‘The State of Production Health 2024′ report is filled with up-to-the-minute industry insights. However, what most struck Augury CEO Saar Yoskovitz were the many indications of manufacturers’ increased trust in AI to help address their challenges. “AI’s impact on the workforce and user buy-in is improving, enabling manufacturers to look to larger, persistent opportunities such as supply chain issues and capacity.”

Good News Against Manufacturing’s Universal Challenges

“The State of Production Health 2024” builds on the baseline-defining premier report from 2023. Hence, it not only defines the current state of affairs but also charts any ongoing shifts. And on one level, there’s much to celebrate: the trust in AI solutions is growing.

The survey suggests AI-powered tools have helped alleviate workforce stresses – after ‘upskilling the workforce’ was the main reason for leveraging AI in 2023 (25%). Now, it would seem manufacturers are ready to set their sights on AI solving other problems. For example, supply chain issues rose to the top in 2024, up 11% from a fourth-place ranking last year, in terms of being the “primary factor that could limit your ability to meet production targets/business objectives over the next 18 months”. 

The report is based on 705 qualified responses from decision-makers working at $100M+ companies with at least five manufacturing sites. These companies cover various industries, including building materials, cement, chemicals, consumer packaged goods, food and beverage, pharmaceuticals, metals and mining, oil and gas, paper and packaging, and wood products.  

“I’m lovingly calling the market now ‘Covid junior,’ because in a lot of ways we’re right back to where we were during the pandemic.”

Facing Down a Strained Supply Chain – Again 

“With workforce upskilling initiatives returning value, manufacturers are shifting their spend toward supply chain and capacity concerns,” the report states. “With over 90% of the manufacturers agreeing that supply chain disruptions are expected to become more frequent over the next 12 months.” 

This fear is easy to explain. As a director of a logistics company in the article ‘It’s All Happening Again.’ The Supply Chain Is Under Strain’ eloquently says: “I’m lovingly calling the market now ‘Covid junior,’ because in a lot of ways we’re right back to where we were during the pandemic.” 

Except now, instead of battling a virus, we’re facing a perfect geopolitical storm. And: “If the supply chain disturbances of the pandemic proved anything, it was this: Trouble in any one place tends to ripple out widely,” the article states. 

“The consequences of the pandemic were difficult enough to grasp, with great miscalculations over the impacts on demand for factory goods. But everyone understood that pandemics end eventually. The Houthi strikes and the effects on the Suez Canal, on the other hand, involve enormous geopolitical variables that make forecasting difficult. […] There is no clear solution in sight.” 

In other words, we need to make every production moment count. 

“Nearly all the respondents either strongly agree, agree, or somewhat agree that AI and advanced technologies will help create new jobs in the manufacturing industry (97%), and they are personally optimistic about the future of the manufacturing industry (96%).”

Success – Especially Measurable Success – Builds Trust

So while supply chain worries distract manufacturers, the Production Health report also reflects a certain positivity – driven by an increased trust in AI’s ability to help on various levels. 

“Despite acknowledging the industry’s manifold challenges and obstacles to production, optimism for the future is evident. Nearly all the respondents either strongly agree, agree, or somewhat agree that AI and advanced technologies will help create new jobs in the manufacturing industry (97%), and they are personally optimistic about the future of the manufacturing industry (96%).”

And the faith in AI seems to be aligned with how it’s become easier to measure an AI project’s success. As the report states: “The significant growth in respondents reporting the ability to quantify value from AI investments in various areas indicates that manufacturers are getting better at using AI, and thus increasingly realizing a return on investment.” 

More Success, Less Hurdles 

The increase in speedy ROI perhaps explains the 300% increase in respondents citing no roadblocks when adopting AI tools to solve production challenges. “Six percent of 2023 respondents said there were no roadblocks to AI adoption, whereas in 2024, that figure grew to 19%.”

But perhaps the most heartening is the apparent drop in the number of AI projects ending in “pilot purgatory”. “Half of respondents (50%) said that between 11% to 25% of AI projects reached scale at their sites, and four in 10 (40%) said between 26% to 50% of AI projects reached scale.” These numbers starkly contrast to those of the World Economic Forum, which shows that over 70% of companies investing in Industry 4.0 technologies fail to move beyond the pilot phase of development.

It seems Industry 4.0 is finally coming of age.  

“As manufacturers look toward the future – and specifically toward improving production health – those who have yet to embrace IoT connectivity and AI solutions need to do so immediately.”

Onward and Upward

As the report states, “Crucially, optimism in the value of AI is a key uptick and very promising for the future state of manufacturing. AI continues to offer promises to create a much more empowered workforce, unlock efficiencies, create new collaboration methods, and change how manufacturers plan for and measure success across the organization – including machines, processes, upskilling, waste reduction, operations, and more.”

But yes, there’s still much to be done. 

“As manufacturers look toward the future – and specifically toward improving production health – those who have yet to embrace IoT connectivity and AI solutions need to do so immediately. While those who have already found success should expand those investments to better visualize and act on the data that connects machines, processes, and operations. This is foundational to the ability to meet production objectives while overcoming what they say are today’s key challenges, such as capacity constraints, supply chain issues, workforce concerns, and equipment reliability and efficiency.”

Let’s get to work.

Read the full report: ‘The State Of Production Health 2024’.

The post Report: Trust In AI Is Growing With Manufacturers appeared first on Augury.

As a lead-up to Augury’s Beyond The Line event on June 18th 2024, Augury Co-Founder and CEO Saar Yoskovitz presents a three-part series on how new technologies are aligned to help manufacturing meet its many different, and often conflicting, goals. In parts 1 and 2, Saar summarized the ongoing challenges and emerging solutions. Now, he outlines the required capabilities manufacturers need to flourish in this new era of data-centric manufacturing.

Let’s do a quick recap! We started with ‘The Manufacturer’s Nightmare’, in which we presented a dreaming golfer who realizes his old bag of golf clubs can no longer make him a winner in today’s modern world. And yes, that golfer represents today’s manufacturers who wonder how they can deliver the massive leaps in efficiency, sustainability, quality, and flexibility needed to meet the demands of their customers, investors, and employees. 

In part two, we showcased ‘A New Bag Of Tricks’ – those macro trends in technology and the workforce that are now creating tremendous opportunities for manufacturers. Indeed, a new set of clubs exists that will help turn many of the rosiest promises of the past years into practical solutions – and do things manufacturers previously only dreamed of.

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But how do manufacturers apply those trends to bring this dream to life? How do they create a blueprint for themselves and their strategic vendors to ensure they have the digital infrastructures, new work processes, and highly skilled teams they need to win?

We will now address these questions. 

