We Optimize your Maintenance Management
Our SaaS solution is based on IIoT, Big Data and our LRCM methodology which captures equipment failure mode information for predictive analysis. We provide asset intensive companies with the knowledge base, process, and analytics they require to optimize equipment maintenance and increase safety while reducing downtime and maintenance costs.
Which maintenance related data is relevant to physical asset reliability improvement? How do we transform that data into decision models for more effective equipment management decision making across the organization? How do we continuously update those models for verifiable asset reliability improvement? These questions drive our relentless pursuit of new maintenance technics. We have found the solution to the long standing problem of achieving physical asset reliability from data.
Savings in Maintenance Costs
Improvement in decision Information
What the industry and customers say
“Big Data, the Internet of Things and Predictive Analytics are currently more than feasible when applied to maintenance, and represent a huge potential opportunity for benefit”
Sandy Dunn, Assetivity
"The LRCM methodology ensures the dynamic construction of the maintenance strategy."
"The LRCM methodology extends the theory, precision language, and concise reasoning of RCM to achieve reliability from data in daily maintenance practice."
Murray Wiseman, CEO Living Reliability
“Invariably, we hear that today the best real-world benefit examples are coming from the use of IoT-generated data to facilitate better Condition-Based and Reliability-Centered Maintenance (CBM & RCM)”
Dan Miklovic, LNS research
“The solution has improved in 50% the quality of decision information”