Equipment downtime is a very expensive problem for businesses and unplanned maintenance significantly increases the operations cost. Predictive maintenance, using machine learning techniques, can change this significantly. How do you utilize the data collected? How this works and how it can benefit you? These are some of the topics we will be discussing in this webinar.
Predictive maintenance, using machine learning techniques, can change this significantly. Foresee the future of your equipment by monitoring their condition and performance under normal settings.
Vinay completed his doctorate from Clemson University, SC and since then has developed maintenance scheduling models for Norfolk Southern Railroad, Atlanta, preventive scheduling models on GE turbines and windmills and has used equipment performance data for BHP Billiton, Australia to determine ways to maximize throughput. Currently, he is working on conducting root cause analysis on failures of electric charging stations.