At Augury, we use a rainbow of AI techniques: picking the right AI application for each specific purpose. “It’s all about using the right tool for the right job,” says James Newman, Head of Product and Portfolio Marketing at Augury. “Whether it’s Industrial AI, GenAI, or Causal, they all have particular strengths that can work to make your work easier and more impactful.” 

It’s safe to say that Augury has always been in the Reliable AI business. And happily, we continue to create more tools that are reliable when applied correctly and for the proper use cases. We’ll use any technique to improve our models in real-time. It’s what we do. 

Meanwhile, there’s a push to regulate AI, and many governments already have regulations – or will have them soon. In general, it’s about making emerging AI technologies transparent, explainable, safe, and based on FAIR data. These are all reasonable ideas everyone should aspire – in the name of creating  Trustworthy AI.

Reliable AI – AI that works to produce the proper desired outcomes – is very much part of this vision. And as you all know, in an industry like manufacturing, you cannot afford mistakes in terms of both safety and the bottom line.

State Of The Art Industrial AI – And Beyond

Our so-called bread-and-butter AI is industry-renowned for its ability to predict when a machine will break down – in fact, it’s even guaranteed. Designed for purpose-built solutions, this AI will continue growing with more use cases, capabilities, and new ways of leveraging insight. And, we’ll continue to use our neural networks to do the heavy lifting in terms of in-depth modeling. 

We will also keep experimenting with new and emerging forms of AI. For instance, our recent success with our Machine Health algorithms in applying Continuous Learning, which represents one of the more significant milestones in our quest toward overall expert-level AI, was primarily thanks to the rich – and accurate – training data created by Generative AI.  

“Yes, GenAI has a reputation for hallucinating. But it would be best to remember it’s a tool, not an outcome. Gen AI’s accuracy is 100% based on the model it’s being executed against and the parameters around which it is being controlled.”

GenAI Is Your Friend If It’s Used Right

Yes, GenAI has a reputation for hallucinating. But it would be best to remember it’s a tool, not an outcome. GenAI’s accuracy is 100% based on the model it’s being executed against and the parameters around which it is being controlled. GenAI is not evil. It’s down to the people to control it.

The large language models (LLMs) of GenAI work by sucking up lots of data, learning the patterns, and then working to predict the following pattern – in an often-unknowable way. It’s about answering a question that resembles the answers people usually give. Hence, when it doesn’t have the data to fill in the blanks correctly, it starts hallucinating.

In the case of Continuous Learning, we ensured the LLMs we developed only had access to quality data – namely, the over 500 million hours of Machine Health data taken from over 100 types of machines and dozens of industries. In other words, reliable data begot reliable outcomes.  

“By embedding a GenAI agent into our platform, we are now able to let our users engage with our AI very quickly and in the natural language they prefer – bringing our best-of-class AI to the front row, as it were.”

Complicated But Doable: GenAI As Reliable AI Assistant

It will take time to unfold all of GenAI’s potential and value, and it will take even more time for a high-risk industry like manufacturing that cannot afford to base its decisions on a hallucination. GenAI is still coming fast, but it will require a lot of work underneath it. 

However, one other GenAI use case we will see in the short term is related to how the inner workings of all of Augury’s AIs have been largely hidden from our users. Yes, you are accurately told what machine needs fixing and how to do it within a specific time frame before it becomes a problem. However, the users could generally only dig deeper in a rather manual and cumbersome way. 

By embedding a GenAI agent into our platform, we are now able to let our users engage with our AI very quickly and in the natural language they prefer – bringing our best-of-class AI to the front row, as it were.  

An AI To Help Explain AI 

Naturally, we’re not talking about just throwing ChatGPT at it, which would spark hallucinations and insufficient insights. You need to control the data that ChapGPT is dealing with carefully – and the same goes for any custom LLM we develop.

Either way, this AI agent will help users better understand what’s happening with the AI in the background. Those working on the factory floor can start querying the platform directly for supporting evidence: Why must I look at this machine? What is the metadata? Can I compare the metadata with the metadata of another machine? Has this happened before? Who fixed it and how?

This is where GenAI can shine: engaging with a trustworthy model to give you additional insight. 

“It’s not just about considering how one thing impacts another but also how it affects many different factors and what changes you need to make to get your desired result.”

What Will Causal AI Mean For The Future Of The Factory Floor?

In many ways, Causal AI offers the perfect fit for fully transparent and safe AI. Because it’s all about learning cause-and-effect relationships between different data sets, these Causal AI models are very explainable thanks to their very construction. 

As we aspire towards full Production Health, we can loop in more knowledge models based on domain expertise – combining data sets from maintenance, production, operations, quality, etc. As we bring in these other data sets, we’ll use Causal AI to examine all the cause-and-effect relationships between what we see on the machines and what the system produces. 

In short, it’s about finding true causality rather than just the correlations offered by GenAI. It’s not just about considering how one thing impacts another but also how it affects many different factors and what changes you need to make to get your desired result. 

“In short, Reliable AI is not about a single methodology.”

The Dance Of The AIs – As Choreographed By Humans

Causal AI will be huge for manufacturing. By allowing manufacturers to find relationships they may not have seen before, Causal AI will spark whole new ways of doing things to optimize processes. 

And to help explain these intricacies, a GenAI agent may be looped in to help – but without losing the power of the Industrial AI that forms the backbone of highly accurate, and dare we say it, reliable AI insights. It’s this dance between different technologies that will define the future of manufacturing. 

In short, Reliable AI is not about a single methodology. It’s about using the right combination of methods to provide reliable answers to people in reliability. 


Stay tuned for more exciting Augury AI info! Reach out!

The post Reliable AI: Providing Reliable Insights For Reliability Professionals appeared first on Augury.

Augury’s new R4000-series sensors are already doing what they’re supposed to be doing. However, the real story comes together early next year, according to Augury’s Head of Product and Portfolio Marketing James Newman. That’s when the Cassia X-2000 is deployed as the leading industrial Bluetooth gateway optimized for industrial IoT applications. “With sensor/gateway integration, a whole new IoT chapter can begin: faster, more reliable, more flexible, and able to put AI wherever you need it most. Bring on your edge use cases!”

