Augury: AI-Powered Machine Health and Solving the Skills Gap
Introduce yourself and your role
My name is Saar Yoskovitz and I am the Co-Founder and CEO of Augury, a company focused on Machine Health and Process Health.
I collaborate closely with our Industrial customers and partners to revolutionise work and innovation through AI insights into their operations.
What sets Augury apart as a company?
At Augury, we envision a future where people and machines work together to improve every aspect of our lives.
We stand out because we blend cutting-edge AI technology with extensive industry expertise. As pioneers in AI-driven solutions for Machine Health and Process Health, we combine the Internet of Things (IoT) with sophisticated AI diagnostics and a team of dedicated industry experts.
Our AI technology, informed by the world’s largest data library for machine health, helps us predict and prevent machine failures, optimise processes and enhance operational efficiency. We don't just provide technology; we build lasting partnerships with our customers, helping them transform work for their teams, achieve sustainable production goals and unlock their full operational potential.
Tell me more about Augury’s AI-driven machine health platform
Our AI-powered solutions are designed to help manufacturers and industrial firms minimise downtime, increase efficiency, optimise yield, reduce waste and emissions.
Through our Machine Health solution, sensors capture and transmit data 24/7; AI quickly identifies issues, what causes them and how to fix them; and actionable insights empower reliability and maintenance teams to enhance operations and safety.
What insights can manufacturers gain from decoding machine sounds?
Decoding machine sounds offers manufacturers crucial insights into their equipment’s health and performance. By analysing vibrations, temperature variations and magnetic data, our Machine Health platform can anticipate and avert failures, diagnose issues proactively and provide actionable suggestions.
This empowers manufacturers to minimise downtime, optimise maintenance routines and improve operational efficiency overall. Essentially, it transforms machine information into valuable data that enhances both the maintenance and performance of machines, leading to smoother and more dependable operations.
How does your platform enhance sustainability?
Our platform promotes sustainability because healthier machines create less waste and consume less energy.
Through predictive maintenance and failure prevention, we assist manufacturers in avoiding unnecessary downtime which also minimises the amount of repairs and parts and prolongs equipment lifespan. Optimising machine performance means a reduction of energy consumption, effectively lowering the overall carbon footprint. We enable companies to achieve their sustainability objectives while meeting their production goals.
How do you reckon with the sustainability downsides of AI- like the huge amounts of energy it requires?
A recent study done by Eclipse Ventures, in collaboration with Rho Impact, estimated that Augury’s technology will have a net positive impact on carbon emissions, reducing 69 MTCO2e by 2050. On top of this, if we look at the current arc of technology, we see a clear push to bring the compute, the AI inference, to the edge, running as close as possible to the data source. This has many benefits, one of them being reduction in data bandwidth and transmission - which is a huge power draw - reducing the overall Energy consumption.
What would you say is the current mood and state of UK manufacturing?
The manufacturing industry in the UK is bouncing back following unprecedented shifts in demand during the pandemic, disruptions in prices following the Russian invasion of Ukraine and supply chain issues due to the blockage and conflicts in the Suez Canal. All things that have impacted manufacturing on a global scale.
The key issue UK manufacturing is trying to overcome is the shortage of skilled workers. However, things are looking up as Make UK expects manufacturing to grow by 1.2% this year.
How can UK manufacturers adopt predictive maintenance solutions? Why should they?
Integrating predictive maintenance begins with identifying the key metrics that you are looking to improve and the assets that impact them the most.
Next, find a solutions provider to partner with and install sensors on key equipment and leverage that continuous machine data into an AI-driven platform for real-time insights. And of course, at the end of the day technology is about the people who use it so make a change management plan to drive adoption and get the most out of your technology investment.
The advantages are endless. By enhancing reliability and efficiency, predictive maintenance helps manufacturers solve production issues, stay competitive and achieve sustainability goals.
How is AI going to help manufacturers navigate a global skills shortage?
Companies are facing a significant skills shortage. To address this challenge, many are turning to AI to not only automate routine tasks and provide real-time diagnostics but also to revitalise roles within the industry. In the case of machine health, workers can cover more machines, move away from repetitive routine tasks and focus on higher-value work.
With AI technology, workers experience more predictable workdays, increased safety and the industry is becoming more appealing to digital-minded job seekers. It’s even created new roles that are helping to drive future innovations.
What are your predictions for the future of AI and machine health?
As AI continues to advance in its capabilities, we will have opportunities to tie together new datasets, that help us answer questions we have never imagined asking. This requires multi-modal models that can react in real-time to a host of environmental, operational and mechanical changes and predict the best path forward - going beyond optimising machines’ reliability, to optimising production health.
Is there anything else you’d like to share with Manufacturing Digital’s audience?
The biggest challenge our industry is facing, by far, is the shortage in skilled workers and the generational gap that is looming as our most experienced workers are set to retire in the next few years.
We must find a way to digitise their knowledge and quickly onboard the next generation as they come into the workforce. This also creates a massive opportunity. We can re-imagine the way our teams work and what they can create by infusing AI into the different stacks of manufacturing operations.
We can finally break down silos between teams and achieve the TPM vision of integrated work groups. We can empower our people to focus on the key tasks that matter, making fast decisions based on data and insights.
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