Analysing machine performance is important to increase productivity, and efficiency and to reduce the overall cost of several industries. Important measures like throughput, utilization rate, downtime, and quality metrics like defect rates help measure performance accurately. Root Cause Analysis (RCA), Statistical Process Control (SPC), and benchmarking are the methods that help identify and set realistic goals. Accurate analysis depends on accurate data gathering, irrespective of whether it is done manually or automatically. Instruments like MES and ERP systems help in performance tracking and visualization. Future advances are expected to focus on artificial intelligence (AI) and machine learning for improved analysis, with constant monitoring and feedback loops ensuring continuous improvements.