Everyone is grappling with new technologies: futurologists, consultancy bureaus, asteroid miners, Oreo tasters… What will 2025 look like for them? How will it look for us? Read all about it in our regular round-up of manufacturing-related news. 

Fun fact: the name Augury comes from the Greco-Roman practice of observing bird behavior to receive omens that could offer insights into the future. According to Plato, this method was later superseded by haruspices, inspecting a sacrificed animal’s liver, since this was considered much more prestigious. 

So, in terms of hygiene alone, it’s easy to understand why crystal balls ended up cornering the soothsaying market.

The Long History of Futurology

“In A Century of Tomorrows, Glenn Adamson offers a hurtling history of the art, science, and big business of looking ahead,” according to ‘From Tarot Cards to Streamlined Design, We Can’t Stop Predicting the Future’.

“The act of probing into the future need not be predictive to be useful,” writes historian Adamson. “Instead, considering what the future might look like can focus attention on the good and bad of the present. Adamson opens with a fascinating, albeit brief, account of weather forecasting, which became more reliable with the advent of the telegraph: as he notes, ‘a lot of tomorrow’s weather is already here today; it’s just somewhere else, usually a little farther west.’”

In more recent weather news: ‘DeepMind AI Weather Forecaster Beats World-Class System’.

The Future Is Futuristic 

According to ‘Dreams Of Asteroid Mining, Orbital Manufacturing And Much More’, an army of “space cadets who see the world beyond Earth as something not just to be explored but conquered” is arising.

These cosmo-peneurs are confident they will soon be able to piggyback on asteroids to mine platinum and other precious metals, make optical fiber in Zero-G far superior to the conventional sort, or improve drug efficacy by crystallizing their ingredients in orbit. 

But it won’t be easy. “The obstacles would be formidable, even to the less ambitious goal of setting up a nursing home for retired billionaires. But formidable is not insurmountable.”

Go, space cadets, go!

Future Past

“A technology pioneered by Benjamin Franklin is being revived to build more efficient electric motors,” according to ‘Electric Motors Are About to Get a Major Upgrade Thanks to Benjamin Franklin’.

It’s said Franklin used his invention, an electrostatic motor, on a picnic to power a turkey rotisserie. However, enabling technologies only matured enough recently to make the motor efficient enough to go whole-hog. .

“It’s reminiscent of the early 1990s, when Sony began to produce and sell the first rechargeable lithium-ion batteries, a breakthrough that’s now ubiquitous. […] These motors could lead to more efficient air-conditioning systems, factories, logistics hubs, and data centers, and – since they can double as generators – better ways of generating renewable energy. They might even show up in tiny surveillance drones.”

Major players such as FedEx and Rockwell Automation are already testing the motors. 

Are Even the Fact-Based Soothsayers Threatened?

“The golden age for CEO whisperers may be coming to an end,” according to ‘Have McKinsey And Its Consulting Rivals Got Too Big?’.

“Not long ago the consulting industry looked indestructible. Fees rocketed during the Covid-19 pandemic as clients sped up efforts to digitize their businesses, diversify their supply chains, and respond to growing calls to bolster their environmental, social and governance (ESG) credentials.” 

But now there’s a slump in demand and widespread layoffs due to a potent mix of shrinking markets brought on by deglobalization, a waning interest in ESG, and seemingly endless technological disruption. 

But the consultants are not standing still, and are actively developing digital tools to improve their workflows. Many are also partnering up with the companies developing the AIs. “Such partnerships look like a welcome source of growth for the consultants. In time, though, they could become a drag – especially if they are successful. The quicker corporate clients become comfortable with chatbots, the faster they may simply go directly to their makers in Silicon Valley.”

However, these short-term gains from AI could lead the consultancy bureaus to irrelevance – “something for all the strategy brains to stew on.”

The Future Is Tasty!

It’s a problem for food developers: the tastings. According to ‘Oreo Owner Mondelez Taps AI to Tweak Its Classic Snacks’, this is especially true if you happen to be a health fanatic developing sugar products.

“I used to work in Sour Patch Kids, and if you did a tasting every day for a week, it was a nightmare,” says one food developer. 

But now AI is transforming the process. “Food scientists there use the AI tool to create optimal recipes by specifying desired characteristics, including flavor (‘buttery,’ ‘in-mouth saltiness,’ or ‘vanilla intensity,’ for instance), aroma (‘oily,’ ‘egg flavor,’ ‘burnt,’ among others) and appearance (‘amount of chips,’ ’roundness,’ ‘chip edges’ are considerations). The tool also considers parameters like the cost of ingredients, their environmental impact and their nutritional profile.” 

“Earlier iterations of the tool that weren’t given as much data made some unhinged suggestions. ‘Because [baking soda is] a very low-cost ingredient, it would try to just make cookies that were very high in baking soda, which doesn’t taste good at all,’ said one manager.”

So yes, you will still need human Subject Matter Experts in the loop to serve as tasters and brand stewards. “The brand steward is key… They’d be telling the tool: This is what the essence of an Oreo is.”

Nice work when you can get it.  

The Future is GenAI. If We Take A Deep Breath…

In other new use case news, “OpenAI and Google have unveiled their next generation of products,” according to ‘What Do The Gods Of Generative AI Have In Store For 2025?’.

In short, playtime is over, and now it’s time “to release clever products that prove there is a market for all this ingenuity.” However, the rush to produce has meant some of these products have been “marred by glitches”.

It seems GenAI  is evolving so quickly that the technology is defining the product. “You are normally taught not to be a hammer looking for a nail,” says Kevin Weil, OpenAI’s chief product officer. But “every two months computers can do something that we have never before been able to do.”

What is the moral of the story? Take a deep breath, people. Take a deep breath and lead with the nail: that problem that really needs solving. 

The New Crystal Ball On The Block

In summary, the future is hazy. No one and nothing – including crystal balls – are sure how it will play out. 

One thing is certain: the new telegraph in town is called AI. And 2025 might be the year it offers yet sunnier forecasts. 

Read last month’s Manufacturing – The News: ‘Will AI Become the Time Person of The Year?’.

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In a recent edition of the Manufacturing Meet Up podcast, hosts and industry veterans Alvaro Cuba and Ed Ballina look back at 2024 and dust off their crystal balls to see what they see coming up in 2025. Let’s summarize!

 

It was a big year in manufacturing, and Ed and Alvaro discuss the stories and trends that shaped 2024 – and how they see 2025 developing. And here’s a spoiler: challenges remain, but the future looks bright as long as humans and machines work together and keep team-building. Watch the full episode! 

What Did 2024 Mean For Manufacturing?

1) Cost And Productivity Pressures

It’s all getting rather expensive for many reasons. Yes, we’re still dealing with the wake of COVID: incurred costs and wobbly supply chains. And yes, the labor market is still very tight. And for sure, consumers are getting tired of paying the price.

