AI-Powered Test Plan Optimisation: Predicting Next Tests in Engineering

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Presented by

Joel Henry, Jousef Murad

About this talk

Validating complex, non-linear systems can be difficult. It's not possible to test every possible scenario on a test bench or simulation. Over-testing only confirms what is already known, while under-testing can risk failing certification or missing issues. Active learning uses machine learning to help engineers create testing plans more efficiently in automotive and aerospace product development. Monolith has created a new feature, the Next Test Recommender (NTR), which enables users to train and assess machine learning models. It offers valuable recommendations for optimal test conditions to apply in the next round of testing. NTR assesses previously gathered data to suggest the most effective new tests to conduct. Join Dr. Joel Henry, Dr. Gareth Jones, and Jousef Murad for a discussion on how Monolith AI software enhances test engineers' capabilities to iteratively optimise their test campaigns by maximising the value derived from the time allocated to a test campaign or by reducing the time taken to achieve a certain quality of testing. This knowledge and human-in-the-loop design empower engineers to make informed decisions, optimise their test plans, and keep responsibility for continuously improving the final product's safety, quality, and reliability. In this webinar, you will learn about: – Optimising test campaigns for efficient resource allocation and improving testing quality. – Leveraging machine learning models to make data-driven decisions. – The benefits of using Monolith AI software.
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Monolith software is trusted by the world’s top engineering teams including Rolls Royce, Siemens, Honeywell, and BMW to develop better quality products in half the time. Backed by one of world’s largest software investors and recognized by Gartner as a Cool Vendor for AI in Automotive, Monolith AI empowers engineering domain experts in automotive, aerospace and industrial markets to reduce expensive, time-intensive testing, lower risks to product performance and quality, and cut product development time. Featured in Forbes magazine and named one of the UK’s top 100 startups, Monolith AI founder Dr. Richard Ahlfeld received his PhD in Aerospace Engineering from Imperial College and was named to MIT Technology Review’s Top 10 Innovators under 35. Monolith AI is headquartered in London with global enterprise clients worldwide.