Life On The Edge

Three years ago, Augury Co-Founder and CPTO Gal Shaul was asked in an interview what emerging technology he believes has the most potential for manufacturing. “I’m really excited about the movement around AI – especially edge AI, which can work at the endpoint and use models as accurately as those using data from a platform. It will enable us to make many new transitions in the market. […] In a few short years, we will be unable to remember how things used to be because it will all be so different.”

For years, edge computing represented the future. Allowing sensor-enabled devices to collect and process data closer to the manufacturing action would enable more AI-led decisions in near real-time, creating a new rainbow of potential use cases to benefit both productivity and those working on the factory floor. But yes, it remained tricky in terms of issues such as security concerns, scalability, and sheer complexity. 

Until now. Now, it’s payback time.

Our new Machine Health sensing platform can now run AI via our new Halo R4000 series sensors, the upcoming Cassia X2000 Enterprise Bluetooth IOT Gateway, and, of course, as we’ve done traditionally, the Cloud. With our wholly new IoT, we are now experimenting with customers to figure out what works best to double down on increasing value.

In other words, welcome to the world of Machine Health 2.0 – where the long-vaunted potential of edge computing can finally reach fruition.   

“AI-powered end-to-end condition monitoring solution designed for cost-effective monitoring at scale with maximum flexibility.” Read the full press release.

Big Story: Rugged, Future-Proof Sensor

The new Halo R4000 series is the world’s first Edge AI-capable Machine Health sensor. As our most miniature industrial-grade sensor yet, the R4000-series features longer battery life, smart and dynamic diagnostics, self-healing connectivity, and wet environment protection – it’s ready to cover any asset that matters, anywhere.

Thanks to the upcoming HexaLock sensor mounting system, designed for greenfield and brownfield environments, the sensors are easier to install and maintain, eliminating some of the challenges of other designs.

One of the main benefits of the R4000 sensor is increased flexibility, in terms of costs, capabilities, and scaling.

Flexibility In Use – And Costs

One of the main benefits of the R4000 sensor is increased flexibility, in terms of costs, capabilities, and scaling.

You’ll naturally still want the full Cloud-backed coverage for your critical assets. This enables deep and descriptive diagnostics and provides the raw data that helps our vibration analysts truly understand what’s going on with a particular machine. However, the sensor chip can now also process this data more efficiently before sending it to the Cloud, thereby saving bandwidth and transmission costs. 

However, in terms of headline news, the chip will also let you run sophisticated AI models on the edge for less critical assets to provide actionable insights, such as basic anomaly detection – helping customers unlock cost-effective total plant coverage. 

Thanks to collaboration with various partners and early adopters, we have solved this IoT connectivity problem.

Bigger Story: New IoT 

All these new innovations – the sensor, the HexaLock, and the Cassia X2000 Enterprise Bluetooth IOT Gateway – means new IoT. 

We all know working with Internet of Things technologies isn’t always easy – too many things can go wrong between reading the data and getting it to the Cloud, where the more in-depth AI magic can happen. Thanks to collaboration with various partners and early adopters, we have solved this IoT connectivity problem.

For instance, the gateway can apply AI for specific value-added applications, such as auto lubrication.

Opening The Innovation Floodgates

Due for general implementation in early 2025, the Cassia gateway is currently being tested in the field with customers. Significantly, and thanks to the increased efficiency of the overall system, we can further increase the number of sensors to 40 per gateway – more than twice what we could do previously.

The gateway’s ability to cover a much wider range will also help many scenarios, not least of which is safety – particularly in harder-to-reach or environmentally restrictive areas where it’s best to minimize human-machine interaction. 

You’ll also be able to run custom firmware from the gateway itself. For instance, the gateway can apply AI for specific value-added applications, such as auto lubrication.

Can you tell we’re excited? The time has truly arrived to make a difference. Are you ready to double-down with us.

Do you have a use case that might benefit from AI on the edge? Reach out! Let’s talk!
Or first, check out the full press release.

The post Finally… The World’s First Edge-AI Native Machine Health Sensing Platform appeared first on Augury.

We have a remarkable number of happy long-term customers. Most stay for the same reason they signed up: being free of unplanned downtime. But there’s more, according to James Newman, Augury’s Head of Product and Portfolio Marketing. “It’s about reducing risk, elevating reliability, and continuing to fight the good fight for continual improvement.”

 

At Augury, we’re incredibly proud that our customer retention rate is currently 97.6%. We’re perhaps even prouder that our net dollar retention (NDR) rate is 130% – which means not only do people stay with Augury, but they spend an average of 130% more with Augury every year as they expand with us.

In other words, unlike Hotel California, it’s not that you can’t ever leave, it’s that you won’t ever want to. And there’s one big reason for this: value, which begins with the elimination of downtime. 

In most cases, we eliminate unplanned downtime in one or two years. And once you’ve achieved that, you’d never dream of returning to how it was before. However, you can begin to imagine what comes next. 

Yes, It’s The Reliable AI

We track this progress on our platform, repeatedly showing how sites and organizations eliminate the endless firefighting around unplanned downtime. When we began, this was the big problem of manufacturing we wanted to solve. And its solution brought people to Augury. 

But now that the problem is solved, why not eliminate Augury?

It’s because of what Augury does for a company’s workforce, processes, and operations. Customer after customer and plant person after plant person says, “I can’t imagine working without Augury. Every day, I walk in and decide what I should focus on based on what Augury tells me. It alerts me to a problem. It also tells me what’s not a problem.” 

Solving The Problems That Need To Be Solved When They Need To Be Solved

Hence, the sustaining value is the assurance that Augury will tell you how to spend your time on what needs your time the most. No one can imagine going back to that level of uncertainty they had before – which would probably be heightened now in an age of continued labor and expertise shortages. After all, companies are all about mitigating risk. Why would you put your plant at risk?

So, Augury offers reliability and risk reduction. And this used to be about having less unplanned downtime. Now, it’s about the reliability of having your people do the right things at the right time. 

