Application of Data Analytics in Process Prediction, Analysis, Management & Visualization Using Microsoft Power BI

This research explores the application of data analytics, specifically Microsoft Power BI, to optimize processes within the chemical and manufacturing industries. By analyzing large volumes of production data from a PVC (polyvinyl chloride) manufacturing plant, it aimed to identify trends, anomalies, and opportunities for improvement. The study involved collecting, cleaning, and transforming production data, including process temperature, flow rate, torque, tool wear, energy consumption, and failure types. This data was then loaded into Power BI, where it was analyzed and visualized to gain insights into the manufacturing process. Through data-driven analysis, critical relationships between process variables and product quality were identified. For instance, it was observed that variations in voltage and temperature can significantly impact product quality and energy consumption. By monitoring these variables and making timely adjustments, it is possible to optimize production processes, reduce energy costs, and minimize product defects. The findings of this research demonstrate the potential of data analytics to revolutionize industrial processes. By leveraging the power of Power BI, organizations can harness the value of their data to achieve significant improvements in efficiency, productivity, and overall performance.