International Journal of Industrial Engineering and Management

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Original Research Article

Enhancing production efficiency through value stream mapping and simulation in the automotive industry

Josue Velázquez-Serrrano
Autonomous University of Hidalgo, Academic Area of Engineering, Mineral de la reforma, México
Hector Rivera Gomez
Université du Québec, École de technologie supériure, Montreal, Canadá
Sergio Blas Rámirez-Reyna
Autonomous University of Hidalgo, Academic Area of Engineering, Mineral de la reforma, México
Rafael Granillo-Macias
Autonomous University of Hidalgo, Campus Ciudad Sahagún, Tepeapulco, México
Oscar Montaño-Arango
Autonomous University of Hidalgo, Academic Area of Engineering, Mineral de la reforma, México

Published 2025-08-01

abstract views: 29 // FULL TEXT ARTICLE (PDF): 9


Keywords

  • value stream map,
  • lean manufacturing,
  • simulation,
  • automotive sector

How to Cite

Velázquez-Serrrano, J., Rivera Gomez, H., Rámirez-Reyna, S. B., Granillo-Macias, R., & Montaño-Arango, O. (2025). Enhancing production efficiency through value stream mapping and simulation in the automotive industry. International Journal of Industrial Engineering and Management, article in press. https://doi.org/10.24867/IJIEM-386

Abstract

Lean manufacturing and Value Stream Mapping (VSM) have long helped automotive companies uncover waste and streamline production. However, most studies treat VSM and simulation in isolation or focus on a single product line, leaving a gap in how to integrate them dynamically. This paper addresses these gaps by introducing the Multi-Machine Activity (MMA) approach to group-related tasks and operators into coherent cells for simultaneous analysis. This study aims to improve production efficiency by integrating VSM and discrete‐event simulation via the MMA approach. We mapped current and future states of two steering-column assembly lines, collected cycle-time and inventory data, and validated improvement scenarios using simulation. The results show that non-value-added time reduces from 7.56 to 2.69 days for the guided model, and from 5.88 to 2.43 days for the nonguided one, while cutting lead time by over 60%. The contribution of the paper is threefold: we formalize MMA as a theoretical tool for dynamic VSM; we demonstrate its capabilities in a dual-model comparison; and we quantify total bottleneck elimination, thereby advancing lean-simulation integration theory. These findings confirm that proposed approach enhances decision-making. 

Article history: Received (February 7, 2025); Revised (May 12, 2025); Accepted (May 14, 2025); Published online (August 1, 2025)

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