Capturing The Magic: Think Capabilities, Not Products

Step one: you need to realize that no one can predict all the answers. A strategy for manufacturing crafted even a few years ago, for example, would not have embraced the emerging power of generative AI platforms such as ChatGPT – much less, Chat GPT 4.0. It would have underestimated the advances being made by smaller startups and emerging leaders in applying Machine Learning, AI, and data engineering to basic but crucial challenges such as energy management, asset reliability, and process optimization. 

“Step one: you need to realize that no one can predict all the answers.”

The key is to think about general capabilities, not specific products. And, here are the five capabilities that must be built into the emerging digital ‘tech stacks’ of successful manufacturers:

Five Required Capabilities for Digital Success 

1)    Infrastructure: Reliable Sensing And Computing – From Cloud To Edge

The modern foundation for AI-driven manufacturing will need to be cloud-based. Only by aggregating massive volumes of data can AI models evolve quickly enough and become trustworthy enough to be used confidently in manufacturing. The Cloud is ideal for this task. 

But while models might be built and trained in the Cloud, real-time insights needed for autonomous production optimization will also require work to be done much closer to the manufacturing process. In other words, computing power needs to extend from the Cloud all the way to the Edge – namely, the assets themselves and even the sensors that are collecting and analyzing the vast amounts of data already generated by modern manufacturing systems. 

AI processing at the Edge not only reduces cost but also increases speed. This way, changes to processes or spotting risks to assets or people can be done in minutes and executed in real-time on the plant floor – and not discovered days later through some centralized data science exercise. 

“But while models might be built and trained in the Cloud, real-time insights needed for autonomous production optimization will also require work to be done much closer to the manufacturing process.”

Integrations must be ubiquitous. This is not just about moving data from one place to another, but also integrating disparate tools to take advantage of raw data and insights generated by other systems in the manufacturer’s overall technology stack. 

2)   Insights: Agility in Data Collection and Sharing

Manufacturing systems will throw off ever more data as sensing becomes more ubiquitous and affordable. This will feed more powerful and accurate AI systems and give the people who use them deeper, more effective insights into the tactics needed to optimize manufacturing. 

But as data volumes grow and analysis becomes more real-time, data collection itself will need to become more responsive. Rather than fixed sensing at regular time intervals, sensing regimes must be more dynamic. For example, you might want to increase or vary your data collection when indications suggest deeper analysis is required or when you want to respond to certain behaviors of machines or processes. To do that, AI engines have to create models at the speed of production – which means in a matter of hours and not months.

Like the ‘gain’ function on a radar, which can be turned up or down to achieve greater accuracy or reduce unnecessary signals, sensing depth and power should be variable to match the depth of insight to the task at hand. This will help control costs, reduce bandwidth requirements, and create new opportunities for analysis.  

“The added context provided by a more diverse array of data types will mean faster and more confident decision-making by people and the digital systems that support them.”

3)  Coverage: Everywhere And Beyond

A) Multidimensionality Of Insights And Data Sources

Just as with a self-driving car finding its way through a combination of data sources and sensors (GPS inputs, on-board cameras, LiDAR systems, etc), the AI-driven processes that will help manufacturers navigate complex process changes and asset management strategies will benefit from more and more sources and types of data. The added context provided by a more diverse array of data types will mean faster and more confident decision-making by people and the digital systems that support them. 

This scenario is already emerging in areas such as Machine Health, where classic data inputs such as vibration or temperature are now being augmented with external processes and factors, such as input pressure for water or materials, environmental conditions like humidity, and even the specific SKU being run at any given time.  

All of this can help get better insights into machine performance and reliability. Hence, manufacturers should ensure they’re architecting strategies to embrace and demand these integrated data collection and analysis approaches. Here, it will be particularly important to break down insights and contexts into four functional levels:

Forensic: Data and context that help determine after an event what caused it to occur
Predictive: Data and insight that can identify with high accuracy when an event will occur
Prescriptive: Data and insight that can predict an event and provide the best means of intervention to prevent negative outcomes and maximize positive ones
Proactive: Data and insight that’s trusted enough to also autonomously give commands or adjust systems or processes to prevent negative outcomes and maximize positive ones. 

B) Broad Instrumentation And Coverage

The manufacturing process is an incredibly complex and integrated effort involving tens or hundreds of mechanical components, raw materials with constantly varying characteristics, and changing goals (cost optimization, throughput, quality, etc). 

Data will also need to come from everywhere to make insight-driven manufacturing a full success. Every machine type and all key subprocesses will need to be instrumented and understood, and those data sources will need to be brought together into a holistic view of the end-to-end process.  

“Leading manufacturers will harness that power to be able to adjust processes in real-time, within individual shifts, and continually tune the mix and behaviors of machines, materials, and even work processes to get the desired outcome every time.”

C) Holistic Approaches To Assets, Processes, And People

Manufacturers will need to be able to see all the elements of a process through a digital lens. Basically, this involves taking the ‘digital twin’ concept to a whole new level. 

Capturing and understanding the interrelationships between the hundreds or thousands of variables that exist in any manufacturing operation will be essential for optimizing overall production. Long the ‘holy grail’ of manufacturing, that end-to-end visibility can become a reality today due to the intersection of technology trends outlined above. Leading manufacturers will harness that power to be able to adjust processes in real-time, within individual shifts, and continually tune the mix and behaviors of machines, materials, and even work processes to get the desired outcome every time. 

Domains of work that are isolated today (such as asset management not being connected to process optimization, or operating parameters not being able to incorporate changes in weather or raw materials compositions, etc) will come together to enable higher-order decision-making by truly cross-functional teams. 

“Manufacturers must have a culture and rewards system that attracts and retains a new generation of digitally native workers while providing the training and opportunities that keep their current expertise in-house and motivated.”

4)   Engagement: Digital-Ready Workers and Culture

While all these technological advances create the opportunity for a new era in manufacturing effectiveness, in the end, it will, as always, come down to the people who use them. Manufacturers must have a culture and rewards system that attracts and retains a new generation of digitally native workers while providing the training and opportunities that keep their current expertise in-house and motivated. 

While worker, product, and environmental safety will remain paramount, the speed of innovation will become more critical. Manufacturers will need to understand where they can take greater risks and where they can even afford to ‘fail fast’ to try out new approaches and tools. 

The decentralized decision-making prevalent at many manufacturers will need to evolve. The benefits of data-driven manufacturing will be amplified by scale. With more data flowing in and insights flowing out, learning will be accelerated – along with the flow of benefits for all the processes and plants across a portfolio.

And as the individual manufacturer tweaks its in-house capabilities, the external world must also lend a hand…  

“The winning manufacturers in this new era will not be the ones who try to work in islands, but those who see the benefits of connectivity and data sharing.”

5) Ecosystem: Long Live Not Living On An Island

Data sharing across supply chains, with OEMs and other partners (and even aggregated data sharing, in anonymous ways, between competitors) will deliver even greater benefits due to the rapid improvement it can drive in AI models and algorithms.