Certainly, Our People Are Also Valued

It might be pushing to say we get paid because of our nice and supportive people, but our people are certainly valued! Just like with tech, it’s about having a relationship that you can grow, trust and count on. 

“She is a machine whisperer who can tell what’s wrong with our equipment from hundreds of miles away – while my technicians and I think everything is perfect.”

Recently, a plant manager from a food and drink manufacturer reached out to say how happy he was with our Team Lead for Reliability Success. He admitted he was initially highly skeptical of our solution and was “just waiting for Augury to be wrong.” But in the end, he was proven wrong. Our lead pushed him to act on our alerts, and she was proven right twice in a short period.

1)     “She called out bearing wear, and we reluctantly pulled the motor and sent it to a shop to inspect it. We gave them zero instructions on what to look for. The shop identified that very same bearing as problematic.”

2)     “Later, she pushed for weeks on an alignment issue, and during a stoppage, the maintenance manager pulled the guards and checked it with a straight edge. He confirmed Augury’s alert and made the repair.”

The manager said, “She is a machine whisperer who can tell what’s wrong with our equipment from hundreds of miles away – while my technicians and I think everything is perfect.”

Stories like this motivate many of our customers to say our people are just as important as our technology. I’d say it’s more about the combined relationship between our tech, our people, and those on your floor.  

But There’s More! How About Taking Continuous Improvement Beyond Assets? How About Optimizing Your Planned Maintenance Scheduling?

There often comes a point around continuous improvement when something seems as good as it can get – for instance, when you have put all your rotating machines into a real Machine Health Solution. In other words, the firefighting work is done. But actually, that moment really represents the beginning of your continuous improvement journey. In other words, it’s now time to focus your efforts on where they will have more impact. 

If it doesn’t break, try it across several machines. And once you’re sure it’s not an outlier, start looking holistically across your enterprise. How much are you saving now?

For instance, it might be time to change your planned maintenance schedule. Since the Augury system tells you when something doesn’t need to be fixed, why would you do maintenance on it every three months? Perhaps you can take that from a three-month cycle to a five-month or maybe even a 10-month cycle.

If you do push an asset to the breaking point, Augury’s AI will warn you to jump in. So why not let that machine go an extra two months? If it doesn’t break, try it across several machines. And once you’re sure it’s not an outlier, start looking holistically across your enterprise. How much are you saving now?

When you continually push the envelope in minimizing unnecessary maintenance, you might come across exceptions: instead of doing your maintenance every three months, you might look at the data and decide to do it every three weeks. But that’s okay. You will not only still save money overall, but you’ll also have better-prepared machines overall. 

It also puts a lot of power in the hands of Machine Health customers to not just stop failure but to make everything better.

And Why Not Extend The Life Of Your Assets?

Once you’ve optimized the operation and maintenance of your machines and they’re all running in the green all the time, you can follow the same principles to extend asset life. After all, if their performance isn’t degrading, why replace them? Yes, your OEM might say you should replace them every 12 years. But the data might tell you you can quickly push it to 15 years. Why not defer that cost for three years and make some free profit off that machine in that time?

Yes, this is very much a long-term play. However, with continual improvement now possible and trustable, it’s a play that’s actually executable. It also puts a lot of power in the hands of Machine Health customers to not just stop failure but to make everything better. And that power might go a long way in explaining why we have so many long-term customers.

Learn more, reach out. Or maybe you want to read this first: ‘How Do You Measure Success Once You Beat Unplanned Downtime?’

The post Why Do Customers Stay – And Grow – With Augury? appeared first on Augury.

A survey of 500 APM practitioners reflects how more manufacturers recognize the business benefits of technologies like predictive maintenance (PdM) and the Industrial Internet of Things (IIoT) – and how these benefits will only amplify with AI enhancements. However, the report also comes with a warning: there needs to be more focus on increasing employee satisfaction.

The leading technology research and advisory firm ARC Advisory Group published the report ‘Advanced Asset Performance Management and Its Impact on The Workforce’. Based on an in-depth survey of over 500 end users from various industries in North America and Europe who follow an advanced Asset Performance Management (APM) program, the report contains many relevant recommendations for tracking key metrics, managing expectations around ROI, and scaling. 

However, the report’s key insights relate more to employee satisfaction and how embracing AI seems like the next logical step in continual improvement.

“About 90 percent of the respondents indicated that since the adoption of advanced PdM programs, they were able to add more assets to their asset management programs.” 

A Solid Business Investment – One That Keeps Giving

According to the report, the three top reasons for investing in an advanced APM solution are: 

1.  Improve maintenance practices
2.  Reduce safety incidents
3.  Improve employee job satisfaction

And happily, “the majority of survey respondents indicated that they are able to bring in continuous improvements to their asset management processes and practices as they have adopted advanced PdM practices. About 90 percent of the respondents indicated that since the adoption of advanced PdM programs, they were able to add more assets to their asset management programs.” 

“The one area that clearly needs attention is around employee satisfaction, where a greater number of participants indicated that the benefits were not realized. The same is true for employee retention.”

There Are Only Losers With Employee Dissatisfaction

“While business benefits are very well recognized, what remains to be understood is the impact of advanced APM technology adoption on the industrial workforce,” according to the report. 

“The one area that clearly needs attention is around employee satisfaction, where a greater number of participants indicated that the benefits were not realized. The same is true for employee retention.”

Hence, manufacturers need to examine APM programs more closely from an employee perspective and ensure these align more with employee needs. After all, in an industry already finding it hard to attract and retain talent, there are only losers when it comes to dissatisfied employees. Turnover can, in turn, lead to not only increased recruiting and training costs but also increased downtime and decreased production.  

“Many manufacturers recognized how AI-driven tools can be deployed to increase employee satisfaction through training and retention and skillset expansion. The use of AI can even work to attract talent.”

Can AI Provide More Than Purely Business Benefits?

Now, back to the good news. “AI is another key technology that will have a significant impact on how we manage our assets. Among a list of key areas that AI can impact, survey respondents felt process optimization and PdM benefit significantly with AI enhancements,” notes the report.