Manufacturers are looking for value and cutting costs, and this won’t be changing anytime soon. In fact, manufacturing has always been about making the best possible products for the least amount of money. So, it’s something we have to live and deal with. That’s where tech comes in…

2) Booming Global Market For AI

You couldn’t miss it: AI hit not only factories but also your family and communities. It’s everywhere and only set to grow. The global AI market for manufacturing is estimated to go from US$4 billion in 2023, to US$156 billion in 2033, growing at a CAGR of 45%.

Most companies believe AI will be a pivotal technology to drive growth and innovation in the sector. People are starting to see the value of the coins coming in. AI adoption in manufacturing is set to go from 26% in 2022, to 86% as of now, and to 93% in two years – which basically means everyone.

In short, it’s a revolution!  

3) Connected People

People still matter – big time. Yes, there’s a “Silver Tsunami” of retirements. But there’s also a “New Collar” class rising. Trades are at an all-time high in demand and get paid attractively well. Not to generalize, but these folk are not only out to punch the clock but want to find meaning in their work – and AI can help with that. Instead of working in breakdown mode, you can use Predictive Maintenance technology to get you to the equipment and address any issues before anything terrible happens. With no greasy messes to clean up, you can focus more on solving root causes. With a connected workforce, it’s no longer just about brawn but also brain. 

With purpose, everyone wins.  

What Will Matter In 2025 

1) Industry 5.0: Looping In The People

So all this Industry 4.0 tech is great for the shop floor – and job satisfaction. But we must do more to complement it with the front-line people using it and their skills. It’s estimated that around 44% of roles have evolved thanks to human-AI collaboration (and this will only continue). And, the idea behind Industry 5.0 is to empower people with the relevant skills to do their jobs better and to also make them more versatile and resilient.

Yes, you need to connect the workers to the tech. Still, you also have to connect them with each other – down the line, in the different factories in your portfolio, with the customer service people, supply people, quality people, etcetera. 

In other words, Maintenance and Operations will become better friends in 2025.

2) Next-Level Connectivity And Data

Once you connect the people, you need to connect the systems. Yes, we’re talking about bringing Machine Health together with Process Health so everyone can collaborate to achieve full Production Health. We’re talking about next-level connectivity for complete transparency and supply chain optimization. Once all these elements are joined, the results will be incredible.

3) Sustainability. The Real Thing

This is the year that sustainability starts to become less symbolic and more systemic. Before, we had C-Suite sustainability, which made a nice picture in the annual reports. And that’s important: we need goals to work towards in terms of benefiting the planet. But the real sustainability is in the lines. With tech-empowered operators and supervisors, your lines will run better – and that means less waste and energy use. And that brings serious dollars. 

By doing a better job in a more relaxed way, those working the line also have more time to think and introduce even more innovations. In other words, sustainability can start paying for itself. Ka-ching. But again, this is what manufacturing folk have been doing their whole careers. It’s always been a balancing act between productivity, quality, customer service, and all the rest. What Alvaro and Ed are saying is that it will all just get easier in 2025.

Happy New Year! Watch the full Manufacturing Meet-up episode: ‘2024 Trends, 2025 Predictions’.

The post Manufacturing Meet Up: 2024 Trends, 2025 Predictions appeared first on Augury.

In a recent edition of the Manufacturing Meet Up podcast, hosts and industry veterans Alvaro Cuba and Ed Ballina discussed digital transformation, its impact on maintenance and reliability, and how its transforming manufacturing. They even offer a snappy history lesson. Let’s recap!

Coming To A Shop Floor Near You (If It Hasn’t Arrived Already)

The numbers don’t lie. Industry 4.0 is coming, and it’s coming fast, according to a number of recent surveys. For instance, in 2022, only 26% of manufacturers had started doing something with AI; two years later, that number is 86%. Today, the global market for artificial intelligence is around $4 billion; in 10 years, it’s predicted to be $156 billion. Meanwhile, in the last couple of years, 44%, almost half of the roles and responsibilities of the positions in the manufacturing arena have been changed and upgraded thanks to artificial intelligence. 

In other words, we are very much talking about accelerated change. And if it hasn’t already arrived on your shop floor, it will very soon. 

According to industry legends and early adopters Alvaro Cuba and Ed Ballina, during a recent episode of the Manufacturing Meet Up podcast, it’s best to prepare yourself.  

Another Industry History Lesson à la Alvaro and Ed

What are we talking about when we talk about Industry 4.0? Ed and Alvaro gave an edifying summary of how we got here. And they give credit where credit is due: our furry and feathery friends in the animal world.

It all began many eons ago when monkeys started using sticks to scoop up delicious mouthfuls of ants, and birds began dropping clams from high heights to crack them open for a nice little chowder fest. Indeed: animals were the original tool inventors and jumpstarted what we’ve come to call manufacturing. 

Regarding human progress, 4.0 began with 1.0 in the 18^th century using mechanization and steam. Then in the first part of the 20th century, we embraced electricity and mass production. And then, at the beginning of the 21^st century, with the Third Industrial Revolution, it became all about the internet, automation, and electronics. 

4.0 Is Happening Fast But Not Fast Enough

So, we’ve finally arrived at the fourth big transformation – Industry 4.0 – which includes smart manufacturing, digitalization of the supply chain, synchronization, the full ecosystem, and everything related to AI and the Internet of Things, etc.

At its core, it’s about the connections between people, processes, and technology and making these connections as efficient as possible – not only in specific parts but across the entire end-to-end supply chain.

So yes, it’s an ambitious revolution. However, despite the surging statistics mentioned above, the implementers are still struggling to find savings. But with an onslaught as big as this one, the slow start can be considered natural growing pains while organizations try to figure out what works and what doesn’t. 

Top Advice For Embracing AI In Manufacturing

Happily, Alvaro and Ed have already walked this road many times and offer quality advice: 

1) Start Small: With Detecting Equipment Failures

Most manufacturers start with a particular use case: predicting asset failure. When assets don’t blow up, there is no collateral damage. Plus, there’s no greasy mess to clean up. And as we all know: a safe and clean workplace makes for a happier workplace. Hence, you’ve already won most of the battle.

From here, you can continue a process of continual improvement and expand to quality, process, yet more safety, etcetera.

2) Make Sure You Use Quality Data

You know the old saying: crap in, crap out. So maybe you should snap on some snazzy sensors to collect lots of quality and immediately interoperable data?

3) Think Security

You have to consider government regulations and hackers who may be after your luscious IP. So perhaps that’s another reason to have your own internal system to collect data. 

4) Keep Your Eye On The Three Balls: People, Process, And Technology. And In That Order!

Start with your people: What training do they need to get prepared, open, and excited about what is to come? They shouldn’t be worried about losing their jobs – they are just getting tools to do their jobs better. As for processes, AI can do a lot: analytics, data, data mining, and the ability to help make fast and accurate decisions. Say goodbye to trial and error! Only then can you start thinking about increasing automation, etc. 

