IoT Based PM solutions

MHS launched MHS Insights a IoT-Based Predictive Maintenance Solution5 min read

A US-based single-source provider of material handling automation and software solutions company, MHS announces the launch of MHS Insights, a condition-based maintenance solution that monitors assets through IoT sensors and system data to provide timely maintenance recommendations and strategic health assessments.

John Sorensen, senior vice president, Lifecycle Performance Services, MHS Said:

“By not leveraging data, warehouses and distribution centers miss significant opportunities to reduce downtime and make their service operations more effective and efficient, MHS Insights is designed to address this deficiency by combining data and analytics to provide precise, timely maintenance insights.”

MHS Insights integrates readings from multiple data sources with predictive models, historical readings and detailed knowledge of failure modes. This provides service organizations 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 when alarms would activate in the control room.

By detecting emerging failure risks early, businesses can turn unplanned downtime into strategically planned repairs that minimize system disruption and help maximize reliability. Condition-based maintenance can also avoid unnecessary routine preventive maintenance tasks based on arbitrary schedules, not asset-specific information.

Facilities can integrate MHS Insights with the company’s CMMS solution, for a seamlessly integrated, effective package to optimize maintenance spend and system performance. MHS Insight alerts can auto-populate work orders and part orders, saving time and cost on administrative tasks, and arming technicians with OEM specific recommendations and equipment information to expedite service.

To learn more about MHS Insights.

# Its a Press Release originally published on MHS (Material Handling Systems, USA)

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