The winning manufacturers in this new era will not be the ones who try to work in islands, but those who see the benefits of connectivity and data sharing. Speed of innovation and the courage to move quickly will outweigh the traditional benefits of secrecy and proprietary thinking.

The Lean Dream Coming True

And of course, all these capabilities interact and build on each other. With data finally breaking down silos between work functions, the full power of concepts in lean manufacturing, TPM, or similar models will finally be able to be realized. 

Just as IT operations and application security eventually fused with software development to shorten cycle times, reliability, process engineering, and other functions can come together in one integrated approach to optimizing manufacturing. 

So, let’s revisit that golfer’s nightmare in the first post… He’s standing at the first tee and realizing all their once trusty clubs were either gone or useless. However, with this new set of capabilities in place, his nightmare can turn into the dream scenario where the bag is full of a new set of clubs – designed with AI precision, crafted of the latest materials, and proven in the hands of the world’s best experts. Now, that’s the manufacturing world we can build for the future. 

In other words, as with golf, we can now enter the zone.

Read Part 1 of Beyond The Line: ‘The Manufacturer’s Nightmare’
Read Part 2 of Beyond The Line: ‘A New Bag Of Tricks’

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The post Beyond The Line (3): Bringing The Manufacturer’s Dream To Life appeared first on Augury.

As a lead-up to Augury’s Beyond The Line event on June 18th, 2024, Augury Co-Founder and CEO Saar Yoskovitz presents a three-part series on how new technologies are aligned to help manufacturing meet its many different and often conflicting goals. After summarizing the ongoing challenges in part one, Saar now presents the macro-trends opening up new possibilities – to make old promises a reality.

Innovation Can Be A Waiting Game

There’s a saying attributed to Bill Gates: “Most people overestimate what they can achieve in a year and underestimate what they can achieve in ten years.” That truism also applies to changes in our technologies and practices: we generally overestimate how quickly and effectively new technologies and trends will impact us in the short term while underestimating their long-term transformational impact. 

For instance, the 1939 World’s Fair predicted flying cars and robot helpers for our homes, and in the 1950s, Dick Tracy comics showed off his two-way wrist radio. All those things have come true to varying degrees – albeit decades after the most optimistic prognostications. In fact, it was only in 2023, the FAA approved the first flying car prototype.

What keeps those things from coming true faster oftentimes isn’t the core idea or invention; it’s the supporting technologies and conditions needed to make them practical. Making small radios was not a problem in the 1950s, but small, powerful batteries were. And while the basic requirements of a flying car were already known for decades, we lacked the compact engines, GPS software, and robotics needed to reduce the risk brought on by non-expert operators.

Read part 1 of this series:
‘Beyond The Line (1): The Manufacturer’s Nightmare’.

Enabling Tech Is Now Catching Up

For decades, manufacturing has had real-time data-driven predictions and insights, as well as automation – innovations that could transform our machines and our relationships with these machines. However, the practical application of that idea has lagged well behind the predictions of how soon this would all play out. The reason, again, was the lack of supporting technologies and conditions. 

However, the developments have been rapid, and the supporting tech is now available to open the door to a massive change in manufacturing. We can now look forward to huge gains in productivity, quality, sustainability, and efficiency. So, what’s changed that allows us to finally turn a decades-long promise into a reality?

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Five Macro Trends Driving The New Era Of Manufacturing  

1)    Cheap Processing Power – And Lots Of It

You need massive processing power close to where the work is being done to get the near-real-time insights that can lead to fast, effective responses to process deviations, reliability risks, or quality escapes. Processing power has made those leaps, and today, cheap ubiquitous processing at the edge of our computing networks – and therefore at the center of our manufacturing processes – is now a reality. 

2)    Trustworthy Data – And Lots Of It

Manufacturing environments have become increasingly chatty over the years. Many assets already come with some level of sensing and data collection capability. For others, it’s more about choosing from an increasing array of third-party sensing solutions, which are often tied to specific use cases (quality, reliability, compliance). 

Either way, or in combination, the overall result is that manufacturers now have vast quantities of data about their processes, assets, and operations. However, to apply all this data you need evolved AI capable of applying powerful analytics… Which leads us to:  

3)    A Massive Leap In AI Effectiveness

While Generative AI systems are getting all the news today, more purpose-built, AI-driven solutions have impacted parts of manufacturing for several years now in areas such as reliability and maintenance. 

What’s made these more purpose-built solutions successful is oftentimes they are end-to-end solutions that solve the entire problem, from data collection to analysis and insight. More general-purpose uses of AI, however, have been less successful. But today, the constraints that have limited AI effectiveness – namely, lack of sufficient processing power where it’s needed and lack of sufficient trustworthy data to train AI models – are falling away. 

The result is that layers of AI-driven solutions, some more purpose-built around quality, reliability, and efficiency, and some more generative and interactive built on platforms such as OpenAI, can be effective in terms of their ability to be trusted copilots or ‘assistants’ to more complex manufacturing problems (such as end-to-end process improvement). 

4)    Greater Connectivity Between Systems

Data is great to have, but data trapped in silos is just an added storage cost. Happily, these siloes are starting to break down thanks to Increased connectivity between manufacturing systems, increased use of cloud infrastructure, and emerging sets of APIs to enable manufacturing systems.

The ability of these systems to “talk” to each other is key to powering the emerging AI-enabled decision-making tools and enabling real-time, autonomous optimization of everything from spare parts management to the manufacturing processes themselves.  

5)    A Workforce Eager To Embrace New Technologies.

New tools and technologies are only as good as the rate at which they are adopted and fully utilized. Fortunately, the workforce entering manufacturing today will not only adopt these tools but demand them. 

These digital natives will be fully comfortable with AI-assisted decision-making and high levels of autonomy in the tools they use. They will accelerate the rate of adoption and the resulting transformation of a wide range of manufacturing processes. 

Companies used to capital investment cycles that span decades will have to learn to iterate at the speed of new technology, evolving their strategies and execution in months and quarters, not years and decades.

Right Place, Right Time

These macro trends around workforce and technology are intersecting just when it’s needed most. As many of the past strategies for increasing manufacturing efficiency become worn out, the new strategies and tactics enabled by AI, data, interconnectivity, and edge computing will step into the breach and spur another wave of productivity in manufacturing – one that’s efficient, sustainable, and more responsive to customer demand. 

But gaining the benefits of these trends doesn’t come without some effort. Manufacturers must develop clear strategies for their technology ‘stack’, ensuring they lay the foundation to grow, iterate, and scale. This will require different thinking on their part. Companies used to capital investment cycles that span decades will have to learn to iterate at the speed of new technology, evolving their strategies and execution in months and quarters, not years and decades.  