5) Think Big: The True Value Comes When You Start Putting Different Systems Together

Machine Health is great, Process Health is great, and safety is great. But the true value arrives when you start combining these and other aspects for even deeper insights. As you strive for full Production Health with maintenance and operations joining forces, the benefits don’t just add up; they multiply because of their synergy with each other. 

6) Benchmark, Benchmark, Benchmark

How do you know you’re winning if you don’t keep score? It can start simple: tracking your mechanical uptime and/or your energy usage. But as your various solutions start to interact and influence each other, you will also need more complex KPIs that may go beyond your regular P&L. Overall carbon footprint? Labor turnover? Supply chain partner satisfaction? Etcetera.

But yes, for now, the low-hanging fruit remains elaborating on your line uptime. How much are you saving in terms of operating costs, waste, and labor? 

7) Don’t Be Afraid. Trailblazers Came Before You

This stuff has been around for a while. There are now many paths that have been carved into the woods for you to follow. Take advice! Learn from others! We’re already basically drowning in too much data. Let’s use it. This is the promise of AI: it can streamline all this data so we don’t have to spend all this time gathering and analyzing it ourselves. Thanks to AI, the data is now given to us in bite-sized actionable chunks. 

Listen, like, share, and subscribe to the full podcast ‘AI and the New Era of Manufacturing’. 

The post You Know You Want To: Embracing Digital Transformation In Manufacturing appeared first on Augury.

With uncertainties around climate and geopolitics, one thing is clear: AI is coming of age as it improves outcomes across industries and even wins two Nobel Prizes. What’s next? Will AI become Time magazine’s Person of the Year? … Read all about it in our regular round-up of manufacturing-related news.

It’s been a big year for AI. Last month, AI was validated by winning the Nobel Prizes for both Physics and Chemistry. Not so shabby for a bunch of zeros and ones.  

A Certain Vigilance Might Be Called For

But yes, as vast as the promise, the rise of AI also comes with its own array of warning labels, as the bestselling historian Yuval Noah Harari ably communicates in his latest book, Nexus: A Brief History of Information Networks from the Stone Age to AI.

“At the heart of Nexus is the idea that networks – whether social, political, economic or technological – are the bedrock of human cooperation and power. Harari argues that the strength of human societies has always come from their ability to create and sustain networks of information. These, in turn, allow large-scale collaboration and the distribution of resources, knowledge and authority,” according to ‘Has AI Hacked The Operating System Of Human Civilisation? Yuval Noah Harari Sounds A Warning’.

However: “The networks that have served humanity so well in the past, enabling unprecedented levels of cooperation and progress, are now at risk of becoming too complex and opaque for humans to fully manage. AI, Harari warns, is not simply a tool that we use; it can make decisions and generate new knowledge independently. Its rise could fundamentally alter the structure of human society. This is why Harari argues for its regulation and control.” Fair enough. 

“Nexus is ambitious, bold and at times, unsettling. It does not offer solutions that are easily within our grasp. But it challenges readers to think critically about what governs our lives and the ways AI could transform them.” Again, fair enough.

To be clear: while Harari recommends vigilance, he also believes: “Obviously, AI also has enormous positive potential.”

“Business technology leaders are winding down two years of fast-paced artificial intelligence experiments inside their companies, and putting their AI dollars toward proven projects focused on return on investment.”

The Holiday is Over: ROI Over Experimentation

Indeed, in the real world, more established forms of AI are ably dealing with very specific problems – whether it’s CuspAI creating materials-on-demand that can be deployed for cheap carbon capture or Every Cure repurposing existing drugs to treat currently untreatable diseases.

In terms of manufacturing, even GenAI has found some use cases that seem viable for the short term, whether using the preferred language of frontline workers or collating documentation and training in a single interface, according to ‘Five GenAI-Enabled Low-Code Industrial Analytics Use Cases Firms Can Get Started With Today’.

And it’s about time: the AI holiday is over. It’s time to get down to business… 

“Business technology leaders are winding down two years of fast-paced artificial intelligence experiments inside their companies, and putting their AI dollars toward proven projects focused on return on investment,” according to ‘Companies Had Fun Experimenting With AI. Now They Have to Show the Returns’.

“When generative AI came along, there was a certain amount of discretionary funding that we could look at to go experiment and test out some of the technology,” says one CTO.

“This is a year where you have to be expecting business results,” says another.

“The problem is, roughly 70% of business customers’ generative AI projects are still stuck in pilot or testing phase.”

“Accuracy and reliability is a big problem.”

“To get over the experimentation hump, businesses need to ensure there is widespread access to corporate data so that technology builders can use it to implement AI […] That’s how you get to the workable prototype that you know is fit for purpose, that you know will move the needle on the business.”

“One way to tell if the needle has moved: AI-based tools must be able to prove their worth in less than 12 months.”

“Another option: breaking down AI initiatives into smaller chunks that are more easily proven out.”

“I’m quite happy that it’s not a magic wand. We understand that it really is a useful, powerful tool, but it fits into the broader ecosystem.” 

“… has helped shrink the process of taking a new model of a regular vehicle from conception to mass production from around five years to about two.”

Stimulating Simulations

In manufacturing and AI, we hear a lot about “digital twins,” which is a fancy way of saying “running simulations.”

“When a factory has secrets to protect it is not unusual for security staff to ask that no photos be taken. This industrial campus in Milton Keynes, northwest of London, however, is particularly cautious. It is the home of Oracle Red Bull Racing, a Formula 1 team involved in a competitive contest that relies on levels of engineering so advanced they would leave most manufacturers in the dust,” according to ‘Digital Twins Are Speeding Up Manufacturing’.

“The digitization of car design and the virtual testing of prototype vehicles in a simulator has helped shrink the process of taking a new model of a regular vehicle from conception to mass production from around five years to about two. […] Carmakers are now trying to create digital twins of their factories and supply chains to plan production more efficiently. As the volume of data grows, AI will help analyze the twins and suggest improvements.”

“Spotting problems before they occur has both safety and financial benefits. It also makes routine servicing more effective. Aircraft used to require their engines be serviced at set intervals, even though some journeys cause more wear and tear than others. Planes flying out of an airport in a desert region, like the Middle East, can ingest gritty dust particles, which abrade components faster. Certain flights are more heavily laden, which adds stress. And some pilots push the throttles harder than others.”

“As the digital twin takes such things into account, maintenance schedules can be tailored to how each engine is actually wearing. This means some engines can stay on the wing as much as 30% longer.” 

“He said the 15 years of experience traditionally required for a human to handle a complex role can be accomplished at the same level by someone with five years of experience working with two AI co-pilots.”

