Maintaining machinery in the chemical and manufacturing industries is costly. Global Fortune 500 manufacturing and industrial companies claim to lose over 3 million hours a year due to unexpected downtime, resulting in an $864 billion loss — the equivalent of 8% of their combined annual revenue. Moreover, according to Gartner, the average cost of machine downtime is $5,600 per minute.
With the rise of the Industrial Internet of Things artificial intelligence and machine learning, and data engineering, companies have shifted towards tech-powered solutions to save money.
At the same time, organizations prefer to validate the initial prototypes before implementing large-scale IoT projects. Going all-in might be risky without evaluating the upcoming development’s financial benefits based on a PoC.
PreFix, Intellias latest IIoT predictive maintenance concept, is designed to help companies maximize uptime and limit potential complications in production. It detects anomalies like heat exchanging system breakdown, liquid leakage in chemical storage tanks, pumping system failure, motor vibration, and more.
The core objective of the project was to address the main problems of the chemical, manufacturing, energy and utility, and construction industries with remote monitoring and instant alerting. Intellias team created an edge computing system using pressure sensors and machine learning to monitor industrial equipment health. This system processes high-frequency data (10,000 records/sec) to detect anomalies, offer early warnings, and prevent failures. As a result, Intellias implemented an intelligent microservices-based IoT platform for collecting, storing, and analyzing real-time data. Correct interpretation of sensor data allowed to apply that data further in predictive maintenance models to minimize repairs and system damage.
Apart from reducing expenses on fixing issues that have already occurred, another goal of Prefix is to showcase the practical implementation of technology to ensure safety in industrial environments. Incidents in chemical or manufacturing facilities may result in personnel meeting toxic liquids or vapors and may lead to catastrophic consequences.
Proactive asset management can help companies avoid incidents and unlock new value and growth opportunities instead. The numbers on predictive maintenance presented by Deloitte speak for themselves:
-
20% increased equipment uptime
-
25% lower maintenance costs
-
25% increased productivity
Read more details about Prefix – the predictive maintenance predict-and-fix concept on the Intellias website.