They’ll also need a clear blueprint of what they must build for themselves and what they should expect from their technology partners.

Now For The Real Work

Aspiring manufacturing leaders will also need to think of strategies that consider the insights from a strong insight-first strategy as crucial assets on the same level as pumps, rollers, or ovens. They’ll also need a clear blueprint of what they must build for themselves and what they should expect from their technology partners. So please tune in next time as we explore how to best do this on a practical level…

Read Part 1 of Beyond The Line: ‘The Manufacturer’s Nightmare’
Read Part 3 of Beyond The Line: ‘Bringing The Manufacturer’s Dream To Life‘

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The post Beyond The Line (2): A New Bag Of Tricks appeared first on Augury.

Augury CEO Saar Yoskovitz is a committed techno-optimist. A recent webinar with business consulting firm Frost & Sullivan reflects his sunny outlook on how tech can help manufacturing solve its most pressing problems. “It doesn’t matter where you are on that road; the tools are already there to drive you forward,” says Saar.

 

‘The AI-driven Factory: How Production Health Will Shape the Future of Manufacturing’ features our own VP of Strategy, Artem Kroupenev, and Sebastián Trolli, the Research Manager and Global Head of Industrial Automation at Frost & Sullivan.

As a deep-dive fireside chat, it does a wonderful job summarizing current manufacturing realities and outlines how the industry will transform over the next five to ten years – with early adopters having already paved the way.  

Our Age Of Complexity And Innovation

Sebastián ably described the ongoing challenges facing manufacturers today as defined by two words: ‘complexity’ and ‘innovation’. As he formulated it: “On one hand, there’s the urgent need to adapt to evolving market demands and stringent environmental regulations. On the other hand, there’s the challenge of leveraging technology to make these adaptations possible and profitable.”

A flurry of issues works to stir up the complexity: the skilled labor shortage, continued post-COVID supply chain disruptions, nagging inflation, shaky geopolitics affecting trade, etcetera. It’s a long and, unfortunately, long-familiar list.

There is good news. “Manufacturing operations are benefiting from the deployment of new technologies, which are offering solutions to traditional problems and opening up new avenues for growth and revenue,” says Sebastián. “The massive amount of data generated from operations presents a goldmine for optimization and innovation. However, the challenge lies in effectively harnessing this data to drive actionable insights. Analytics and AI are crucial to unlocking this potential.” 

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From Paper To Satellite

So, how far are we, as an industry, in applying such innovations concretely? Frost & Sullivan’s statistics are sobering. Despite the proven impact of AI and analytics on production optimization, a staggering 90% of manufacturers have not embraced AI at all yet. And of those who do take on digital transformation projects, 75% of these projects fail – succumbing to what’s called ‘pilot purgatory’. 

Artem provided an insightful analogy to put these numbers into perspective and highlight how we are, in fact, beginning a journey of ongoing progression. “Look at transportation over the last 20 years. We began with using paper maps. Then, we had these static GPS routes. And now, in the last 10 years, we’re using real-time turn-by-turn navigation. You can add stops. It adapts to traffic conditions. The basis is now laid for autonomous driving,” says Artem. “And now a similar thing is happening in manufacturing.” 

“Though we’re still at maybe 1% of adoption, across the wider industry, in five or ten years, it will be irresponsible not to implement these new approaches that can optimize the health of your machines and processes. You’ll simply be left behind. In fact, technologies are already out there as reliable products providing tons of value.”

ETA May Be Pushed Back, But We’ll Get There

Certainly, a factory can be compared to a car: they both have inputs, outputs, and complexities. To get the plant from A to B in terms of its optimization and driving product, many moving parts need to be navigated towards a similar goal. And that’s exactly what we’re seeing across manufacturing today. Unfortunately, too many manufacturers are still at the paper map stage. 

However, this is set to change fast, according to Artem. “Though we’re still at maybe 1% of adoption, across the wider industry, in five or ten years, it will be irresponsible not to implement these new approaches that can optimize the health of your machines and processes. You’ll simply be left behind. In fact, technologies are already out there as reliable products providing tons of value.” 

Follow The Leaders

Indeed, many factories are already achieving autonomy across various use cases – such as with Machine Health, where unplanned downtime is essentially a thing of the past. “And it’s important to note that by autonomy, I don’t mean that the factory has no people operating it,” says Artem. “In fact, the opposite is true: the people are empowered to really know how to optimize that factory, to create those double-digit improvements, in terms of efficiency, productivity, sustainability, and so forth.”

And, thanks to these pioneers, there’s already a clear roadmap for overcoming standard hurdles, such as establishing an effective change management program, properly documenting ROI and other wins, setting up a reliable IoT infrastructure, and dealing with legacy IT systems.  

Towards The Eternal ‘Golden Batch’

Meanwhile, these pioneers continue to push ahead. Machine Health and Process Health are both great. But the real goal is to combine these data streams, along with others, to provide actionable insights to optimize for full Production Health. In other words, we will be able to choreograph a dance between arenas that were previously wholly separated.

“There is absolutely an optimal way to run a factory at any given time,” notes Artem. “And most factories have run at their peak at some point in their history when all the stars were aligned. Everything was just perfect for a short period of time: the perfect production shift, producing the perfect product in the most efficient way possible. But then things go downhill. And there are too many variables to understand what went so right – or wrong.”

And now, with AI, we have the perfect tool to juggle countless variables – and do that in real-time so we have time to make adjustments to recreate that ultimate “golden batch.” Plus, you’ll be able to adjust your production process for multiple objectives – for instance, increasing yield and quality while saving energy and time. 

As Sebastián summarized nicely: “I see the future of manufacturing as brighter than ever.

Let’s get to work.

Watch the full fireside chat: The AI-driven Factory: How Production Health Will Shape the Future of Manufacturing’.

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The post Driving Towards A Future Of AI-Driven Factories – With You In The Driver’s Seat appeared first on Augury.

As a lead-up for Augury’s Beyond The Line event on June 18th 2024, Augury Co-Founder and CEO Saar Yoskovitz presents a three-part series on how new technologies are aligned to help manufacturing meet its many different, and often conflicting, goals. For part one, Saar begins by outlining the industry’s many sandtrap-like challenges. But rest assured, he’s just setting us up for a clean shot towards a happy ending

I’m not a professional golfer by any stretch, but I can imagine the kind of nightmare these folks could have. It goes like this: you’re approaching the 18th tee with a chance to win a championship. Your fans are eagerly watching; your sponsors are expecting a great outcome; all your hard work over the years is about to pay off. But you look at your golf bag; all your clubs are bent and broken. You have nothing to hit the ball with – and no way to satisfy your audience and achieve your goals. 

Hard To Win

This is a somewhat weird scenario, perhaps. But that’s how nightmares go. And for manufacturing leaders today, there’s a similar bad dream unfolding. But this one’s real, and not waiting for nightfall to cause stress. 

