Manchester-based Industry 4.0 technology start-up has announced a partnership with leading industrial and electronics products distributor RS Components.
The 拢1.3 million R&D project will produce the first affordable machine learning-enabled predictive maintenance solution for manufacturing SMEs.
The partnership will be supported by Innovate UK, which has awarded a joint R&D grant to support the technology鈥檚 development.聽
The project will focus on the application of anomaly detection for improved maintenance, engineering and decision-making.聽
It hopes the end result will be a platform capable of using standard manufacturing environment equipment to harvest and process relevant data in order to detect anomalies within machinery.
Machinery downtime currently costs British manufacturers approximately 拢180 billion every year, representing 3% of all working days. It is estimated that the implementation of such a solution would save SMEs 65% of these costs.
/company/samsonvt/
鈥淲e know that the high costs and complexity of PdM tools are a big barrier to adoption for SMEs 鈥� which make up the majority of the UK鈥檚 manufacturing companies,鈥� said Sam Burgess, CEO at SamsonVT.聽
鈥淏ut, by delivering a PdM platform that is accessible and affordable 鈥� leveraging cutting-edge machine learning techniques 鈥� we can help save British manufacturers billions every year in unplanned machine downtime.鈥�
Richard Jeffers, director of maintenance solutions at RS Components, added: 鈥淲e 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.聽
鈥淭his 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.鈥