Many manufacturers recognized how AI-driven tools can be deployed to increase employee satisfaction through training and retention and skillset expansion. The use of AI can even work to attract talent.  

However, almost half of the respondents saw that the most significant potential for AI was process optimization. “With this asset management focused survey, it was interesting to see process optimization at the top of the list. This highlights the ongoing trend of Process Health and Machine Health coming together. As APM becomes closely tied with business goals, asset management professionals are also thinking about process optimization opportunities.”

Meanwhile: “As PdM becomes more effective, affordable, and easier to implement, end users are able to expand their PdM programs, this not only ensures better and comprehensive asset care but also simplifies asset maintenance and offers a helping hand for employees.”

In short: all this investment is great and will benefit the organization, but let’s not forget the human part. We must make sure that we aren’t just optimizing processes but also optimizing how we help our people become the best they can be. That’s when we will create a true win-win.

Read the full report: ‘Advanced Asset Performance Management and Its Impact on The Workforce’.

The post Report: While AI Continues To Excite, More Focus Is Needed On Employee Satisfaction appeared first on Augury.

The newly released ‘2024 Machine Health Is Business Health’ report reflects how manufacturers increasingly recognize the benefits of adopting tech solutions, though C-Suite and plant-level staff perspectives diverge on several fronts. 

“Manufacturers continue to focus on critical asset reliability and finding technologies that can help,” according to the new ‘2024 Machine Health Is Business Health’ report. “Workforce concerns still rank among the top challenges, but signs of optimism indicate progress is felt in the back office and on plant sites.”

In other words, the technologies have proven their worth, and now it’s time to embrace them even more – and by more people. 

Download report: ‘2024 Machine Health Is Business Health’.  

Bringing People and Culture Up to Speed

For this third annual Augury report, research partner Endeavour Business Intelligence surveyed 224 corporate and plant-floor managers who are members of the Plant Services database. The wide-ranging industries span the energy, utilities, process manufacturing, and discrete manufacturing sectors. Most companies have 1-5 manufacturing facilities (65%), while 18% have more than 20 manufacturing facilities (18%).

The report builds on last year’s ‘2023 Machine Health Is Business Health’ findings, which concluded: “Manufacturing leaders faced with workforce and economic challenges are leveraging advanced monitoring technologies to manage plant health.” 

Efficiency Is Up But Workforce Concerns Remain

Certainly, the central message of the 2024 report remains the embracing and scaling of tech solutions that address specific challenges. Yet, there have still been some significant shifts. For instance, the need for upskilling has surpassed downtime as a primary concern for plant-level respondents.

“While supply chain disruptions are the leading challenge from both the corporate and plant perspectives, workforce shortages and skills gaps are the second- and third-ranked challenges for plant respondents, surpassing even unplanned production downtime by a significant margin. These two workforce challenges also rank relatively high among corporate respondents, sharing fifth place.”

“The need for upskilling has surpassed downtime as a primary concern for plant-level respondents.”

It’s also interesting to note other differences between corporate and plant responses. “For instance, the front line and back office moved farther apart on the challenge of adopting new technology, which jumped from 11% to 29% for corporate respondents but was relatively flat for plant respondents year over year.”

Prescriptive Maintenance Taking Hold

One particularly positive shift is the increasing use of proactive maintenance, with prescriptive maintenance – which offers real-time predictions on degrading assets – entering the report as a measured value for the first time. 

“Surprisingly, corporate respondents who report having the ability to visualize the real-time condition of critical assets across all sites fell to 36% in 2024, from 48% in 2023. This appears to be a disconnect with the plant point of view. […] 85% of plant respondents this year report the ability to respond well, moderately well, or extremely well to real-time changes in asset conditions.”

“One explanation could be that the more technology is adopted, the more detached the corporate and plant teams become. Another possibility is that some corporate respondents with centralized, personalized, at-a-glance business metrics are prioritizing other metrics above cross-site, real-time critical asset conditions, which would be unfortunate.”

After all: “As more prescriptive solutions become available and more plants leverage the technology, the industry as a whole will gain from its value.” 

“There are generational advances happening in technology, and more industrial companies should be reimagining and transforming how their plants run.”

Optimism In The Air

All in all, the report reflects increased optimism: “The combination of artificial intelligence (AI) solutions, Internet of Things (IoT) sensors, and reliability expertise holds the key to overcoming multiple roadblocks and challenges, from workforce gaps and unplanned downtime to asset data collection.”

But yes, challenges remain: “Manufacturers should be eyeing strategies that leverage those same tools and setting ambitious goals around supply chain management, tech adoption, upskilling, and other areas. There are generational advances happening in technology, and more industrial companies should be reimagining and transforming how their plants run.”

In other words, there’s still plenty of work to do – both in the boardroom and the factory floor.


Download report: ‘2024 Machine Health Is Business Health’.

The post Report: Workforce Is Central as Tech Adoption Continues to Flourish appeared first on Augury.

Augury’s AI has merged with Baker Hughes’ robust Ranger Pro sensor to create an unparalleled diagnostic solution for hazardous environments. “This collaboration not only delivers immediate customer value but it changed how both companies work,” writes James Newman, Augury’s Head of Product and Portfolio Marketing. “But there’s more! It also opens up exciting new possibilities for third-party technology integration into Augury’s platform – that can, in turn, work to rewire the entire manufacturing ecosystem.”

Tech Breakthrough

“When we first conceived this alliance, we aimed to combine our best-in-class hardware and infrastructure with Augury’s exceptional sensor-based AI and machine learning,” said Carlos M. Gomez, VP of Global Partnership & Alliances at global energy giant Baker Hughes during Augury’s recent ‘Beyond the Line’ event. “And the result has far exceeded our initial expectations.”

This collaboration integrated Baker Hughes’ sixth-generation Ranger Pro Wireless Condition Monitoring Sensor and Cordant Gateway with Augury’s Machine Health platform. In other words, our Guaranteed Diagnostics AI can now be applied to maintain machinery in hazardous conditions typical of heavy industries like oil fields and refineries, where safety and environmental resilience are critical.

