To ensure quality standards in automated production, it is necessary to implement a quality management system (QMS) at all stages. Critical control points (CCP) should be monitored using sensors and IoT devices to monitor parameters in real time. It is important to use machine learning systems to analyze data and predict potential defects based on historical information. Regular equipment calibrations and audits should become part of the production culture. Implementation of Lean and Six Sigma methodologies will minimize waste and variability. Training personnel in quality control issues completes the cycle of ensuring standards.

Use advanced technologies like real-time monitoring systems and AI-driven inspection tools to detect defects early in the process and initiate action to over come quality issues TQM is a philosophy-driven yet proven method for improving quality. It seeks to incorporate quality into the company's culture, train all staff to identify problems, and empower them to intervene when necessary. Today’s TQM programs are software-driven and become much more potent for controlling and ensuring quality when linked to a data management platform like Machine Metrics.