SamsonVT (and RS Components) begins predictive maintenance R&D project13 January 2022

Manchester-based Industry 4.0 technology start-up SamsonVT has announced a partnership with RS Components to produce what they describe as the first affordable machine learning-enabled predictive maintenance (PdM) solution for manufacturing small to medium-sized enterprises.

The partnership will be supported by Innovate UK, which has awarded a joint R&D grant to support the technology’s development.

The ADX project will focus on the application of anomaly detection for improved maintenance, engineering and decision making – and will see SamsonVT integrate data extraction, criticality assessment, machine learning (ML) and root cause analysis with its existing condition monitoring platform, SamsonBASE. The end result will be a PdM platform capable of using standard manufacturing environment equipment to harvest and process relevant data, in order to detect anomalies within machinery.

By ensuring machinery is neither under nor over maintained – as is often the case with time-based preventative maintenance practices – PdM helps to optimise maintenance resources, reduce the unnecessary replacement of parts and minimise the ancillary damage repair costs caused when parts fail in situ.

They said that most SMEs are yet to adopt this approach, however, due to the high implementation costs. The ADX project seeks to address this problem by significantly reducing this cost burden. It will provide SMEs with bespoke ML/ anomaly detection models for effective maintenance, with no initial changes to infrastructure required. This means SMEs can use their existing network of sensors, hardware, and equipment – provided they have been harnessing data for a minimum of three to six months – and do not require highly trained personnel to interpret the findings.

Sam Burgess, CEO at SamsonVT said: “We know that the high costs and complexity of PdM tools are a big barrier to adoption for SMEs – which make up the majority of the UK’s manufacturing companies. But, by delivering a PdM platform that is accessible and affordable – leveraging cutting-edge machine learning techniques – we can help save British manufacturers billions every year in unplanned machine downtime.”

Richard Jeffers, director, maintenance solutions at RS Components adds: “This will provide [SMEs] with a PdM solution that is as close to plug-and-play as you are going to get, generating the insights they need in order to know when to act and, just as importantly, when not to.”

Operations Engineer

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