This is good news for many – and for many reasons. 

“This co-developed solution showcases how innovation-driven companies of different sizes and capabilities can collaborate successfully.”

Changing The Way We All Work

Baker Hughes brings formidable technology to the table. With over 50,000 sensors deployed in high-risk areas, the Ranger Pro boasts the maximum hazardous environment rating (C1D1 / ATEX High) and can transmit data over a remarkable 150-meter line of sight. Their IoT network supports between 40 to 60 sensors per Cordant Gateway, significantly expanding Augury’s sensing capabilities and making it easier than ever to deploy at scale.

This co-developed solution showcases how innovation-driven companies of different sizes and capabilities can collaborate successfully. The partnership has also changed how both companies work.

Impact: Success Out of the Gate

The co-developed solution has already made a huge impact with Augury’s customers. In less than two months since announcing the availability of Machine Health for hazardous environments with Ranger Pro, Augury has seen significant demand from customers from the chemicals and building materials industries – notching up 3-7X ROI at existing installations.  

As our CEO Saar Yoskovitz expressed it: “Our customers know and understand the challenges of monitoring highly critical machines in hazardous environments. They rely and trust on Baker Hughes’s expertise and Augury’s technology to protect their machines and their plants from expensive unplanned downtime. It became instantly clear that this is the solution for them.” 

“That’s a true SaaS model of digital technology: to basically embrace your customer and say, I am not only delivering you something incredible, but I am going to actively help you get there in terms of demonstrating value and ROI.”

In the Name of Customer-Centricity

Carlos was lyrical in how he saw a legacy company like Baker Hughes embrace a new way of working that put the customer at the center. 

“I can see what the customer’s doing. They can see how we’re helping them. And together, we’re creating value together. It’s a whole different dynamic. And that’s a true SaaS model of digital technology: to basically embrace your customer and say, I am not only delivering you something incredible, but I am going to actively help you get there in terms of demonstrating value and ROI,” Carlos said during ‘Beyond the Line’.

“This experience has gotten us even closer to our customers.” 

“This new way of working can also contribute to rebuilding the manufacturing ecosystem from the ground up, with best-in-class technologies integrated into a single platform to support customer choice and maximize coverage.”

From Partnership To Ecosystem

The partnership certainly has transformative implications for customers in vertical markets like energy and for existing Augury customers who now have access to the highest level of hazardous coverage. It’s a big step for Augury, increasing the global reach of Machine Health and helping the industry scale it in new ways.

Specifically, it represents the first time Augury’s AI has been integrated with a third-party sensor, opening up new possibilities for future innovations. In fact, this new way of working can also contribute to rebuilding the manufacturing ecosystem from the ground up, with best-in-class technologies integrated into a single platform to support customer choice and maximize coverage. 

Works With Augury 

This project also aligns with Augury’s strategy to extend its IoT infrastructure through the “Works with Augury” program. This program enables leading IoT and application providers in the Production Health ecosystem to provide faster and higher-value services to manufacturers worldwide.

This lays the groundwork for the connected digital infrastructure needed for an AI-driven Production Health future.  

“We can both go to our customers and offer them more value. This is probably what folks in the alliance world wish could happen every time.”

It’s Only Just Begun

As Carlos said, “You always want the alliance to transcend and evolve from what we designed it to be upfront to what it could be later on down the road. And I think we’ve achieved that. We can both go to our customers and offer them more value. This is probably what folks in the alliance world wish could happen every time.”

And as our VP of Strategic Alliances, Mercer Rowe, said during the same conversations, “Watch this space: there’s a lot more to come from this exciting partnership.”

Time to put on our seatbelts.


Learn more about this partnership and the evolving manufacturing ecosystem by watching ‘Beyond the Line’, or reach out for a demo.  

The post Augury & Baker Hughes: Magic Happens When You Work Together appeared first on Augury.

Augury’s recent ‘Beyond the Line’ event showcased how the company’s tagline ‘Predicting A Better Future’ is now a self-fulfilling prophecy, writes James Newman, Augury’s Head of Product and Portfolio Marketing. “We are building what manufacturers need to create a better future. And with four core elements coming together, manufacturers can enter that future today.” 

Self-Fulfilling Prophecy

We unveiled our new Production Health blueprint during our recent ‘Beyond the Line’ event – showing how manufacturers are at a watershed moment in optimizing their production goals. In short, Augury, buoyed by its tagline “Predicting A Better Future,” is already building what manufacturers need to make this better future happen. 

Yes, it remains a work in progress – as any journey of continual improvement should be – but it’s already one offering value to our customers. Four core elements are now coming together that will transform our industry as manufacturers gain more control over achieving their goals.

1)    Machine Health 2.0
2)   Process Navigator
3)   Fusion Diagnostics
4)   Ecosystem

1) Machine Health 2.0 (The Ever-Evolving Foundation)

The blueprint builds on our long-established foundation of Machine Health. Augury has built its business and reputation on making unplanned downtime a thing of the past for our clients. While Machine Health is the foundation for everything that follows, it continues to become broader and deeper. For instance, we can now speak confidently about Machine Health 2.0 as we continue to make advances in infrastructure, improved IoT, and next-generation AI.  

2) Process Navigator (Looping In Clear Prescriptive Insights For Operations)

With precise and real-time actionable insights into the state of your machines, the next logical step is to have the same clarity and control over your Process Health. Our Process Navigator offers dynamic real-time simulation you can use to optimize your operations – and then change when needed. 

During the ‘Beyond the Line’ event, a comparison was made to the history of navigation. Too many manufacturers still rely on “paper maps” to negotiate their processes. But now we’ve gone beyond paper maps and even static GPS routes. We have achieved a Google Maps level of navigation for both machines and the processes: the ability to provide turn-by-turn instructions that adapt to “traffic conditions” and can be calibrated for one’s particular needs – be it speed, energy efficiency, or both. Indeed, you are now able to adjust your production process for multiple objectives.

The next step is supervised self-driving processes. (Tune in next year.) 

