their company struggled to manage the rate at which content becomes outdated. More alarming still is the large proportion of respondents who conceded that their company has difficulty ensuring everyone who needs access to content is able to access the most up-to-date version of each document (54%).

Solidifying Industry 4.0 gains 

The overarching issue is that manufacturers spend heavily to update their processes to reduce defects and ensure products make it to market on time, documentation issues are continually undercutting those investments.

Perhaps the starkest illustration of the problem lies in the fact that 73% of respondents felt that inefficiencies in their product communication processes were undermining gains made through other technology initiatives.

But it’s not all doom and gloom, and there is a silver lining here. The findings pointed to evidence that manufacturing companies are looking to cure the problem, rather than simply manage the pain. While the data is clear, so are the actions companies can take.

By addressing their problems in product documentation, companies can take a huge leap in realizing the full potential that Industry 4.0 offers and maximize their investments in it.

About the author:

Patricia Hume is Chief Executive Officer of Canvas GFX.

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