But It’s Not Just About Productivity, It’s About People

“Honeywell CEO Vimal Kapur said at the recent CNBC Evolve: AI Opportunity Summit that he expects AI to be a much bigger growth driver than a productivity fix for the industrial company. That’s because of a generational shortage in skilled labor and the ability of AI copilots to reduce the time it takes for newer employees to become experts at their jobs,” according to ‘Why Honeywell CEO Vimal Kapur Doesn’t Think The AI Payoff Will Come From Productivity’.

“The AI opportunity for Honeywell is creating a new labor pool that can learn and work alongside AI and accumulate and deploy institutional knowledge much faster. He said the 15 years of experience traditionally required for a human to handle a complex role can be accomplished at the same level by someone with five years of experience working with two AI co-pilots.”

“For all the debate about how quickly AI opportunities will materialize, Honeywell’s Kapur is bullish on the adoption curve steepening quickly. ‘Awareness is high, adoption is low, but there will be an inflection point,’ he said. ‘I do believe 2025-2026 will be a big year for adoption of AI in the context of industrials.’”

So, here’s a thought: perhaps Time should name early AI adopters as their Persons of the Year. 


Read last month’s Manufacturing – The News: ‘What Happens After The November Ballot?’.

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Both US presidential candidates want to support manufacturing – but in very different ways. In the confusion, many manufacturers are holding back on long-term planning and investment. Too much risk. But at least there wasn’t a shipping strike. And what’s this CapEx vs OpEx thing all about? … Read all about it in our regular round-up of manufacturing-related news.

This week’s cover story for The Economist should be good news to many: ‘The Envy Of The World: America’s Economy Is Bigger And Better Than Ever’.

However, the subtitle asks a painfully relevant question: ‘Will Politics Bring It Back To Earth?’ 

Difference Strokes for Different Folks

“Manufacturing accounts for about 10% of U.S. gross domestic product and an even smaller share of the nation’s jobs. But the sector bears outsized importance since the production of essential goods holds national security implications and many manufacturing workers live in key swing states,” according to ‘Trump And Harris Both Want A Manufacturing Boom. They Have Very Different Plans For Doing it’.

“Harris aims to close corporate tax loopholes and throw government support behind the production of critical goods. By contrast, Trump wants to protect domestic manufacturers with tariffs on foreign products while cutting corporate taxes and easing regulations.”

While imposing tariffs hasn’t had the most outstanding track record, it is also too soon to tell “whether the support for manufacturing provided by the Biden administration has yielded significant gains in output or jobs.”

Time will tell…

How Big A Difference Does A President Make?

“In truth, no president can single-handedly control the growth of specific industries. Larger economic forces like recessions and exchange rates tend to play a much more powerful role. But some policies can help or hinder their progress,” according to ‘To Revive Manufacturing, How Much Can a President Do?’

In short: “local factors are more important.”

For instance, where are potential employees moving? “As much as politicians might promote the number of jobs a manufacturing project creates, it has become more difficult for companies to fill positions. Sun Belt states have attracted more people in recent years with their lower cost of living, and manufacturers have taken notice.”

“Nevada’s manufacturing job base grew more than 13 percent from the beginning of 2020 to March 2023. Some of that had to do with federal policy: For example, the state received a Commerce Department grant to develop its lithium extraction and refining sector as well as battery production and recycling, which has seeded a new industry cluster.”

“But the expansion has been in the works since the early 2000s, when the state began an effort to diversify its economy beyond hospitality and entertainment.”

Besides being actively open-armed when it comes to welcoming manufacturers, Nevada has

“also benefited from its proximity to California, which has lost about 60,000 manufacturing jobs since the pandemic began.”

And so, California wants to follow Nevada’s lead. But again, there’s a familiar refrain at play: “One factor chilling investment is the election itself. Companies know that the outcome will affect taxes, trade policy, subsidies and regulations, so they are waiting for more clarity before carrying out new plans.”

As one industry expert says, “I think we’re kind of stuck here until the end of the year.” 

Going From CapEx To OpEx

Another sign of uncertain times: “The growing demand for subscription models that move tech acquisition from CapEx to OpEx is driving the growth of the device-as-a-service market,” according to ‘Device as a Service Market Expected to Generate $1.8 Trillion by 2031’.

“Increasing demand for subscription-based models that help customers convert the high cost of acquiring new technology from a capital expenditure (CapEx) to an operating expense (OpEx) drives the global device-as-a-service market. Also, rising adoption of DaaS due to its adaptability, cost savings, and data security has supplemented the growth even more.”

Something solid to think about?

At Least There Wasn’t A Strike

One thing is sure: it’s good news that a large and long-term dockworker strike was averted on the US East and Gulf coasts – especially after ocean supply chains were already hit hard by conflict in the Red Sea, drought around the Panama Canal, and the Baltimore bridge collapse. 

“In a statement, the union said that it had reached ‘a tentative agreement on wages’ and that its 45,000 members would go back to work, with the current contract extended until January 15. The union said it was returning to the bargaining table ‘to negotiate all other outstanding issues.’” 

According to the insightful ‘Beneath the Potential Strike at U.S. Ports: Tensions Over Innovation’, one of the greatest of these issues is automation.

“Confronted by the militancy of longshore unions, port operators have deployed automation, in part to limit their vulnerability to labor troubles. Not coincidentally, dockworkers tend to look suspiciously at robots and other forms of innovation, divining threats to their livelihoods.”

“History validates their assumption that their bosses are embracing automation in part as a way to reduce costs. The most obvious example is the advent of container shipping in the 1950s.”

“Most industry experts view automation as both inevitable and positive. The questions are: Who controls the technology, and will workers be cushioned against changes with training programs that prepare them for new opportunities?” 

Post-Election Boost

As perhaps a reflection of better post-election news to come: “British factories recorded their best month for two years during July, with output and hiring rising and optimism building after Prime Minister Keir Starmer’s landslide election victory,” according to ‘UK Manufacturers Show Fresh Signs Of Life After Election, PMI Shows’.

“Output and new orders increased at the fastest rate since February 2022, while manufacturers added staff for the first time in 22 months.”

So perhaps there’s hope in the unknown.

Tune in next year.

Read ‘Manufacturing – The News: Getting Constructive With Creative Destruction’.

The post Manufacturing – The News: What Happens After The November Ballot? appeared first on Augury.

At TechEx 2024 in Amsterdam, industry leaders from LEGO and Whirlpool shared insights on how they are leading the charge regarding Industry 4.0 – while already enjoying significant payback. Meanwhile, on the exhibition floor, exhibiting companies are increasingly offering the “picks and shovels” to smaller operations that are unsure how to tap into the digital transformation gold rush.

One question was often asked during the European 2024 edition of TechEx 2024 in Amsterdam: “If you follow the saying ‘When you’re in a gold rush, sell picks and shovels’, who is selling those picks and shovels for Industry 4.0.?”

