THE IMPACT OF QUALITY CONTROL STRATEGIES ON MEASUREMENT PROCESS OPTIMIZATION AND OPERATIONAL PERFORMANCE: A CASE STUDY IN AUTOMOTIVE MANUFACTURING

Abstract

Maintaining accurate and reliable measurement systems is essential for ensuring product quality and operational excellence in precision manufacturing industries. This study investigates the impact of quality control strategies on measurement process optimization and manufacturing performance through a case study conducted in an automotive component manufacturing environment. The research employed a quantitative case study approach using production records, Measurement System Analysis (MSA), Gauge Repeatability and Reproducibility (Gauge R&R), Statistical Process Control (SPC), Pareto analysis, Fishbone analysis, scatter diagrams, and process capability analysis to identify measurement-related challenges and evaluate the effectiveness of corrective actions. The findings revealed that measurement system deficiencies, including overdue instrument calibration, inadequate operator competency, lack of standardized measurement procedures, and environmental variations, were the primary contributors to process instability and product rejection. Following the implementation of integrated quality control strategies comprising calibration system enhancement, standardized operating procedures, environmental control, operator training, and continuous SPC monitoring, substantial improvements were achieved across key operational indicators. The process capability index (Cpk) increased from 0.61 to 1.58, Gauge R&R improved from 41.1% to 11.8%, the rejection rate decreased from 4.8% to 0.6%, monthly customer complaints declined by 85.3%, and quality-related costs were reduced by approximately 81.3%, resulting in estimated annual savings of PKR 37 million. These findings demonstrate that systematic quality control strategies significantly enhance measurement process reliability, improve production performance, and support continuous improvement in manufacturing organizations. The study provides practical guidance for production managers and quality professionals seeking to strengthen operational performance through structured quality management practices and evidence-based decision-making