Data Visualization and Predictive Analytics in Manufacturing: A New Paradigm in Maintenance

Technology has come a long way with data science as its evolution has led to major changes in all types of industry. This paper deals with the optimization of data visualization of predictive maintenance in the field of manufacturing. Predictive maintenance is a technique which is applied by manufacturing companies to foresee any equipment failures. This is performed by examining data from sensors or various other sources. By recognizing potential failures, the companies can avoid equipment downtime, costly failures and maintain their maintenance schedules. The traditional preservation practices include fixing an equipment once the breakdown occurs or during fixed maintenance schedules. However, this can be time consuming and can affect the company's schedule or it can be costly. This issue can be targeted through predictive maintenance. This includes collecting data from factors such as air temperature, process temperature, rotational speed, torque and tool wear. Through this visualization, a clear correlation can be made between the various factors provided using power BI.