Who, indeed? The short answer is that fully nurturing ecosystems that get everyone digging into and applying their data to boost production and efficiency remain largely works-in-progress. Tech innovation in enterprise largely remains a Wild West, with no single player dominating the market and many parties offering many solutions.

Meanwhile, in the last two years, events like TechEx have been largely hijacked by speculative solutions that sought to leverage the potential (and hype) around generative AI. There’s now a definite feeling that this era is over, as people want to see more short-term returns. In other words, if you spend all that money on picks and shovels, you want to see some ROI gold.

Welcome to the new frontier.

Industry 4.0 Needs To Stake Its Claim

The adoption of Industry 4.0 technologies could be a lot faster, especially for SMEs. While most leaders recognize AI as a critical tech for growth and innovation, they generally lack confidence in the readiness of their data and workforce.

In other words, Industry 4.0 remains a tricky terrain for the smaller players to exploit fully. But at least they can learn from – and hopefully, be inspired by – the more prominent companies leading the charge. 

Let’s Play! Lego Leads The Way!

Look at Lego. It’s a company with many luxuries. It’s family-owned and, as such, built on organic growth. Their product and their company are truly global and truly standardized. It also happens to be regarded by many as the most reputable company in the world. Plus, they make fantastic stuff – they’ve even just released a musical biopic about Pharrell Williams. What’s not to get excited about?

And if you just consider the fact that “it only takes 6 Lego bricks to create 915 million combinations,” the possibilities are indeed endless.

For his presentation ‘Revolutionize Your Operations: Unleash the Power of Digitalization and Innovation!’, Lego’s VP of Operations, Jesper Touboel, enthused how a sense of play infused the company’s efforts in applying data to foster fast and informed decision-making. At the core of these efforts is embracing condition-based maintenance – following an established TPM methodology so the wins can be carefully measured along the way. 

“This may not be a maintenance conference,” notes Jesper. “But a lot of new knowledge is coming out of maintenance. Many of us, as engineers, were taught that you need to maintain everything in a certain way. But that’s complete rubbish because we over-maintain a lot.”

After some successful pilots, Lego is scaling its Global Maintenance Efficiency Program to fully and consistently embrace condition-based maintenance across all its facilities. “It really changes your philosophy around maintenance,” says Jesper. “We’ve already been able to extend the lifetime of our equipment significantly.”

But yes, “It’s always difficult to drive change. You need lots of training to make people part of the journey.”

Digital Twin!

There was standing room only at ‘The Digital Twin: An Essential Step In Industry 4.0,’ presented by Julien Bertolini, an IoT expert for Volvo. Perhaps the audience was lured by its description as a “real-life case study” about establishing a digital twin that could measure the performance of 15 Volvo Group factories around the world.

And indeed, large-scale scaling remains an eternal challenge for many. And Julien’s advice followed closely with those who have come before him: 

–       strong foundational strategy
–       get your data house in order: quality is critical 
–       IT and OT have to bury the hatchet and collaborate
–       clear use definitions 
–       find those scarce skilled professionals 

A Smart Factory In Argentina

If scaling tech is not challenging enough, try doing it in Argentina’s famously struggling economy. Whirlpool, the kitchen and laundry company, did just that. And won. 

In the presentation ‘Whirlpool’s South American Smart Factory,’ the senior manager behind the project, Alessandro Malucelli, described the efforts involved in building a state-of-the-art factory in this remarkably challenging context.

At the time, it was a time of high inflation and import restrictions. “If the country goes to the right, we’re going to have more market – to have an opportunity,” says Alessandro. “Left politicians intended to evaluate South American business, which means there could be an opportunity either way. So, we decided to face a storm to capture benefits later on.”

According to Alessandro, it took 22 months to build a highly agile and automated facility, and the resulting factory has already shown a 20% improvement. This was all thanks to closely following a World Class Manufacturing (WCM) program. Basically, another version of TPM, WCM was originally developed by the Japanese professor Hajime Yamashina as a management and continual improvement approach that aspires to build the best and most cost-effective products or services by involving those working at the facility.  

Onward And Upward

Many larger companies are obviously having success with Industry 4.0 technologies. And the fact is they all started somewhere. So who will help supply and apply the required picks and shovels to manufacturers everywhere?

We’re ready. Let’s get to work.

Time for our pitch: Reach out to learn how Augury can set you on the road to Industry 4.0 payback.

The post TechEx 2024: Searching for the Gold in the IIoT Rush appeared first on Augury.

In a recent edition of the Manufacturing Meet Up podcast, hosts and industry veterans Alvaro Cuba and Ed Ballina gave a short and sweet history of how manufacturing has increasingly gotten its act together over the years – in the name of maximizing service, productivity, quality, safety, and sustainability. Let’s recap!

1)    Birth Of The Production Line (Okay, Henry Ford Deserves Some Credit)

Once upon a time, a few hundred years ago, humans created industrial machines to make their lives easier. But then it took a while before they aligned different machines into production lines. “Ford did great at that with his Model Ts,” notes Alvaro Cuba. “But he did it with a fixed mentality and little innovation.”

“Every car was fine as long as it was black,” adds Ed Ballina. “And Honda actually also did the same in their early years by offering their best-selling Accord in only six colors.”

2)     Output! Output! (Whatever It Takes To Win The War)

In the 1940s, the military took over the US manufacturing arena. It was all top-down, with output as a priority. It was about pumping out as many planes, ships, tanks, etcetera as possible. And this worked out rather well: the war was won.

Unfortunately, the US proved over-confident after World War II. “The US economy was not looking for new manufacturing methods,” says Ed. “They didn’t have time or interest in what a guy like W. Edwards Deming had to say about the science of statistical process control.” 

“It was only in the 1970s when people started to realize that the cars coming out of Detroit – with the “just get-them-out mentality” – were terrible gas guzzlers and unreliable, especially compared to the trustworthy Toyota.”

3)     Let’s Break This Down In The Name Of Quality And Efficiency (Reinventing The Wheel)

Meanwhile, Japan and Germany, with their bombed-out factories, had the luxury of starting with a clean slate and thinking about how they could do things differently. They listened to Mr. Deming and showed him respect. In fact, he brought his science of statistical process control, with its focus on quality and Lean, to Japan where it would later become part of the foundation for the Toyota Production System. 

“It was only in the 1970s when people started to realize that the cars coming out of Detroit – with the “just get-them-out mentality” – were terrible gas guzzlers and unreliable, especially compared to the trustworthy Toyota,” observes Ed.

In other words, more people began recognizing the value of systematically increasing the efficiency of machines’ various processes and the quality of the products.

4)     The Dance Begins (Enter: People) 

“So, as everyone continued to figure out how all these processes worked, the next step was to figure out how to loop people in. How do we engage the shop floor? How do we go beyond the brawn of using our arms and hands to engage our brains and even our hearts to some degree?” asks Ed.