It allows us to know how processes are affecting machines and how machines are affecting processes – and not in retrospect, but in real-time.

3) Fusion Diagnostics (Breaking Down The Wall Between Maintenance & Operations)

It may sound fancy, but Fusion Diagnostics does what it says. It’s the connective tissue that allows the tearing down of the wall between maintenance and operations – call it a sledgehammer or a wrecking ball. Call it whatever you want. But it’s the unification we always needed. It allows us to know how processes are affecting machines and how machines are affecting processes – and not in retrospect, but in real-time.

With Machine Health, we already had turn-by-turn instructions on what to do about your machines. With the launch of Process Navigator for Process Health, you now have turn-by-turn instructions on what to do about your processes. And now, Fusion Diagnostics brings machines and processes together – which is entirely different from the two silos they live in today. We are bringing in two vast and complex data sets that AI can use to turn new and previously unseen connections into actionable insights with turn-by-turn instructions that impact the entire organization collectively and not in isolation.

Fusion Diagnostics reconnects all the teams that should have been connected from the beginning – giving them the insights that matter to both: optimizing production.

Do you want to manage your energy use? Go ahead. Do you want to manage waste to meet your sustainability goals? Go for it. 

Thanks to real-time operator-driven actions that respond to changing needs, every shift can deliver its best work. After all, your best route today might not be your best route tomorrow.   

“Unlike in Middle Earth, there isn’t, and there will never be, a single app or platform to rule them all. It’s only by the combined efforts that we will complete this vision of creating a better future.”

4) Ecosystem (No Solution Is An Island)

To attain that better future, you need to realize you can’t do it alone. No one can afford to be an island anymore. And now, with large partners in the ecosystem, we can offer customers more expanded capabilities much sooner than we dreamed of – whether that’s better synching capabilities with Baker Hughes, simplified technology stacks with Schneider Electric, or changing how you manage your assets with IFS Ultimo. 

And there’s so much more potential and partners we are – and will be – tapping into. Whether it’s automating parts-as-a-service or keeping your assets adequately lubricated, the sky is the limit. And it’s impossible to build all these possibilities ourselves. And certainly, it does not best serve our customers. Yes, we will stay focused on building the central capability set that drives value – see above – but meanwhile, we can also leverage entirely new ways of working – thanks to being part of a larger ecosystem.

To put it in another way (and with apologies to JRR Tolkien fans): Unlike in Middle Earth, there isn’t, and there will never be, a single app or platform to rule them all. It’s only by the combined efforts that we will complete this vision of creating a better future. 

A diverse and robust ecosystem will also allow your technologies to be as connected as your teams need to be. Looping in additional data sources will inspire yet more innovation through new techniques and AI capabilities. 

This is why the blueprint for full Production Health will never be finished. This is a house that will only keep growing.   

Conclusion: Upward and Onward

There will always be people who say, “Wouldn’t that be nice?” We can now say, “It’s already nice.” We are making that prophecy of a better future come true: not in three or ten years or Sunday, but in real-time. Now. The building blocks are now in place.

This doesn’t mean we’re done. There are lots of things to come. But for the first time, the vision is not just a wish but a reality.

Learn how to break efficiency barriers with an ever-evolving Production Health blueprint.
Or cut to the chase by reading the ‘Your Production Health Blueprint‘ one-pager.

Read Part 1 of Beyond The Line: ‘The Manufacturer’s Nightmare’
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‘.

The post The Better Future We Predicted Starts Right Now appeared first on Augury.

Too many manufacturers are still dragging their feet on going digital by using a variety of excuses: insufficient skilled labor, leadership churn, too mom-and-pop, contrasting maturity levels across sites, etcetera. However, the digital success story Indorama took these types of excuses as reasons to embrace an AI-driven solution. “It’s about flipping perspectives,” writes James Newman, Augury’s Head of Product and Portfolio Marketing. “Why think digital is too far off when it can tell you where to focus right now?”  

There Will Be No Happy Ending Without Digital

As always, the NAMES conference was inspirational. So, I was surprised I still had too many conversations with manufacturers holding back on digital solutions – even when they knew these could bring significant value. 

Without exception, they were bogged down by a myth and often several myths: that they are still too mom-and-pop, that their organization is already going through too much flux, that they don’t have the people to make it happen, etcetera. Meanwhile, they offered these kinds of excuses while they also happened to be the country’s largest producer of such-and-such a product!

Well, they won’t be the largest producer of such-and-such for long since their AI-embracing competitors will squeeze them out soon enough.

[Full disclosure: these conversations make me grumpy.] 

It was about a company that recognized its challenges, flipped some perspectives, found the solution that fit it best, and then went on to enjoy success. It is currently scaling across its portfolio.

Why Not Go Digital?

Happily, I was part of the fireside chat ‘Overcome Uncertain Times – Digitally Enabled Transformation to Drive Business and Workforce Success’, which told the other side of the story. It was about a company that recognized its challenges, flipped some perspectives, found the solution that fit it best, and then went on to enjoy success. It is currently scaling across its portfolio. 

Failing To Take Off

Srinivasan “Shankar” Prabhushankar is the CTO for Recycling at Indorama Ventures, a global chemicals manufacturing company and the world’s largest producer of PET resins. The $20 billion company has about 140 manufacturing sites in about 40-plus countries on all six continents and about 15 recycling sites where PET material is recycled back into pellets that can be used to make more packaging. 

Shankar explained how the company long faced a Sisyphus situation: pushing another tech solution up the cliff of employee indifference only to see it roll back down. Each time, they couldn’t get people to adopt, and they couldn’t figure out why. “We knew there had to be a better solution,” says Shankar. And to his credit, he sat down with the company’s digital team to determine what that solution should look like. 

Defining The Problem

“The major thing was that our operating rates were so low that we were constantly reactive – fighting whatever fire came up. We needed immediate help. So, the system had to be simple to implement – and not take months to install,” says Shankar.

