Monolith

Detecting anomalies early is key to maintaining efficiency and accuracy. With test labs generating millions of data points daily, manual monitoring can become overwhelming without the right tools. 🕵️♂️This is where automated data inspection comes in. Monolith's Anomaly Detection, powered by unique machine-learning algorithms, efficiently detects issues across millions of data points, saving time and effort. An Anomaly Score calculation flags errors according to your needs, and our multivariate analysis technique allows for complex errors to be detected across hundreds of channels faster. ▶️This video is a short demo of anomaly detection with Monolith. If you're already with us and want to dive deeper, we have a helpful blog and webinar. Thanks to: Joel Henry Or if you want to get started with Monolith, book a demo directly on our website. Our team are always happy to support, reach out anytime. #anomalydetection #engineering #aiengineering #multivariate

Where does our "Test Less. Learn More." come from? Today, I wanted to share the story of how one of our “catchphrases” at Monolith was born: Over the years, Monolith has grown in new use cases of machine learning to help engineers be more efficient in testing. One of the significant ways we did this was by using machine learning to optimise and predict which tests to run to ensure you covered the design space as efficiently as possible with our test plan optimisation modules. Our hypothesis: We could look at the tests we have run so far, feed those into a machine learning algorithm and use active learning to recommend the most efficient subsequent tests, reducing the number of tests you need to run. In other words, machine learning would allow engineers to test and validate their products with fewer overall experiments. When validating this hypothesis, we downloaded data from a Stanford study, put it through our algorithms and found a reduction in the total number of tests needed by 73%! And at that point, we confirmed:  -You could either run fewer experiments  -Or you could run the same number of experiments but gain more insights Hence, “Test Less. Learn More.” was born. Want to see how we did it? Check out the full methodology and data in this white paper on AI in engineering: https://lnkd.in/e-d4KBAD Are you interested in hearing more stories about Monolith, machine learning, and engineering? 🔗 Make sure to follow me Richard Ahlfeld, Ph.D. #engineering #machinelearning #monolith #ai #startup

Wondering what's the latest in battery research, publications, podcasts, thought leadership, white papers and more? 🔋 🤔 📖 Check out Watt's New in Batteries featuring content from: ⚡ Ascend Elements ⚡ Strativ Group ⚡Monolith ⚡ Exponent ⚡ Beckhoff Automation ⚡ Iontra Inc ⚡ Blue Current, Inc. ⚡ Fruition IT ⚡ Factorial Energy ⚡ ACCURE Battery Intelligence ⚡ JuliaHub ⚡ TA Instruments ⚡ Exum Instruments ⚡ Maritime Battery Forum ⚡

Excited to announce a new webinar: Anomaly detection tools aren’t new but the errors being uncovered by machine learning are.🔍 Dive into anomaly detection with our experts and discover a better, faster way to detect errors: https://lnkd.in/eUFzXaq5 #batterysolutions #cae #ai #anomalydetection #batterytesting Joel Henry Arnaud Doko Simon Yang D.

Examining the potential of solid-state #battery technology, and recent advancements: 🔋 What are the advantages over traditional lithium-ion batteries in applications such as electric vehicles? 🤔 What are the challenges of commercialisation and potential solutions? Explore the topic here on the Monolith blog! 🔗 https://lnkd.in/e4CJeEjG #energystorage #batterysolutions #batterytechnology #electrification

We're heading back to The Battery Show, this time in North America! Looking forward to connecting with engineers, industry leaders, and innovative minds working on powerful solutions for the future 🚗⚡ The Monolith team will be ready to demo our platform and answer any questions you have about how to test less and learn more. 📍🙋♂️ Stand 6107 Will we see you there? Drop by or book a time-slot here: https://lnkd.in/etDhga82 Richard Ahlfeld, Ph.D. Jim Shaw John Pasquarette Arnob Bhuyan #batteryshow #ai #engineering #engineeringtools #automotiveengineering #batterysolutions

Register now for our upcoming webinar, and learn how using new anomaly detection tools can uncover errors you couldn’t find before!

Awesome article from Lead Principle Engineer, Joel Henry. Univariate to multivariate analysis, learn to detect anomalies earlier — direct from an engineer: https://lnkd.in/e934vS3e Or watch the webinar here: https://lnkd.in/e6szJJBV

What if we could detect battery testing errors before they compromise our work? Join John Pasquarette, Joel Henry and Arnaud Doko of Monolith as they discuss recent breakthroughs in AI/ML for preemptive error detection and resolution in battery technology: https://lnkd.in/g24uWdD6 🤖 🔋 Aaron Wade Ulderico Ulissi Alex Cipolla Matthias Simolka Myra S. Dyer, PE Jennifer Channell Volta Foundation

Integrating AI into battery testing, development, and manufacturing is transformative. AI optimises resource use, minimises waste, and enhances efficiency, enabling OEMs like Jaguar, Volkswagen, BMW, and Volvo to better achieve sustainability goals. But, constructing and operating advanced testing labs comes with an undeniable environmental impact. The journey towards a truly sustainable EV ecosystem involves more than just the vehicles themselves. Explore the topic here: https://lnkd.in/er35KzBY #ai #oems #automotive #manufacturing #industry #engineering #sustainability