Lean Manufacturing Principles in Automotive Assembly Plants: A Comprehensive Analysis of Productivity Enhancement, Waste Reduction, and Operational Efficiency Through Value Stream Mapping
Keywords:
Lean Manufacturing, Value Stream Mapping, OEE, Kaizen, Just-In-Time, Total Productive Maintenance, Waste Reduction, AutomotiveAbstract
This study presents a systematic investigation into the application of lean manufacturing principles across three automotive assembly plants in North America and Europe over a 20- month longitudinal period. The research employs Value Stream Mapping (VSM), kaizen events, 5S methodology, Total Productive Maintenance (TPM), and Just- In- Time (JIT) production strategies within a structured implementation framework. A novel composite metric the Lean Efficiency Index (LEI) was developed to holistically measure operational improvement across multiple performance dimensions. Overall Equipment Effectiveness (OEE) improved from a baseline average of 57.9% to 84.1% across all plants, representing a mean absolute improvement of 26.2 percentage points. Production lead times were reduced by 38.4%, while work- in- progress (WIP) inventory decreased by 44.6%. Statistical analysis using paired t- tests confirmed all performance improvements were significant at p less than 0.01. Defect rates declined by 67.3% following implementation of Poka- Yoke error- proofing and Statistical Process Control (SPC) charting. The study contributes a replicable lean transformation roadmap demonstrating that phased implementation, strong change management, and cross- functional employee involvement are critical success factors for sustainable lean outcomes in high- volume manufacturing environments.Downloads
Download data is not yet available.
References
Downloads
Published
26-06-2024
Issue
Section
Articles
How to Cite
Lean Manufacturing Principles in Automotive Assembly Plants: A Comprehensive Analysis of Productivity Enhancement, Waste Reduction, and Operational Efficiency Through Value Stream Mapping. (2024). International Journal of Advance Industrial Engineering, 50-53. https://ijaie.evegenis.org/index.php/ijaie/article/view/1181
