Leveraging Data Science for Predictive Maintenance in Industrial Settings

Abstract

In recent years the industrial landscape has been dramatically changing due to technological advances and the increased importance on operational efficiency. In industries where essential machinery and equipment are very complex, integration of data science with maintaining practice has been quite transformative. This technological revolution is benefitting manufacturers plants, energy facilities, transportation networks among others. Keeping an eye on how equipment health and performance metrics are year to year evolving allows companies to make data driven decisions regarding when to do maintenance activities and how to do them. With that, the applications of data science in predictive maintenance become more and more obvious and it’s obvious that we are not talking about a fleeting trend here, but a completely new approach to industrial operations based on predictive maintenance. The ability to predict and prevent equipment failures has widespread impact on productivity, safety, profitability within various industries.