Operational strategy for enhancing automotive parts manufacturing quality and productivity through cycle time optimization

Abstract

Developing effective operational strategies is essential for automotive parts manufacturers to improve quality and productivity while meeting market demand with limited resources. This study empirically validates an integrated operational strategy in which Cycle Time Reduction serves as a primary capability for improving downstream manufacturing performance. A quantitative explanatory approach was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM) based on data from 100 respondents in an automotive parts manufacturing company. The model examined relationships among Cycle Time Reduction, Machining Operational Performance, Burritori Operational Performance, Assembly Operational Performance, Final Inspection Performance, and Overall Manufacturing Productivity. Results show that Cycle Time Reduction significantly improves machining (β = 0.510) and burritori performance (β = 0.388). Machining (β = 0.295) and burritori performance (β = 0.392) positively influence assembly performance, which strongly affects final inspection (β = 0.586) and overall manufacturing productivity (β = 0.598). The model explains 26.0%, 15.0%, 37.2%, 34.4%, and 35.8% of variance in these outcomes, respectively. The findings confirm that Cycle Time Reduction functions as an integrated operational strategy, enabling cascading improvements across the manufacturing value chain and supporting lean manufacturing practices.