Predictive Maintenance identifies imminent failure patterns that are often undetectable by humans through real-time analysis of multiple parameters. This allows proactive maintenance scheduling and minimization of the risk of unscheduled downtime.
Predictive Maintenance uses embedded sensors to potentially monitor hundreds of parameters without human intervention and detect departure from normal operational parameters continuously without needing highly specialized tools or experts. A machine learning based approach to predictive maintenance can learn continuously and generalize from new data – potentially identifying breakdowns that have never been observed before. This not only reduces overall cost and frequency of maintenance, but also reduces reliance on specialized tools and expertise required for traditional predictive maintenance.
Our holistic approach starts with an assessment of the current maintenance and downtime performance of your organization. This is followed by: