HANNOVER MESSE 2020,
20 - 24 April
Unexpected production downtime due to machine failure is costly to manufacturers. Therefore, time-based maintenance programs are often implemented in attempt to ensure the health and performance of production machines. However, this maintenance model is not always effective. When the maintenance cycle is too long, parts could fail prior to the next inspection which would cause machine failure. If the maintenance cycle is too short, parts might be replaced before end-of-life which is unnecessary and could become costly.
BISTel Predictive Maintenance solution leverages its advanced real-time monitoring and data analytic capabilities to predict the Remaining Useful Life (RUL) of machine components and when failures might happen. This allows engineers to perform maintenance activities at the most optimal time possible, providing a more efficient and effective maintenance model.
- Powerful real-time monitoring and data analytics eliminate time delays in recognizing impending issues
- Intelligent detection and prediction engine using Statistical Process Control (SPC) and other advanced analysis
- Intuitive dashboard provides simple control charts to visualize performance and trigger maintenance activity
AI based Predictive Maintenance, from Edge to Cloud
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