Business and Technological Processes Optimization in Automotive Manufacturing: Continuous Improvement through Process Capability, Operational Effectiveness, and Return on Investment

Abstract

This study develops and empirically validates an integrated monitoring framework linking technological, operational, and financial performance indicators in automotive manufacturing. While process capability (Cpk), overall equipment effectiveness (OEE), and return on investment (ROI) are widely applied, their interrelationships are rarely examined within a unified empirical framework in real production environments. The proposed model is implemented within a business and technological processes monitoring system for the production of automotive daytime running lights (DRL), combining real-time measurement, automated data acquisition, and structured process optimization. A multi-phase implementation strategy enabled the transition from manual to fully automated monitoring, supported by more than 1,400 measurements collected across key technological operations in accordance with international standards. A longitudinal case study design was applied, and statistical analyses, including correlation and regression methods, were used to examine relationships between process capability, operational performance, and financial outcomes. The results show that systematic optimization increased equipment effectiveness from 78.36 % to 85.41 % and financial return from €2.9 million to €7.98 million, while achieving process capability levels above the required thresholds (Cpk > 2). A strong statistical relationship was identified between OEE and ROI, whereas the relationship between process capability Cpk and OEE was not statistically confirmed as a direct effect. The findings indicate that technological, operational, and financial indicators are interconnected but not strictly linear, highlighting the importance of integrated monitoring for understanding performance dynamics in manufacturing systems. The proposed framework provides an empirically grounded approach for linking process stability, operational efficiency, and financial outcomes, supporting performance evaluation and continuous improvement in automotive manufacturing.