In other words, how can we teach people and machines to dance together to achieve even greater efficiencies through the power of “collaborative” work systems?

“TPM was the next real evolution: taking all these processes and systems and incorporating them into one comprehensive program.”

5)     The System Of Continual Improvement (TPM: Holistic Approach To Perfect Production)

“So now we have quality on one side and people on the other,” Alvaro summarizes. “And we can talk about production and efficiency – and that’s great. But these efforts were still dispersed, and different methods were used.”

Enter: Total Productive Maintenance (TPM). “This was the next real evolution: taking all these processes and systems and incorporating them into one comprehensive program,” says Alvaro. “It doesn’t matter if it’s eight or eleven – use whatever pillars you want. But it should include basics like culture, training, people, safety. quality, maintenance and all the production. And it should be put together so that you can start and follow a process, to get from phase zero to phase four, and see the evolution.”

From here, you can expand beyond the factory walls to engage and incorporate suppliers, procurement, the supply chain, customers, and consumers.

6)     Bringing The Ecosystem Together (Beyond The Factory Walls)

“It’s all been about building blocks,” says Ed. “We started with pretty basic things. We need to get the equipment running well and get our quality where it needs to be. Then, it’s about: How do we integrate people? How do we create these high-performance work systems and great cultures? And then, how do we expand that towards our suppliers and our customers? With better forecasting systems, we can improve our customer delight and order fulfillment.”

And as a result: “It starts looking like end-to-end supply chain optimization.” And by having everyone’s systems talking with each other, there will be fewer surprises for suppliers and customers. And we can move from just-in-time to exactly-on-time.

So here we are. And the future is now. 

“What is your current status in the plant? Do you have a strong 5S foundation and are following a TPM program? Do you already have any preventative maintenance programs already in place? Are you engaging the workforce to join the reliability journey?”

7)     Welcome To The Future (Onward and Upward With Industry 4.0)

“We still have a long way to go, but you start to see the components of the next generation,” says Alvaro. “And that’s Industry 4.0. – with smart manufacturing, digital SCH, and an ecosystem approach – which basically blurs the boundaries between the physical, the digital, and the biological worlds.”

Namely, emerging technologies such as AI, faster communications, Internet of Things (IoT), virtual reality, and robotics can add another layer to improve the performance of machines, people, and processes. “We can put all that together and even predict what will happen next,” says Alvaro. “The opportunities are huge. And there’s much more to come in the future.”

“But first, you need to understand where you are now,” notes Ed. “What is your current status in the plant? Do you have a strong 5S foundation and are following a TPM program? Do you already have any preventative maintenance programs already in place? Are you engaging the workforce to join the reliability journey?”

If not, it’s time to train your people, improve your process, and then automate. Only then can you start claiming your own space in manufacturing’s history – and future.


Listen/watch the full episode of Manufacturing Meet-Up: ‘Zero Waste, TPM, and 5S’.

The post From Ford To Four-Point-O: A Short History Of Manufacturing Work Systems  appeared first on Augury.

Tech revolutions create prosperity – but only after making a mess for a long time. Embracing new technology is one thing, but you must also find new ways to measure your success (and failure) while reorganizing how you work. And in the case of Industry 4.0, you have to do all this with a stripped-back and much less experienced workforce. Yes, it’s challenging but many are already showing the way … Read all about it in our regular round-up of manufacturing-related news.

Old-School Metrics No Longer Measure Up

According to ‘Industry 4.0 Gains Are Ahead of the Tools to Measure Them’, it’s time for a new range of productivity metrics. 

“If Austrian economist Joseph Schumpeter is the father of creative destruction, then today’s entrepreneurs and inventors are his disciples. The term ‘creative destruction,’ coined by Schumpeter in his 1942 book Capitalism, Socialism, and Democracy, refers to the dismantling of traditional business and economic models to make way for revolutionary technologies and innovative processes designed to vastly improve living standards.”

“Economists and statisticians will also need to take a more cross-disciplinary approach to cultivating metrics that measure what cannot be measured today – including artificial intelligence and machine learning.”

But whether it was steam, mechanization, electricity, or computers, these revolutions all involved decades of muddling before the promised prosperity arrived.

Part of overcoming this “productivity paradox” is finding the right tools to track and prove success. GDP and other old-school econometric models like ROI “exclude the impact of AI and machine learning, automation and robotics, IT integration, e-commerce, improved processes and workflows and scaled-up supply chains. Therefore, the shift from traditional to digital manufacturing is not readily apparent.”

So, a Nobel Prize awaits anyone who can provide precise numbers to these obvious yet still intangible benefits. Only then can academia, policymakers, and business leaders come together under a shared set of insights to focus resources that help streamline the path to prosperity.

“Economists and statisticians will also need to take a more cross-disciplinary approach to cultivating metrics that measure what cannot be measured today – including artificial intelligence and machine learning. They, like the general-purpose technologies noted above, serve as force multipliers rippling through the entire economy.” 

Getting Organized… Differently

But yes, not only do you need better statistics, algorithms, and standards that can make realistic sense of the Industry 4.0 revolution, but you also need a wholly new kind of manufacturing organization. And the McKinseys of this world have been pumping out countless reports on how to do precisely that. 

“The experiences of exceptional organizations show that capturing technology’s opportunities means making eight mutually reinforcing shifts that strengthen people, processes, and technology in tandem,” according to ‘Today’s Industrial Revolution Calls For An Organization To Match’. 

The report then dives deep into these eight requirements and three additional critical factors. It also offers five “concrete tasks” to get you on your way:

–        Understand and shape your role in the ecosystem
–        Develop visionary and courageous leaders
–        Define and invest in your tech stack
–        Assess capability needs
–        Work in teams, not in pyramids

But yes, even these concrete tasks remain somewhat high-level. Can we break it down further?

“Gone are the 30-year veterans with average tenure down to only three years in 2023.”

How To Translate 30 Years Into 30 Days

And can we break it down further knowing that the old workforce is never returning? “Today’s manufacturing workforce looks radically different compared to 2019. Gone are the 30-year veterans with average tenure down to only three years in 2023. To make matters worse, 50% of new employees leave manufacturing roles within the first 90 days,” according to ‘How to Get a 30-day Employee to a 30-Year Performance Level’.

Meanwhile: “Traditional approaches to achieving a trained and competent workforce are failing. New generations demand step-change improvements across safety, health, and sustainability performance. Industrial organizations must fundamentally evolve to meet the needs of today and the future.”

In short, manufacturers must embrace AI-driven technologies on the work floor and in their (re)training processes. And here again, it’s time to follow some excellent, albeit high-level, advice: 

–        Accept the New Reality
–        Identify the Capabilities to Invest In  
–        Bridge the Skills Gap
–        Digitally Enable New Employees
–        Provide Next-level Support   
–        Focus on the Future 

“Balanced, stable financial performance and a classical hierarchy of operating metrics are central to the company’s culture. And yet, innovation and leadership on technology, sustainability, and organizational strategy are keys to its continued growth.”

