Litmus Automation Case Studies Asset Management and Predictive Maintenance

	Asset Management and Predictive Maintenance Litmus Automation

Asset Management and Predictive Maintenance

Litmus Automation

Technology Category	Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Equipment & Machinery
Applicable Functions	Discrete Manufacturing
Use Cases	Predictive Maintenance
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. Read More
About Customer	This customer ranks among the leading manufacturers of commercial boilers in North America. Read More
Customer Name	Undisclosed Read More
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 Salesforce.com 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 Salesforce.com CRM. Read More Log in to view content
Data Collected	Downtime, Fault Detection, Machine Performance, Machine Utilization Rate, Maintenance Requirements Read More Log in to view content
Contents

Technology Category

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Equipment & Machinery

Applicable Functions

Discrete Manufacturing

Use Cases

Predictive Maintenance

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.

About Customer

This customer ranks among the leading manufacturers of commercial boilers in North America.

Customer Name

Undisclosed

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 Salesforce.com 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 Salesforce.com CRM.

Data Collected

Downtime, Fault Detection, Machine Performance, Machine Utilization Rate, Maintenance Requirements

Impact #1	[Process Optimization - Predictive Maintenance] Considerably improved service levels through detection of failures.
Impact #2	[Data Management - Data Availability] Providing visibility of previously unknown or out-of-date operational usage and performance information for their Boilers.
Impact #3	[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.

Impact #1

[Process Optimization - Predictive Maintenance]
Considerably improved service levels through detection of failures.

Impact #2

[Data Management - Data Availability]
Providing visibility of previously unknown or out-of-date operational usage and performance information for their Boilers.

Impact #3

[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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Overview

Asset Management and Predictive Maintenance

Operational Impact