Manufacturing leaders might not have rabid fans or enthusiastic sponsors behind them, but they do have demanding customers, impatient investors, talented employees, and sharp-eyed regulators – and they are all watching to see how well you perform. Success isn’t measured in low scores or championship wins but in metrics such as repeat purchases, earnings per share, worker retention, and sustainability goals.  

“But like that sleepless golfer, when today’s manufacturing leaders look into their bag, they don’t like what they see. The traditional tools are no longer in the same shape they used to be.”

You Need A Whole New Bag

None of these targets are easy to hit individually – never mind balancing each against each other. For years, those manufacturing leaders have had a strong and varied set of tools to use to achieve success – their bag of clubs, if you will. For instance, they could outsource manufacturing to lower cost countries or pressure suppliers to keep costs under control. They could dial up or down the workforce size or the number of their facilities to match changes in demand. They could adopt new technologies and new work processes to increase efficiency. And more recently, they could enjoy strong pricing power to pass higher costs onto customers without risking loyalty.

But like that sleepless golfer, when today’s manufacturing leaders look into their bag, they don’t like what they see. The traditional tools are no longer in the same shape they used to be. So, while customer demands, shareholder expectations, and regulatory burdens remain or grow, the tool bag looks pretty empty for today’s manufacturers.  

“It’ll sound pretty discouraging but don’t despair.”

Disclaimer: Good News Ahead

I’ll use the remainder of this post to detail how the macro environment has emptied the tool bag for these leaders. It’ll sound pretty discouraging but don’t despair. In follow-up blogs, we will explore how a different set of macro trends are coming together to create new opportunities to transform manufacturing – a new bag of tricks for leaders to draw on to continue to drive their business forward.

We will also talk about the trends themselves, how manufacturers will have to think about putting them to work, and what they should expect or demand from their partners and suppliers, who will be critical for delivering the solutions that turn these new possibilities into real-world answers.

So let’s dig into the nightmare first, but with the optimism that we will all wake up to find there’s actually a brighter day ahead for manufacturing leaders.

“We’ve gone from a ‘just in time’ supply chain optimized for efficiency to a ‘just in case’ approach centered on risk.”

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The Rethinking Of The Global Supply Chain

For decades, leading consulting organizations, economists, and even global geopolitical strategies drove the idea that the key to improving manufacturing efficiency was leveraging the lower costs and high efficiencies of global manufacturing. The idea was that cheaper labor, affordable shipping, and relative global calm would make it possible to produce goods in the least expensive locations and then sell them in the richest markets safely and efficiently. 

Unfortunately, this strategy has been put into doubt by a confluence of factors: rising costs in those countries (who knew their workers would want to get paid too?!?), constraints in global transportation networks (remember COVID, the Ever Given, and more recently the Baltimore Port disaster?), and an increasingly nationalistic political climate rife with wars of both the tariff and shooting kind. 

As a result, supply chain resilience has too often come to mean giving up cost efficiency to gain safety and predictability or to placate political policymakers. We’ve gone from a ‘just in time’ supply chain optimized for efficiency to a ‘just in case’ approach centered on risk. To localize those global supply chains, many countries are investing billions of dollars – or even a trillion dollars in the case of the US. And this is a task that will take years to accomplish, assuming the political will remains… 

So, there’s all that…

“But those suppliers rely on the same bag of tricks as every other manufacturer, so they are also finding it harder and harder to find new efficiencies.”

The Squeezing Dry of the Supplier Network

Meanwhile, leading manufacturers have been great at doing all they can to make cost issues their supplier’s problem through massive cost pressure on supplier networks. This has had the benefit of squeezing inefficiencies out of supplier networks, materials costs, and such. 

But those suppliers rely on the same bag of tricks as every other manufacturer, so they are also finding it harder and harder to find new efficiencies. They’re starting to push back on their own customers and forcing those further down the line to look for other avenues to reduce cost or increase efficiency.

The Growing Power of the Worker

Certainly, the workforce is no longer a place to go for cost savings. As with other industries, layoffs and hiring cycles have always been a part of managing costs and capacity in manufacturing. When workers were plentiful and had limited options, this approach was easy to implement. New workers (or furloughed ones) could be brought in relatively quickly – and thus limiting the risk of reducing the workforce during slow times. 

Today, however, manufacturers struggle to fill even their currently available jobs. New plants are slow to come online even with billions in construction incentives because workers can’t be found to fill them. This scarcity of new talent is exacerbated by the ongoing retirement of the current experts, draining institutional knowledge and practical experience. These losses will take decades to replace without new approaches such as skills-based hiring practices, on-the-job training, and actively appealing to younger generations by, for example, more actively addressing their concerns around sustainability. 

Regardless, companies are increasingly unwilling to reduce headcount in technical and manufacturing roles because of the risk they won’t be able to backfill those roles – or replace that experience – down the road. Add to that the ability of workers in this time of scarcity to demand higher wages, everyone is now very aware of how we need to look elsewhere to cut costs. 

The Limits of New Work Processes (Manufacturing Creates Boat, Then Misses Boat)

More advanced companies embraced processes around Total Production Maintenance (TPM) and Lean Manufacturing, hoping that more cross-functional, agile teams could wring new gains out of productivity. While those processes made an impact, limits were reached because of constraints beyond anyone’s control. 

While islands of people could quickly be reorganized into cross-functional teams, the islands of data tied to each part of the process could not be so quickly integrated. Like the blindfolded men and the elephant, even though the teams could speak together and plan together, they were still forced to see the manufacturing process through disparate lenses. As a result, data-driven decision-making was slow at best and impossible at worst.

But while execution did not live up to expectations for manufacturing, the concept around TPM has been proven, ironically, outside of the industry that developed it. For instance, software development and sales and marketing were able to more readily integrate unified goals and the sharing of the same real-time data and insights to fundamentally change how they worked. As terms such as Agile and Empowered Teams became universal, DevOps and then DevSecOps became common practice for software development, and integrated sales and marketing ‘pods’ emerged in business-to-business selling.

And while other industries now have their Salesforce and Atlassian based on inspiration from manufacturing, the industry that originally pioneered this approach still lacks the tools to make this game-changing shift on a large scale. (Until now…)

The Changing In The Power of the Purse

And really, the manufacturing sector obviously needs all the help it can get. As they do battle with a shifting landscape as outlined above to stay in business, they must also still forge ahead in meeting sustainability goals – defined by both government regulators and public pressure – while also making sure they still cater to consumer demand. 

“Manufacturers can no longer look to their customers as the solution to their own rising costs or continued inefficiencies.”

