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The process ensures the automated production and inspection of GV12 valve-lifters to maintain quality standards, with a focus on detecting chip formation on the workpiece surface. A batch of workpieces, i.e., parts that are utilized for the assembly of more complex products, is automatically produced and inspected to ensure the quality of the parts. The integration of data collection, compression, and analysis facilitates efficient monitoring and decision-making throughout the production cycle. Main Machinery Involved: Milling Machine Measuring Machine (KEYENCE) for optical measurement of part diameter Independent Lift (LIFT) for transporting parts through the measuring machine Robot for handling the workpieces. This process is characterized by the following steps: Firstly, the production run details are fetched from the Manufacturing Execution System (MES) to initiate the manufacturing process. Then each GV12 valve-lifter is crafted from raw material using a milling machine. Throughout this process, various metrics such as vibration, noise, energy consumption of machine parts, and tool positioning data are continuously monitored and logged for analysis. After manufacturing, each valve-lifter undergoes measurement using a specialized measuring machine (KEYENCE). This machine conducts an optical measurement of the part diameter and generates a detailed point-cloud representation of the part's surface with an accuracy of 0.001 millimeters. The measurement data obtained from this step can be extensive and is stored in the process log for further analysis. Given the potentially large volume of measurement data generated per workpiece, a data compression task is employed to efficiently store this information in the process log. The stored data from manufacturing and measurement processes are analyzed to assess the quality of each produced valve-lifter. A key focus of this analysis is the detection of chip formation on the surface of the workpieces. By scrutinizing the collected data, the system determines whether chips have formed and evaluates their severity. This analysis outcome plays a crucial role in decision-making regarding the disposition of the workpieces.