Equipment maintenance is one of the biggest cost centers for many industries, including manufacturing. Maintenance programs of the past sought to increase the uptime and lifespan of key machinery assets by ensuring they were well cared for on a routine basis, thus minimizing the chance that they would breakdown at the worst possible time, halt production, and negatively impact work order completion rates.
In 2020, more businesses are looking to technology, largely driven by IoT and industry 4.0 case studies, to see how an investment in sensor technology and data analytics software might further optimize their fleets’ productivity and uptime while minimizing repair costs by only completing maintenance when it’s necessary.
Why is predictive maintenance easier now than before?
While the concept of predictive maintenance isn’t new, it is now much easier and more affordable due to the advancements in technology surrounding sensors, data storage, and analytical software-driven by AI. These three key pieces of technology combined, are affording the ability to predict maintenance and service requirements, with more accuracy and based on current machine readings, historical performance metrics, and expected machine performance.
A Strong Uptake in the Aviation Industry
Most industries are starting to aggressively invest in their predictive maintenance programs, however, one sector that’s leading the pack is the aviation industry. According to one of the world’s largest jet engine manufacturers, General Electric, over 1TB of data per engine is collected on an average domestic flight. When paired with the right software, this data can be analyzed and stored for future predictive maintenance programs.
Sensor Accuracy and Lower Data Storage Costs Make Predictive Maintenance Affordable
It’s important to appreciate just how quickly technology has progressed in the previous two decades. Not only have our devices gotten smarter but the cost of accessing high-speed internet and cloud data storage has made accessing “big data” a possibility for almost every business. This combined with the increased accuracy and effectiveness of sensor technology means that many businesses can invest in a predictive maintenance solution with very low overheads.
However, it’s vital to understand that predictive maintenance programs are only as good as the historical data they use. Delaying investment in predictive maintenance prolongs the time it takes for a business to collect the mission-critical data required for these programs to be effective, competitive and show a return on investment.
About VibePro
At VibePro, it is our mission to provide the best predictive tools on a single iPad platform with services to monitor nearly any asset. We strive to bring our customers the portability, connectivity, and affordability offered by the latest available technologies. Our product family combines wireless portable and online vibration data collection and analysis, balancing, shaft alignment, thermography, and ultrasound into an affordable and completely scalable solution on one simple to use platform. VibePro’s predictive technology apps feature many additions that have come directly from customers. Click here to learn more.