Digitalizing manufacturing support processes is essential for improving their efficiency, as well as enhancing decision making. This study focuses on the digital transformation of the tightening confirmation process in an automotive company, replacing a manual, paper-based system with an automated solution. The original process was time-consuming and lacked structured data analysis, making traceability and quality control difficult. To address these issues, a digital system was developed using Microsoft Excel with VBA for data entry, and Python for automated data analysis. The new system streamlined operations by reducing manual tasks, eliminating paper records, and enabling real-time monitoring. These improvements boosted data accuracy, reduced administrative workload, and strengthened quality assurance in a critical process. Additionally, automated data analysis provided valuable insights, supporting decision-making and continuous process improvement. This study contributes to the existing literature by offering a practical example of digitalization in quality control, addressing a gap in research on small-scale digital solutions in manufacturing. Future developments could integrate predictive analytics, expand the system to multiple workstations, and connect it with different company systems to maximize efficiency and its impact.