A System-Dynamics-Based Simulation to Assess the Behavior Over Time of the Production Error Rate Caused by New Product Introduction in General Assembly Activities of an Automotive Manufacturing Facility

This research paper investigates the critical dynamics of engineering changes in the automotive industry, focusing on the New Product Engineering Change Administration (ECA) in General Assembly operations. As automotive companies strive to align their new models with market demands, regulatory requirements, and technological advancements, managing engineering changes efficiently becomes paramount. This study employs System Dynamics modeling to simulate the impacts of these changes on the production error rates during the initial phases of new vehicle introductions. Through the creation of causal loop diagrams and stock and flow models, developed in collaboration with industry professionals, we analyze the interdependencies and feedback loops inherent in the automotive production system. Our model specifically addresses the General Assembly New Product ECA, which deals extensively with the assembly of complex exterior and interior vehicle components. We evaluate various scenarios to determine the effect of different engineering changes on production outcomes, such as delay times, error rates, and overall system responsiveness. The findings highlight significant variances in error rates and introduce strategies to mitigate risks associated with the implementation of engineering changes. The study underscores the necessity for automotive manufacturers to adopt robust system dynamics models to optimize engineering change processes, thereby enhancing product quality and reducing time-to-market for new vehicle launches.

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Publication Details

Published
2024-08-04
DOI
https://doi.org/10.23919/picmet64035.2024.10653377
Citations
6
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
2.09
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article

A System-Dynamics-Based Simulation to Assess the Behavior Over Time of the Production Error Rate Caused by New Product Introduction in General Assembly Activities of an Automotive Manufacturing Facility

R. Cervantes, Andreas Topp, G.L. Emmett, Armando Elizondo-Noriega et al.
6 citations
Manufacturing Process and Optimization
2.09
article

A System-Dynamics-Based Simulation to Assess the Behavior Over Time of the Production Error Rate Caused by New Product Introduction in General Assembly Activities of an Automotive Manufacturing Facility

R. Cervantes, Andreas Topp, G.L. Emmett, Armando Elizondo-Noriega, José L. Ceciliano-Meza, A.A. Castillo-Paz, A.S. Pérez, J.F. Piňal-Moctezuma, J. Rouen, R. Linarr, L. Duarte-Pacheco
article en
6 citations

Abstract

This research paper investigates the critical dynamics of engineering changes in the automotive industry, focusing on the New Product Engineering Change Administration (ECA) in General Assembly operations. As automotive companies strive to align their new models with market demands, regulatory requirements, and technological advancements, managing engineering changes efficiently becomes paramount. This study employs System Dynamics modeling to simulate the impacts of these changes on the production error rates during the initial phases of new vehicle introductions. Through the creation of causal loop diagrams and stock and flow models, developed in collaboration with industry professionals, we analyze the interdependencies and feedback loops inherent in the automotive production system. Our model specifically addresses the General Assembly New Product ECA, which deals extensively with the assembly of complex exterior and interior vehicle components. We evaluate various scenarios to determine the effect of different engineering changes on production outcomes, such as delay times, error rates, and overall system responsiveness. The findings highlight significant variances in error rates and introduce strategies to mitigate risks associated with the implementation of engineering changes. The study underscores the necessity for automotive manufacturers to adopt robust system dynamics models to optimize engineering change processes, thereby enhancing product quality and reducing time-to-market for new vehicle launches.

Tecnológico de Monterrey (MX)
Openalex Percentile: Top 12%
Manufacturing Process and Optimization
2.09
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