Manchester-based Industry 4.0 technology start-up SamsonVT has announced a partnership with leading industrial and electronics products distributor RS Components, to produce the first affordable machine learning-enabled predictive maintenance (PdM) solution for manufacturing SMEs.
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 predictive 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.
“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,” commented Sam Burgess, CEO at SamsonVT.
Machinery downtime currently costs British manufacturers approximately £180 billion every year, representing 3% of all working days. It is estimated that the implementation of a PdM solution would save SMEs 65% of these costs.
By ensuring machinery is neither under nor over maintained – as is often the case with time-based preventative maintenance practices – PdM helps to optimise predictive maintenance resources, reduce the unnecessary replacement of parts and minimise the ancillary damage repair costs caused when parts fail in situ.
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.
“We are excited to be working with SamsonVT on this project. For busy SMEs that may not have previously considered PdM as an option, due to perceived cost and limited management time, this will be a real gamechanger. This will provide them 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,” added Richard Jeffers, Director, Maintenance Solutions at RS Components.
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 3 to 6 months – and do not require highly trained personnel to interpret the findings.