Thrive By Focusing On Practicality And Scale

But what does all this excellent high-level advice look like on the ground? Well, the innovation leaders at Colgate-Palmolive have undoubtedly read these future-thinking reports – since the 218-year-old company is renowned for being ahead of the innovation curve. So, what’s their secret? 

“Balanced, stable financial performance and a classical hierarchy of operating metrics are central to the company’s culture. And yet, innovation and leadership on technology, sustainability, and organizational strategy are keys to its continued growth,” according to ‘Colgate’s Classic Approach To AI For Supply Chain’.

“Another is Colgate’s approach to automation. It starts at a plant level, looking first to site leaders and operators in places like China and Vietnam, whose digital skills are generally far more developed than those in North America and Europe. Coupling this ground-level perspective with system-level thinking about metrics like “robot density” helps ensure practical lessons are balanced with strategic thinking to benefit the whole company.”

So yes, Colgate-Palmolive found new metrics, evolved the organization, and found a way to leverage those still working the floor. “Getting the balance right is a matter of practical thinking about what AI can do to change work processes, and, even more importantly, scaling with good data, solid training, and measurable impact on growth, operating efficiency, and resilience.”

So here’s some inspiration: Colgate has been able to build their own metrics without waiting for a Nobel Prize winner to do it for them. 

Let’s get to work.

Read last month’s Manufacturing – The News: ‘Sun, Sand, And Human Ingenuity’.

The post Manufacturing – The News: Getting Constructive With Creative Destruction appeared first on Augury.

Humans are funny creatures. We can be so dumb, yet we can also create miracles (and usually, we surf the wave between the two). While it sometimes seems, “We’ll go down in history as the first society that wouldn’t save itself because it wasn’t cost-effective” – as the great Kurt Vonnegut quote goes. We are also making profound technological leaps that are driving our world in the right direction… Read all about it in our regular round-up of manufacturing-related news.

Steel Yourself: We Are Still Stuck In The Iron Age

It sounds unbelievable but we are still stuck in the Iron Age due largely to our heavy use of an iron alloy called steel. And, “without iron and steel, we would be thrown back 3,000 years into the Bronze Age,” according to ‘How To Escape From The Iron Age?’.

While steel is often, um, cast as incredibly sustainable since it can be reused without any loss of quality, it is not: “The iron and steel industry consumes more energy and produces more carbon emissions than any other industry.” And unfortunately, “we cannot lower carbon emissions if we keep producing steel with fossil fuels.” 

Meanwhile, we need the steel industry to help us build wind turbines – oh, the irony. 

However, the newer electric arc furnace may prove to be a gamechanger since it “consumes much less energy than the blast furnace, makes use of a recycled resource (no need to mine iron ore), and works without the direct use of coal or other fossil fuels (the electricity can be supplied by solar, wind, or atomic power).”

Unfortunately, it can only be used with scrap steel and we don’t have enough scrap available – since most is embedded in construction.

The author of this article suggests we adjust steel production to available scrap supply – which is, fortunately, rising. “By 2050, scrap availability is expected to rise to about 900 Mt, almost half of today’s global steel production. All that extra steel could be invested in expanding the low-carbon power grid without raising emissions first.” But then, this means producing fewer and smaller cars… 

So, there’s still a lot of work to be done – and policies enacted – before we can finally escape the Iron Age. 

“Opportunities for innovation on our journey to zero emissions extend far beyond the energy sector.”

A Double Whammy Solution

In related news, those amazing electric arc furnaces can apparently also recycle cement!

“Throwing old concrete into steel-processing furnaces not only purifies iron but produces ‘reactivated cement’ as a byproduct. If done using renewable energy, the process could make for completely carbon-zero cement,” according to ‘Absolute Miracle’ Breakthrough Provides Recipe For Zero-Carbon Cement’.

“Concrete is the world’s most used building material, and making it is a particularly dirty business – concrete production alone is responsible for about 8% of total global CO2 emissions. Unfortunately, it’s not easy to recycle back into a form that can be used to make new concrete structures.”

“As well as being a breakthrough for the construction industry, we hope that [this breakthrough] will also be a flag to help the government recognize that the opportunities for innovation on our journey to zero emissions extend far beyond the energy sector.”  

AI Used To Power More AI

A proprietary AI combines data around subatomic particles, radar imagery, and century-old mining reports to find mountains of copper, according to ‘A.I. Needs Copper. It Just Helped to Find Millions of Tons of It’.

“It’s a technique that would be new to mining, but it has a proven, if unusual, record. Previously it’s been used to suss out the location of burial chambers in Egyptian pyramids. Researchers have studied its potential for pinpointing illegal cross-border tunnels.”

“The deposit, in Zambia, could make billions for Silicon Valley, provide minerals for the energy transition and help the United States in its rivalry with China.” Some also hope that a similar approach can be used to find other minerals required for the transition to clean energy, such as lithium and cobalt.

And, another interesting fact: “Well before wire heralded the modern age of electricity, copper was essential to Bronze Age toolmaking. Many of Zambia’s best mines were originally spotted simply because colonial officials noticed that local people had already been mining them, sometimes for centuries.”

Hopefully, the locals will get a more equitable slice of the pie this time.  

“The resources needed to produce solar cells and plant them on solar farms are silicon-rich sand, sunny places and human ingenuity, all three of which are abundant.”

What Exponential Really Means

“An energy-rich future is within reach,” according to ‘The Exponential Growth Of Solar Power Will Change The World’.

“When it was a tenth of its current size ten years ago, solar power was still seen as marginal even by experts who knew how fast it had grown. The next ten-fold increase will be equivalent to multiplying the world’s entire fleet of nuclear reactors by eight in less than the time it typically takes to build just a single one of them.”

And the potential is limitless… “The resources needed to produce solar cells and plant them on solar farms are silicon-rich sand, sunny places and human ingenuity, all three of which are abundant. […] In contrast to earlier energy sources, solar power has routinely become cheaper and will continue to do so.”

“Anything that people use energy for today will cost less – and that includes pretty much everything. Then come the things cheap energy will make possible. People who could never afford to will start lighting their houses or driving a car. Cheap energy can purify water, and even desalinate it. It can drive the hungry machinery of artificial intelligence. It can make billions of homes and offices more bearable in summers that will, for decades to come, be getting hotter.”

“But it is the things that nobody has yet thought of that will be most consequential. In its radical abundance, cheaper energy will free the imagination…”

Let’s get to work.

Read the previous edition: ‘Manufacturing – The News: A Risky Time To Cut Corners’.

The post Manufacturing – The News: Sun, Sand, And Human Ingenuity appeared first on Augury.