“The second thing is we did not have strong site leadership teams in the maintenance department. There was a lot of churn. So, the solution needed to be quick to learn not just by the plant floor but also their supporters in C-Suite. The solution should also ideally be backed by a vendor’s Customer Success team to also help drive our engagement. Those were my main concerns,” says Shankar. “And our digital team had their own criteria: that we needed a collaborative, adaptable platform with an architecture that’s easy to scale.”

Machine Health fit the bill. The impact on the initial site in Dallas was almost immediate. Over six months, they saw a 17% improvement in the unscheduled downtime. “And over the course of 9 to 10 months, we calculated $452,000 costs saved – about a 13 times ROI,” says Shankar. Meanwhile, over the last year, the response time has gone from an average of three days to 1.3 days, and the response rate has gone from 87% to 97.4%.  

In other words, they turned what some people use as excuses into measurable wins. 

The Dallas site experienced an almost complete change in on-site leadership. Meanwhile, the operators who became part of the reliability team had no background in reliability. Yet it worked.

Flipping Perspectives 

1) Your Worst Site Likely Has The Most To Gain

We know the more prominent manufacturers often tout their lighthouse factories as leading the way toward a digital future. Why not flip this idea and test your potential solution on your worst site? Indeed, Indorama’s pilot site in Dallas was rated as one of their worst-performing sites, with no predictive maintenance system, lots of unplanned downtime, and various labor and leadership turbulence. 

“I’d call this our key learning: if we could drive results with such strong ROI with our least reliable site, and one which was experiencing significant turnover, then any other site with significant opportunity should be able to succeed as well.”

This turned out to be true. “The digital solution also works on our more reliable sites,” says Shankar. “Our reliability engineers there said it causes them to watch assets more closely and improve as an engineering team.”  

2) In Times Of Flux, You Can Still Succeed

As mentioned, the Dallas site experienced an almost complete change in on-site leadership. Meanwhile, the operators who became part of the reliability team had no background in reliability. Yet it worked.

So how did they achieve 13x ROI despite these handicaps?

According to Shankar, it was thanks to a perfect triple play. As personified by Shankar, the executive level of the organization provided top-down support and oversaw the change management. It was essential that they stayed committed to solving the problem. In fact, Shankar himself learned to use the system to help his sites succeed – which is in fact rather uncommon. 

Meanwhile: “You also have to recognize the importance that key roles and people have played on the plant floor,” says Shankar. “Our Regional Industrial Manager, Rich Hill, helped select assets for the pilot and evaluate and quantify benefits for the many catches at IVSR to validate the system for expansion. He has also helped select expansion assets and drive engagement.”

Then there was the system itself: the Machine Health platform telling the team where to go and what to fix. In other words, they could get their work done despite all the churn above them. Our vibration analysts and Customer Success Team were also on hand to help with any bumps on the road. 

 “So, our goal is to bring it all together in a cohesive way – first across a site and now across sites.”

3) Digital Is Never Out Of Reach. It Can Help You Focus – And Scale

Once you settle in on a system that identifies and prioritizes what you need to deal with to keep your line running efficiently, you can build up the expertise and experience you need to improve continually into the future. And while you build cohesion in a single site you can also build cohesion across sites as you scale. 

“About 85% of Indorama’s assets are acquired through mergers and acquisitions – so we have sites with different maturity levels,” notes Shankar. “And in the recycling industry, these are mainly mom-and-pop shops, without any level of systematic approach to manufacturing. So, it’s sometimes difficult to adapt their culture and integrate that part of that business with the rest of Indorama,” says Shankar. “Our goal is to bring it all together in a cohesive way – first across a site and now across sites.”

So, no excuses, and listen to Shankar: onward and upward!

[One final full disclosure: I am in a much better mood now.]

Watch the whole fireside chat: ‘Overcome Uncertain Times – Digitally Enabled Transformation to Drive Business and Workforce Success’.

The post How To Embrace Purpose-Built AI: Turn Your Excuses Into Reasons To Go For It appeared first on Augury.

What happens when your machines stay fit, and all downtime is planned? It’s time to scale your ambitions around Machine Health by aligning with Process Health. And as step one, you will need a shared source of data-driven truth for your maintenance and operations teams to unite behind. Welcome to Machine Health 2.0 – when the Lean dream finally comes true.

Always Aiming For A Bigger Picture

Unplanned downtime was always the Achilles heel for manufacturing in terms of both safety and business costs – and remains so for many companies. In fact, it may have only gotten worse for some. Tangled supply chains can now have you waiting 12 to 14 weeks for a spare part – a situation few can afford.

Helping manufacturers avoid downtime was our main pitch for a long time. But now, with our more mature customers experiencing limited downtime, we are in a position to promise more – while still building on that Machine Health foundation. 

In other words, the Machine Health you enjoy today, shouldn’t be the Machine Health you enjoy tomorrow. You should always aim to expand your view to get a bigger, data-driven picture of the world around you. 

Recently, I wrote ‘How Do You Measure Success Once You Beat Unplanned Downtime?’, which was about measuring value beyond that always essential metric ROI. Now, I’d like to build out on that to explain the next steps once you have a healthy Machine Health program and want to take the next steps toward full Production Health.  

Naturally, the ultimate goal would be understanding the full interplay between machines and processes to help you decide how to run your business best.

Understanding The Impact Of Process On Your Assets

On a simple level, there’s always work to be done. Regarding coverage, there are always new machines, components, diagnostic methods, use cases, and environments to contend with. Similarly, in terms of insights and engagement, you can always work to expand your machine diagnostic capabilities, insight accuracy, expertise, and useability. Certainly, we can also work to improve infrastructure in terms of IoT resilience, auto-recovery, serviceability, and scalability. 

Meanwhile, you can also start looking at the next order of magnitude problem. For instance, how do the processes affect the machines? For example, if I changed formulas, do I see issues arise around the behavior of the bearings and the pumps? And conversely, are the machines having an impact on the processes?

Naturally, the ultimate goal would be understanding the full interplay between machines and processes to help you decide how to run your business best. This end goal is what we call Production Health – and we fully plan to get there one step at a time. 

