Accelerating the
Industrial Internet of Things

Asset Management and Predictive Maintenance

Asset Management and Predictive Maintenance

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

- 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.
Emerging (technology has been on the market for >2 years)
Predictive Maintenance - Considerably improved service levels through detection of failures.
Increased Usage Visibility - Providing visibility of previously unknown or out-of-date operational usage and performance information for their Boilers.
Very Fast 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.
The IoT ONE Radar indicates the mix of hardware, software and services used in an IoT solution.
Horizontal applications are standardized (e.g., asset tracking). Vertical applications are tailored to specific needs (e.g., delivery fleet management).
APIs are the market enabler for IoT. They allow users to manage devices, enable data transfer between software, and provide access capabilities.
Middleware integrates the diverse components of an IoT application by structuring communication, workflows, and business rules.
IoT analytics includes real-time or edge computing and batch analysis. Analytics can be behavioral, descriptive, predictive, or prescriptive.
Visualization solutions use dashboards, alerts, events, maps, and other tools to present easily comprehensible data to end users.
Data management solutions capture, index and store data in traditional database, cloud platforms, and fog systems for future use.
Security software provides encryption, access control, and identity protection to IoT solutions from data collection through end-user applications.
System integrators link IoT component subsystems, customize solutions, and ensure that IoT systems communicate with existing operational systems.
IoT data management consultancies help to make sense of big data, decide which data to maintain and for how long, and troubleshoot IT issues.
IoT software consultancies support the development of data analytics, visualization solutions, and platforms, as well as integration into embedded systems.
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