Litmus Automation > Case Studies > Asset Management and Predictive Maintenance

Asset Management and Predictive Maintenance

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 Asset Management and Predictive Maintenance - IoT ONE Case Study
Technology Category
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Equipment & Machinery
Applicable Functions
  • Discrete Manufacturing
Use Cases
  • Predictive Maintenance
About The Customer
This customer ranks among the leading manufacturers of commercial boilers in North America.
The Challenge

The customer prides itself on excellent engineering and customer centric philosophy, allowing its customer’s minds to be at ease and not worry about machine failure. They can easily deliver the excellent maintenance services to their customers, but there are some processes that can be automated to deliver less downtime for the customer and more efficient maintenance schedules.

The Solution

The customer adopted the Loop Platform for secure real-time Data Collection of their legacy boilers. Once the data was collected, Loop enabled the customer to perform complex analytics over the data and utilize its predictive models to detect failures of the machines. Based on this analysis, thresholds were placed around the data using Loop Triggers. Once the data went out of these thresholds that indicated failures, a case lead was generated in their for their Customer Support team so they can be notified. Featuring: - Hosted Loop IoT Platform - Fully White-labeled for their customers - Remote real-time monitoring of their machines - Customized condition monitoring, fault detection, predictive maintenance and alerting - Remote configuration of industrial machines - Customized device management, operational and technical dashboards - Integrations with their enterprise system such as Heroku, and CRM.

Data Collected
Downtime, Fault Detection, Machine Performance, Machine Utilization Rate, Maintenance Requirements
Operational Impact
  • [Process Optimization - Predictive Maintenance]
    Considerably improved service levels through detection of failures.
  • [Data Management - Data Availability]
    Providing visibility of previously unknown or out-of-date operational usage and performance information for their Boilers.
  • [Efficiency Improvement - Time To Market]
    Adoption of the fully configurable Loop Platform allowed the customer the ability to focus on the value adding activities for their customers and their business.

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