Senseye, the industrial software company, today announced a new alliance with MCP Consulting Group, an asset management consultancy that advises many of the world’s largest manufacturing organisations.
MCP has selected Senseye PdM, Senseye’s specialised predictive maintenance software, as a core component of its new Smart Asset Maintenance venture, which combines best-of-breed technologies to provide bespoke asset management and maintenance systems.
Senseye PdM will enable MCP’s clients to monitor their systems and machinery automatically. The software uses proprietary algorithms and AI technology to assess the health of industrial assets and predict future failures up to six months ahead of time by analysing machine data gathered using wireless sensor technology.
Senseye PdM is used by Fortune 500 industrial organisations globally to achieve new sources of competitive advantage by reducing unplanned downtime, spare parts inventory, and maintenance expenditure. Manufacturers across a range of industries have halved downtime levels and achieved reductions in maintenance costs of up to 40 per cent by implementing Senseye as part of digital transformation initiatives.
Simon Kampa, Chief Executive Officer of Senseye, comments: “Major manufacturers around the world recognised MCP for the quality of its advice and ability to drive substantial operational and maintenance performance improvements in large scale industrial environments. We are thrilled to be working in partnership with MCP on its new Smart Asset Maintenance venture and look forward to supporting its clients globally.”
Peter Gagg, Chief Executive Officer at MCP Consulting Group, comments: “We know from our consulting activities that a quarter of manufacturing costs can be attributed to downtime and that the majority of maintenance is reactive work to address sudden machine failures. There is scope for industrial organisations to achieve huge efficiency and productivity gains by improving reliability, and Senseye has shown that it is possible to do this by applying predictive maintenance and condition monitoring technology in a straightforward, cost-effective way.”