Certainly, in more recent years,the supply and demand curve has been greatly distorted by the COVID-19 pandemic and subsequent government responses. Apart from the absence of goods on shelves, inflation skyrocketed even as consumers saw increased spending power due to COVID-related subsidies and other related government stimulus across many countries. This enabled manufacturers to pass higher costs on to consumers and, in some cases, increase profits in the process. 

Today, as those factors have washed through the global economy, pricing power has become more balanced. Consumers are no longer as willing to accept higher prices, and instead do more comparison shopping and bargain hunting. And in some cases, governments have ridden the consumer frustration wave and threatened penalties for ‘price gouging’.

This means manufacturers can no longer look to their customers as the solution to their own rising costs or continued inefficiencies. Meanwhile, increasing interest rates have pulled the rug from under the manufacturer’s feet by also working to decrease consumer demand.  

And From Here?

So here they are –  the world’s manufacturing leaders – staring at a long drive to the flag, all eyes upon them, but knowing that the tricks and tools that have served them so well for the past years and decades are no longer in their bag. Time is ticking down for them to make their next play. But what’s it going to be?

Read Part 2 of Beyond The Line: ‘A New Bag Of Tricks’
Read Part 3 of Beyond The Line: ‘Bringing The Manufacturer’s Dream To Life‘

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More than two-thirds (69%) of CPG manufacturers said they planned to increase AI investments over the last year (second only to food and beverage manufacturers at 74%). And they have high hopes for those investments: when asked which production goals they believe AI can help them achieve, CPG leaders listed workforce, capacity, and yield/throughput issues.  

Consumer packaged goods (CPG) manufacturing covers a lot of ground–from toothpaste, diapers, and cosmetics to yogurt, chips, and beer. But while diverse in products, CPG organizations all face similar challenges–but some companies are driving deep changes in the industry.

Consider just a few shifts happening in CPG: Barriers to enter the market are lower than ever, consumer tastes are moving toward more personalized and healthy products, and sustainability standards are changing how products are produced up and down the supply chain. All of this is putting strain on  manufacturers to become leaner, cleaner, and more efficient across the board–from improving capacity and uptime to reducing waste and attracting and keeping workers. 

CPG Sees Red Flags with Capacity and Workforce Issues 

Augury’s recent manufacturing-wide survey, The State of Production Health, uncovered fascinating details around those challenges, shedding light on how CPG compares to other industrial sectors and offers insight into how organizations are using technology to overcome their biggest hurdles. 

When asked to name their three biggest manufacturing challenges, CPG respondents answered with a consistency not seen in the other verticals: 

• Workforce constraints/upskilling and capacity constraints tied for first–the top picks among almost half of all respondents; forecasting production and scheduling came in just under those.

By comparison, manufacturers as a whole across all nine surveyed verticals listed the high cost of materials/energy, capacity constraints, and quality/yield/throughput issues as their top three challenges. 

CPG leaders reiterated their workforce concerns elsewhere in the survey:

• When asked to name the primary factor that could limit their ability to meet production targets and business objectives over the next 18 months, staffing constraints topped the list by a mile with nearly 42%–considerably higher than any other vertical in the survey.
• Diving deeper into those staffing challenges, CPG leaders tagged increasing competition and knowledge transfer as their thorniest workforce obstacles; interestingly, lack of technology came in third.  

The findings paint a difficult picture, to be sure, but there is also evidence of positive approaches to these challenges, especially in the industry’s embrace of Artificial Intelligence (AI) technology. Still, they’ll need to better harness its true potential before they can claim victory. 

AI as Tool, Not a Remedy 

More than two-thirds (69%) of CPG manufacturers said they planned to increase AI investments over the last year (second only to food and beverage manufacturers at 74%). And they have high hopes for those investments: when asked which production goals they believe AI can help them achieve, CPG leaders listed workforce, capacity, and yield/throughput issues. 

Those are smart targets for the industry. CPG manufacturing processes are complex and dynamic, with variables like raw material use, quality concerns, energy consumption, machine health conditions, and other shifting priorities making it incredibly difficult to find the right balance as you try to meet capacity or yield goals. 

Applied to manufacturing process health, purpose-built AI (solutions developed for and directed at specific process challenges) infuses machine learning algorithms with deep process expertise from a production line. This allows AI to go beyond just looking at data to consider all the unique variables of that production line, from dynamic traceability to loops, buffers, raw material variances, parallel processes, multiple SKUs, and other considerations. This, in turn, allows teams to better target and meet goals around capacity, yield, throughput, and other KPIs. 

AI-powered machine health solutions use sensors to monitor pumps, motors, conveyors, and other types of rotating assets for anomalies in vibration, temperature, and other factors. By analyzing the data in real time, the solution provides accurate and actionable insights to maintenance and reliability teams, helping them resolve issues before they cause unplanned downtime and production disruption. 

Importantly for CPG companies, purpose-built AI solutions not only outperform traditional, human-led approaches to manufacturing optimization, but they also improve upon the skills of the humans themselves. Empowered with AI co-pilots, teams are freed from mundane tasks and firefighting, allowing them to act faster and smarter and focus on optimizing production lines. 

It’s precisely this kind of AI investment CPG companies should be pursuing as they look to retain or regain market share and become truly resilient, efficient organizations. 

One leading global CPG company’s experience with AI-driven predictive maintenance serves as a prime use case. By embracing AI and IoT technologies early and quickly, they were able to uncover issues in a critical machine, saving 2.8M pieces of end-product and avoiding 192 hours of machine downtime.”

The manufacturing environment is changing fast, across all verticals, and leveraging purpose-built AI is not just a nice-to-have–it’s an essential component for a competitive company. With more efficient processes and machines, organizational resilience, and an intelligent, well-armed workforce, CPG organizations will not just survive, but thrive, while also impressing consumers with higher quality, fairly priced, and innovative products. 

Read the full “State of Production Health” report here. Then see how Augury’s AI can deliver value to your manufacturing business.

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As a dual Israeli-American company, these weeks have been without a doubt the toughest we have ever faced. The support and concern we’re receiving has been overwhelming, heartwarming and greatly appreciated. Thank you.

Keeping it together

At this point in time 30% of our 160-person team in Israel are either serving in the reserve forces or have close family in the army. And the rest are at home with their children, worrying about what the future holds.

But in this time of hardship, is when our true spirit shines. I am dumbfounded by the acts of care and kindness that surround me. People opening their homes, supporting each other, volunteering and putting complete strangers’ interests before their own. Whole communities mobilized and organized to make sure every person that is impacted gets the support they need. No one gets left behind.

Inside Augury it’s no different. Our number one priority is the health – both physical and mental – of our team and their families. The level of strength, support and “togetherness” that I see leaves me speechless. The team in Israel continues to deliver while their global peers jump in wherever they can to cover and close any gaps.

Our customers and partners trust us with the reliability and safety of their production lines, and we will not let them down. 

