The way companies approach maintenance of their industrial assets has not changed much since the Industrial Revolution. While manufacturing industries continuously struggle to maximize asset availability, they continue to repair assets mostly when they fail and following a largely unoptimized schedule. These poor maintenance strategies can reduce a plant’s overall productive capacity by 5 to 20 percent, costing industrial manufacturers around $50 billion each year. This centuries-old approach is on the cusp of disruption.
Senseye offers a uniquely scalable predictive maintenance solution that seamlessly integrates with the existing infrastructure. Harnessed by the team’s deep expertise in machine learning, this plug & play uptime-as-a-service software predicts the remaining useful lifetime of machinery, enabling a move from simple condition monitoring to prognostics, and allowing for a factual and proactive maintenance planning. Senseye’s solution reduces downtime and operational costs and brings enterprises to the fourth Industrial Revolution.