In the context of popped plane doors, collapsing bridges, and exploding space shuttles, “cutting corners” is often cited as a contributing cause. So, when does the drive for efficiency become a dangerous game? And how does this fit with the race for general AI? … Read all about it in our regular round-up of manufacturing-related news.

The Mighty Have Fallen

The headlines are full of stories of the dangers of “cutting corners”, with the most covered story right now being around Boeing and the fall-out of having a plane door blow out midair earlier this year – along with two relatively recent fatal crashes. 

According to ‘What We Learned From A Day Of Boeing Hearings’, a picture is emerging of a shocking company culture. “One hearing included testimony from whistleblowers who said bosses at Boeing had threatened them for calling attention to shoddy safety practices, with one saying the company also sought to cover up information about the flaws.”

The hearings taught what happens when quality is sacrificed over cost-cutting and workers are too scared to speak out. In addition, the regulatory body responsible for monitoring any shortcomings, the Federal Aviation Administration (FAA), “was unable to do anything about it.”

“The FAA could have prevented an ever-increasing list of production quality defects,” noted one witness. Hence, the agency is now stepping its own safety management systems by looping in feedback from manufacturers, operators and pilots.” 

“The proportion of its members who have less than six years of experience has roughly doubled to 50 percent from 25 percent before the pandemic.”

Brain Drain (Experience Matters)

Meanwhile: ‘“Shortcuts Everywhere”: How Boeing Favored Speed Over Quality’, painted a picture of brain drain: “When the pandemic took hold in early 2020, air travel plummeted, and many aviation executives believed it would take years for passengers to return in large numbers. Boeing began to cut jobs and encouraged workers to take buyouts or retire early. It ultimately lost about 19,000 employees company wide – including some with decades of experience.”

“‘We warned Boeing that it was going to lose a mountain of expertise, and we proposed some workarounds, but the company blew us off,’ Ray Goforth, executive director of the union, said in a statement, adding that he thought the company used the retirements as an opportunity to cut costs by replacing veteran workers with ‘lower-paid entry-level engineers and technical workers’.”

“The proportion of its members who have less than six years of experience has roughly doubled to 50 percent from 25 percent before the pandemic.” 

In Other Cutting-Corners Related News

“The wide-ranging fraudulent testing at Japan’s top automaker involved the use of inadequate or outdated data in collision tests, and incorrect testing of airbag inflation and rear-seat damage in crashes. Engine power tests were also found to have been falsified,” according to ‘Toyota Apologizes For Cheating On Vehicle Testing And Halts Production Of Three Models’.

“We are not a perfect company. But if we see anything wrong, we will take a step back and keep trying to correct it,” said Chairman Akio Toyoda, the grandson of the company’s founder. The elder Toyoda was also the ground layer of the Toyota Production System (TPS), which formed the basis of Lean Manufacturing – with both approaches championing the value of a happy and empowered workforce.  

“The apparent unraveling of the testing systems at Toyota and its group companies is an embarrassment for an automaker that’s prided itself for decades on production finesse and a corporate culture based on empowering workers to make ‘ever-better cars’.” 

“it would have been a bargain to have tug boats escort that ship as opposed to having to spend billions to replace this bridge, avoid the loss of life and the major hit to that region’s economy.”

Not All Automation Comes With A Happy Ending

Then there’s: ‘Behind The Baltimore Bridge Collapse Is A Familiar Story Of A Corporation Cutting Corners’.

“On March 26, the day after the commemoration of the 113th anniversary of the Triangle factory fire that killed 146 mostly female immigrant garment workers in lower Manhattan — a crew of a half-dozen immigrant men in a non-union paving crew fell 185 feet to their deaths from Baltimore’s Francis Scott Key bridge after it was rammed by the Dali, a rudderless massive cargo ship that was trying to leave the port without a tug escort.”

“In the overall scheme of things,” said one insider, “it would have been a bargain to have tug boats escort that ship as opposed to having to spend billions to replace this bridge, avoid the loss of life and the major hit to that region’s economy.”

Alternatively, control of the ship could have been regained by switching to manual control. “But to do that, you need sufficient crew strength […] People are [now] opening their eyes and asking, do I feel safe driving over a bridge knowing there’s a vessel going underneath it. Do I feel safe with a train coming into the city carrying all these chemicals? Do I feel safe on a plane while there’s a company cutting corners on how they build these things?” 

Demands Of the Job: To Cut Corners

“Frontline manufacturing workers in the UK say they’re having to cut corners and risk their safety to meet the demands of the job, prompting calls for employers to provide extra support,” according to ‘Half Of Manufacturing Workers Are Cutting Corners And Risking Their Safety At Work’.

“The research further reveals a gap in trust, as one in five (20%) say they reported a near miss to their employer, but it wasn’t taken seriously. Another 12% who saw a near miss didn’t report it as they thought their employer wouldn’t take it seriously.”

“On top of pressures in the workplace, manufacturing staff reported feeling stretched and stressed by external disruption. Four of the top five disruptions to the UK’s manufacturing workforce in the past 12 months are weather-related, with hot temperatures, icy weather, floods, and poor air quality all preventing staff from doing their jobs, alongside road disruption.”

“With risk and disruption, communication is key. Management should maintain an open dialogue with staff on the shop floor and take reports seriously, especially as the technology exists to react in real-time and minimize disruption.” 

“When playing Russian roulette, the fact that the first shot got off safely is little comfort for the next.” 

Nothing New About Weighing Risks Versus Expediency 

As is becoming obvious, uncertainty often forces companies – and government organizations – to choose expediency over risk.

According to ‘What We Didn’t Learn From a Space Shuttle Disaster’: “The human element — sometimes heroic, sometimes cloaked in doublespeak and bluster — shines through the many technical aspects of this story, a constant reminder that every decision was made by people weighing risks versus expediency, their minds distorted by power, money, politics and yes-men. It’s a universal story that transcends time, from Napoleon’s decision to attack Russia to the recent Boeing 737 Max debacle.”

As the renowned physicist Richard Feynman wrote after the investigation into the Challenger accident: “When playing Russian roulette, the fact that the first shot got off safely is little comfort for the next.” 

Now What?

So perhaps there are lessons we should take on board as we enter a new age of AI – and chase after unleashing its many obvious benefits. Already, there are AI-driven tools for manufacturing that increase  efficiency without cutting corners — meaning they are decreasing risk. 

At the same time, as the development of generative AI only accelerates, we should stay awake and build AI for the right purposes. After all, it remains uncertain what all the consequences can be. And certainly, there’s still a lot of trust-building to be done.

In other words, this is definitely not a time to cut corners. 

Read last month’s ‘Manufacturing – The News: Healthy Alternatives For Uncertainty?.

The post Manufacturing – The News: A Risky Time To Cut Corners appeared first on Augury.