“Mr. Gorbachev, Tear Down This Wall!”
(AKA Getting Everyone On The Same Page)

The first step is to erase that pesky ampersand between Maintenance & Operations. This ampersand represents a huge wall, which heavily influences how people communicate and run their businesses. And, the goal of Machine Health 2.0 is to ensure that this wall gets torn down and stays down.

We need everyone to stare at the same screen – a screen that unifies all views. We must be able to see how machines and processes influence each other in real-time. And we need to do this together. We need the maintenance and operations teams to collaborate around common insights. 

Only with such a system in place can we aim our ambitions even higher towards full Production Health. 

Yet, even in the best organizations, the operations and maintenance teams often work at odds with each other. And this is largely because they are looking at different dashboards.

Like TPM, But Different 

Of course, removing the ampersand is not a new concept. TPM (Total Productive Maintenance) has always had it right, as do all its permutations, whether TPS, Lean, or Six Sigma. These disciplines embrace the idea of continual improvement and aspire for better decision-making based on a holistic view brought on by breaking down silos. They also recognize that it’s both a technological journey and a people’s journey. 

TPM is the team we belong to. 

Yet, even in the best organizations, the operations and maintenance teams often work at odds with each other. And this is largely because they are looking at different dashboards. The data – as well as the context – is not aligned. Hence, the drive to efficiency – and the ability to make ultimately effective decisions – hits a wall.  

So let’s get everyone on the same page and talking to each other – machines-talking-to-processes, people-talking-with-people.

Making TPM Come True: A Single Source Of Truth

I’d argue the noble goals behind TPM were slowed by technology. As a result, manufacturers could only go so far. The data has been too disjointed and disconnected for them to get the full view. 

And that’s what we are now able to change. We can bring the different streams of once isolated – or even non-existent – data and get it on a single screen for a single team to really see how assets and processes interact. After all, a shared context is a shared reality – and one on which you can work together on continual improvement. 

So let’s get everyone on the same page and talking to each other – machines-talking-to-processes, people-talking-with-people. In that way, people can tweak the machines and the processes for the best possible outcomes.

Ready for the next era of efficiency?

• Register for our event

The post Machine Health 2.0: Tearing Down The Wall Between Maintenance & Operations appeared first on Augury.

ROI is an important metric. However, according to James Newman, Augury’s Head of Product and Portfolio Marketing, it doesn’t tell the whole story. Once you’ve made all downtime planned, you need to go beyond ROI – and Machine Health – to measure value. 

Mea Culpa

It’s our fault, really, that some clients come to question our value. 

We deliver on our promise to make unplanned downtime obsolete – thanks to the alignment between our tech and those working on the plant floor, taking our advice and doing the actual maintenance. 

We prove ourselves with a fast and vast return on investment. In fact, we just upgraded our Value Calculator, which shows potential customers how much time and money they can save with Augury’s Machine Health solution. Indeed, ROI remains a bottom line that cannot lie. After all, every procurement and financial department love these happily crunchable numbers across time and space. 

A Proven Worth

And, of course, we’ll be sticking to our promise of eliminating unplanned downtime. It remains the Achilles’ heel of manufacturing in terms of both costs and safety.  

It’s only become more relevant with continued supply chain challenges – waiting months for a single essential spare part can devastate your business. And then there’s the workforce shortages: with not enough people to hire, manufacturers are forced to do more with less. As a result, Machine Health isn’t going anywhere. It’s proven its worth.

But it doesn’t mean we can’t expand on our ambitions – and how we measure them. 

Awkward Conversations

It’s legitimate for those customers who have been with us for three or four years and are now enjoying almost 100% uptime thanks to our system, to question what value we are bringing them now that downtime is no longer the price of doing business. 

They are looking at the numbers and seeing we are not saving them that five or six million dollars as we did three years ago. Our case was clear.

Dream Team

Indeed, their maintenance teams on the floor are not questioning our worth. We’ve become a fundamental part of what they do, and they still have wins almost every day. And to their credit, they are the core of a successful Machine Health program. 

Teams are responding precisely as they are supposed to – fixing things before they become a real problem. They’ve learned to run the assets better. For instance, they know if a bearing reading changes, it’s time for lubrication. They know what will happen and don’t have to wait for the danger alarm.

This is something to celebrate. But with no full danger alarm, we can no longer count it as preventing downtime…

Building A Value Narrative

Our champions working at our client manufacturers – usually those working on the floor – understand this paradox. They’ve reached out to our customer success managers to help them better describe the worth of our program. And for them, we were inspired to write a FAQ: ‘Do you have any tools for selling the results of our program to our leadership?’. 

There is indeed a much larger story to tell regarding what value Augury brings to the table. A larger value narrative can work to loop in the bigger picture that goes beyond simple ROI. And such a narrative can grow from answering new questions. 

Digging Deeper: Telling The Story In New Ways

Meanwhile, we continue to travel the road of continuous improvement – refining and expanding our Machine Health offering. There are still so many directions to take from here. While often more challenging to quantify, it’s not impossible. We already know from customer conversations they are finding value in all sorts of places.

Look at the number of resolved root causes as the workforce goes from firefighting to planned maintenance based on real-time insights. Has the morale changed? How about your safety numbers?

Look at the retention numbers. Are fewer people retiring early? Are you hiring more younger workers who are attracted to cutting-edge AI tech? Is there increased job satisfaction?

In fact, once you start digging, countless questions may have value in their answers:

·      What business problems did Augury solve?

·      Are there the stories that bring the program’s success to life?

·      What’s changed? In terms of how you do maintenance? In when you do maintenance? Do your maintenance and operations teams interact differently? Did you stop doing things you no longer had to do?

·      How has Augury helped you go after root causes and improve Process Health?

·      What do the users of Augury say about how their day-to-day life has been transformed? In terms of productivity? Job Satisfaction? Safety?

·      Are there other metrics you can measure besides avoided downtime hours?

Yes, our original pitch was and continues to be helping you eliminate unnecessary downtime. But our goal has always been more than that: it’s been to be your partner and co-pilot as you continually up your game and elevate the total value you create for your organization.

The post How Do You Measure Success Once You Beat Unplanned Downtime? appeared first on Augury.