Coming back together

I was interviewed for a recent The Wall Street Journal article, ‘SodaStream Built a Factory for Israelis and Palestinians to Work Together. Then a War Erupted’ [gated]. I told them: “We have Arab employees, we have secular Jews, we have Orthodox Jews, we have right-wing and left-wing. Everyone is going through hell right now, and everyone has their own version of it.”

In January of this year, at the Calcalist כלכליסט “Power In Diversity” Conference, Augury won the award for the highest representation of Israeli Arabs in a Tech company. And it’s true we’ve put a lot of effort into creating an environment that enables people from different backgrounds to come to work every morning and feel safe and respected.

During times of peace our diversity is a source of power and pride. In times like these, when Israel is at war and opinions and beliefs could widely differ, it’s even more important that we keep our promise to respect each other and create a safe space for our team members.

When this is over, and someday soon it will be, we need to think about the society we want to build. Bringing people together through tighter collaboration is the best way I know to bridge cultural divides.

“I hope that we can come back together. If we do not, that will be a very big mistake,” said a manager at Sodastream in the same article. “We all have to stay in hope. We have to show that we really believe in that.”

I totally agree.

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Technology solutions can undoubtedly increase operational efficiency and create new revenue streams. And it’s up to the technology provider to put the user central and make sure the application is clear and understandable throughout the customer journey, says Augury CEO Saar Yoskovitz.

I’m writing this on my way back from the McKinsey’s IoT Summit 2023, where I had the opportunity to meet with key executives in our industry and sit on a panel with them. Even more importantly, I spent quality time and hosted a fireside chat around ‘Unlocking Productivity’ with Roger Brecht, VP of Digital Manufacturing at Nestlé Purina. 

Roger shared his experience of successes and failures in implementing digital solutions throughout his career – both as a plant manager and now as a VP. Roger was a star, and our session garnered excellent feedback since he offered concrete examples on how to best apply technological solutions to the plant floor. Essentially, it comes down to making it 100% about the user.

As he put it, “You need to incorporate the shop-floor operation into any solution design. You must understand their challenges and solve their problems.”

Don’t Blame The Customer

However, a later panel shined a light on a deeply troubling issue in our industry: few people are actually talking to customers or taking them into consideration when designing their solutions. 

In a discussion around why IoT projects fail, someone said most implementations fail because customers are not sophisticated enough to deploy the complexity of IoT solutions. I found this upsetting and had to respond: “It’s time we take more accountability as an industry. Instead of blaming customers for not being sophisticated, maybe we should call our product teams and tell them to stop creating complex products that no one understands.”  

Putting The Customer First

If anything, this interaction strengthens my conviction on how much ground we can gain if we maintain our focus on what really matters: making our customers successful. When we make them successful, we can feel it – particularly when they’ve already spent years trying to adopt and implement this type of technology and are only now finally getting the support, visibility and traction they need from all levels in the organization.

To make our customers successful, we not only need clarity in product and service. We also need flawless execution in terms of delivery, fast wins and ongoing support. As one of our champions recently described it: “The real story here is the scalability, we installed this in four days, and saw value in a few weeks… There is nobody out there who can add that sort of value at that speed.” 

Boosting the Industry

So, we already know what the outcome of a great execution looks like. And we as an industry must work hard to make sure we don’t ever fail our customers on their journey with us.  We all need to be accountable for the quality of our solutions and services and the value we deliver to our customers. They are trusting us to be great every single time. It’s up to us to continue building the technologies and processes that live up to that trust. 

When we do, we make our customers unstoppable. And if we are able to help instil this customer-focused attitude within other technology-oriented businesses, we will also contribute to a stronger and more future-resilient industry as a whole.

Roger nailed it when he said: “Any technological advancement needs to be driven by how it benefits both business goals and the end user.”

Read: ‘Transforming Manufacturing: Turning Lighthouses Into Seas Of Light’.

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Augury Co-Founder and CEO Saar Yoskovitz travelled to Davos 2023 to explore how manufacturing can become the “lighthouse by which it can help solve the world’s greatest challenges.” In this post, he shares his biggest takeaways.

For five intense – and inspiring – days at World Economic Forum’s (WEF) Annual Meeting in Davos, I was able to listen to and connect with an engaged array of world leaders in government, business and social institutions. What struck me most was how the mood has shifted since the previous WEF Annual Meeting last May. 

At the time, things were looking bleak: the world was facing an uncertain recession, the Russia-Ukraine war had just broken out, supply chains were in shambles and “de-globalization” was the most recurrent buzzword. Under these circumstances, any conversation about the environment and investing in sustainability felt like lip-service.

Eight months later, the world seems much more stable: Ukraine is holding up, the energy crisis has been largely averted, global inflation seems under control, and supply chains are building capacity. This brightening scenario enabled much more constructive conversations on how we tackle the world’s biggest challenges. And in this process, I picked up a few insights…

1) In It Together

I found it amazing that the challenges of our growing company are very similar to those of the world’s largest and most prestigious companies. We’re all looking for any signs of clarity on the economic climate ahead. All of us are trying to balance a desire for growth with smart decisions on resources. And we are all taking seriously the global challenges around sustainability, workforce transformation and the efficiency and effectiveness of a global industrial and manufacturing base.

And, most importantly perhaps, we all realize progress still comes down to the basics: smart people getting together to sweat out the details, agree on directions, and really put in the effort to make change happen.

2) Tech Is Coming Of Age

With each annual meeting comes a flurry of reports, such as how circular transformation of industries is unlocking new value, how over a hundred ‘Lighthouse Factories’ are showing the way forward to a more sustainable future, and how AI is being applied to both fight climate change and spur growth. And what’s refreshing about these reports is how they are becoming less about what should be done, and more about what is actually happening.

The next phase of this journey is taking our lighthouses – unique examples of success that shine bright – and scaling them throughout the industry. And I am proud to say this all resonates nicely with Augury’s mission: creating a world where the combined work of people and machines makes life better in every way. 

3) New Trends: Glocalization and Friendshoring

Last year’s big buzzword de-globalization is off the table. It has been replaced with another one: glocalization. This means we are globally interconnected, but have more localized supply chains. While this is linked to creating more resilience, it’s also related to the fact that alternative energy sources are more local by nature and are harder to transport. For instance, solar energy is generated during the day and wind energy when it’s windy – and currently we have no means of mass storage or transmission. This situation will naturally lead to more decentralization of industry. Factories will go to where the cheapest and greenest energy is available (something we’ve seen play out with data centers in the past).

Another emerging term: friendshoring replacing offshoring. Namely, how do we embrace countries that share our values and limit single-source dependencies as we had in the semiconductor industry? The US/EU IRA and CHIPS bills are a huge step in these directions.

