Studies on heavy-machinery maintenance show that long repair cycles, operational variability, and load imbalances reduce service reliability, especially in workshops with limited resources. In this context, chassis repair presents frequent delays that affect customers’ operational continuity. This research proposes an integrated operational model based on Job Design, Standard Work, and Heijunka to improve process stability and delivery service performance. The validation was carried out through a hybrid approach that combined pilot implementation tests with discrete-event simulation in Arena and statistical distribution fitting using Input Analyzer with a 95% confidence level. The results show significant improvements: the simulated average total time in the system decreased from 134.46 to 114.47 days (−14.87%) , and operational capacity increased from 35 to 44 repaired vehicles (+25.71%) within the same time horizon. Likewise, average waiting time in dismantling decreased from 93.68 to 76.72 days, representing an improvement of approximately 18.1%, while workspace utilization increased from 70.75% to 86.72%, reflecting better use of available resources. These findings confirm the effectiveness of the proposed model and provide practical implications for maintenance organizations seeking to improve operational reliability, reduce internal congestion, and optimize resource use in highly uncertain environments. The study suggests exploring advanced Lean integrations and data-based approaches to expand the impact of future optimization initiatives.

Keywords

Lean Production; Job Design; Standard Work; Heijunka; Corrective Maintenance.