MHS introduces IoT-based predictive maintenance solution


MHS, a single-source provider of material handling automation and software solutions, has announced the launch of MHS Insights, a condition-based maintenance solution that monitors assets through Internet of Things (IoT) sensors and system data to provide timely maintenance recommendations and strategic health assessments.

MHS Insights integrates readings from multiple data sources with predictive models, historical readings and detailed knowledge of failure modes. This provides service organisations with precise condition-based predictive alerts on potential failures, rated with a red, yellow or green level of urgency. These proactive maintenance and component replacement recommendations come well ahead of the point at which alarms would activate in the control room.

By detecting emerging failure risks early, businesses can turn unplanned downtime into strategically planned repairs that minimise system disruption and help maximise reliability. Condition-based maintenance can also avoid unnecessary routine preventative maintenance tasks based on arbitrary schedules, instead providing asset-specific information.

Facilities can integrate MHS Insights with the company’s computerised maintenance management system (CMMS) solution, for a seamless, effective package to optimise maintenance spend and system performance. MHS Insights alerts can auto-populate work orders and part orders, saving time and costs on administrative tasks and arming technicians with original equipment manufacturer (OEM)-specific recommendations and equipment information to expedite service.