4) Sustainable and Circular Supply Chains Have (Finally) Become A Priority

Spurred by upcoming regulation around carbon reporting, larger companies are prioritizing sustainable and circular supply chains. Scope 3 emission tracking – that takes into account the total footprint of a product by also including the upstream and downstream impacts of its supply chain – is being described as “a nightmare” by some.

It’s certainly tricky. Everyone is scrambling to track it properly but are lacking proper frameworks or tools. Scope 3 is also highly relative between products. For a cement manufacturer, Scope 3 is only 6% of their emissions, but for a food or automotive company it can be 80%. Hence, we must come together as an industry to have the much needed impact.

5) Talent, Talent, Talent 

Access to talent remains a huge talking point – but now with a twist. Company investments in new geographies are moving from looking at Labor Cost Arbitrage to Skills Arbitrage. In other words, people are asking: Where can I find talent that can leverage digital tools and automation to be more productive?

Let’s get to work

In short, I left Davos with a deep sense of optimism. We have much better clarity on the challenges ahead and what is required from the industry to overcome them. It won’t be easy, and it will require governments and industries working together, but we have a path forward.

We can do this.

Read ‘Destination Davos: Augury At World Economic Forum’s Annual Meeting’. Or reach out if you want to learn more about our mission.

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Sustainability is no longer an elusive concept that competes with traditional metrics of profitability and efficiency, but one that can be measured and achieved by using what you have, far more intelligently. 

This article was originally published in Supply and Demand Chain Executive

Supply chain disruptions and inventory concerns have continued to trouble governments, businesses and consumers worldwide. Even as current supply chain bottlenecks begin to clear up, severe sustainability and supply problems remain due to the amount of waste traditionally produced by retail and manufacturing sectors and the increasingly stringent metrics by which they are judged by investors and consumers.

Moreover, with ongoing geopolitical contention in Europe and Asia, severe inflationary challenges and increased consumer spending amid extreme inflation, the manufacturing and supply chain industries are under pressure to navigate constant obstacles.

The Interconnectedness Of The Supply Chain

It is time to look at the interconnectedness of the supply chain to understand where solutions could reside. Factories, for example, play a prominent role in mitigating a host of supply chain problems and can aid in lowering the impact of inflationary pricing by working more efficiently in several ways. For instance, worn down and inefficient machinery slows production, causing bottlenecks and waste – in both energy and materials.

Furthermore, labor costs increase as more people are brought into the fold to address broken down machinery, while even more money is lost while the factory line pauses production. And inefficiency in machines and processes drives up labor and energy costs in subtle ways ranging from overuse of materials to over maintenance of equipment.

Where Does Sustainability Come into Play?

Oftentimes, efficiency and sustainability are seen as competing interests in operations, but what if there was a way that companies can establish both in their manufacturing processes and support supply chain efficiencies?

A focus on sustainability on the factory floor can reduce scrap and waste (most obviously by lowering costs and increasing yields) while alleviating pressures at other less obvious points in the supply chain. How so? When less materials are needed to create a product, less mining, harvesting and sourcing these materials is required, thus involving less processing, trucking and warehousing and minimizing potential pain points in other areas of the supply chain.

And when machines operate efficiently while producing quality goods, there is also a chance of fewer recalls around issues that occur in the manufacturing process. This, in turn, diminishes the inventory volume of goods traveling back through the supply chain, alleviating another host of problems. And these benefits compound; improvements in quality issues not only boosts sustainability scores but will show up in customer preferences scores as well.

Running manufacturing assets better and more efficiently can help organizations realize their sustainability goals and serve customers better, while easing supply chain pressures ahead of the holiday bloat.

To do so, we must consider machine and process health through a predictive lens.

Machine Health

There are three key components to machine health: mechanical problems, design problems and operational problems. Therefore, every industrial leader must understand how the factory level is performing across these three measurements to ensure production runs smoothly. 

Monitoring for mechanical problems includes monitoring temperature, vibration and magnetic data to identify changes ahead of complete machine failure.

“Running assets more efficiently can also save U.S. manufacturers $3.3 billion in waste caused by downtime, reduce energy consumption by 12% to 15% and avoid up to 6,500 workplace accidents annually.”

Design problems come to the forefront when individual machines undergo extra amounts of stress due to an inefficiently designed production facility. As a result of getting ahead of these issues, facilities can avoid unplanned downtime, delays, bottlenecks and inconsistent product quality, tying back to the efficiencies detailed above. 

Operational problems come into play with the human element. Even with a perfectly designed machine, people make modifications and unknowingly create additional issues.

Continuously monitoring machine health can curtail unplanned downtime and boost productivity to new heights that will be felt throughout the supply chain. Running assets more efficiently can also save U.S. manufacturers $3.3 billion in waste caused by downtime, reduce energy consumption by 12% to 15% and avoid up to 6,500 workplace accidents annually.

But machine health is only half of the equation to solving industry concerns. Process health offers a look into the interconnected inputs and elements of a full production system and other contributing factors, which when misaligned become part of the industry’s sustainability problems.

Process Health

Manufacturing and supply chain leaders are aware of profits left on the table but that does not have to be an accepted standard. There is a critical measurement that can combat inefficiencies and losses. Enter: process health.

“There is an estimated $1 trillion loss due to unplanned downtime in the process industries.”

Process health looks at the ability of a process to realize its objectives or outcomes. In other words, are things running efficiently and effectively? 

According to a report by ARC Strategies, there is an estimated $1 trillion loss due to unplanned downtime in the process industries. In order to bridge the trillion-dollar gap, organizations can unlock productivity by honing in their machine health and optimize production by 40% and improve energy use up to 30%. Those are significant markers!

Process health can help leadership prevent losses from occurring in the future by analyzing data at every step and level of production. It can also identify optimal process settings and establish connections between dynamic and complex variables. It is a no-brainer for industry leaders who want to see significant improvements in quality, throughput, energy and reductions in CO2 emissions and waste.

Big Picture Vision

The supply chain is undoubtedly a complex structure, but one that is the backbone of our economy. While there may not be a one-size-fits-all solution to address the dilemmas of late, repositioning our understanding of the interconnectedness – starting at the factory floor – can illuminate opportunities that may not have been as apparent. 

Continuously monitoring machine and process health can reveal untapped potential. In fact, it is estimated that 10% to 20% of manufacturing capacity is shadow capacity or production capabilities that exist within current manufacturing lines but are going unused. Embracing shadow capacity has positive implications for onshoring, productivity and efficiency. 

As supply chain obstacles continue amid ongoing geopolitical turmoil, fluctuations in consumer spending and a possible recession, it is high time we rethink the relationship between sustainability, manufacturing and the supply chain. Sustainability is no longer an elusive concept that competes with traditional metrics of profitability and efficiency, but one that can be measured and achieved by using what you have, far more intelligently.

To learn more about what Augury’s full-stack prescriptive solutions offer manufacturers, get in touch today.

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