The automotive industry demands high standards of efficiency and reliability in order to remain competitive. This study addresses the optimization of an automatic production cell (“Line X”) dedicated to the manufacture of cables for automotive latches, which initially presented critical performance levels, with an average Overall Equipment Effectiveness (OEE) of 42%, significantly below the strategic target of 85%. Adopting the Design Science Research (DSR) methodology, the research diagnosed the root causes of inefficiency, mainly associated with the electric cutting process, cable insertion, and component feed stability. Targeted technical interventions were designed and implemented, including the development of copper-beryllium electrodes with tungsten tips to reduce wear, a new symmetrical electrode opening system to eliminate burrs, and a spiral cleaning tool to prevent insertion failures. The results demonstrated a substantial improvement in operational stability: corrected OEE stabilized above 80%, reaching a peak value of 87.7%, clearly highlighting the effectiveness of the implemented technical improvements, while performance consistently exceeded the 95% target. Additionally, there was a dramatic reduction in non-compliance rates (ppm), validating the effectiveness of the engineering solutions. This work confirms that technical redesign focused on critical process steps is decisive in recovering the productivity and availability of automatic assembly lines.
- Open Access
- Article
Enhancing an Automatic Automotive Cable Assembly Line: A Design Science Research Approach to Improve OEE
- Rodrigo Lopes 1,
- Raul D. S. G. Campilho 1,2,
- Arnaldo G. Pinto 1,
- Isabel M. Pinto 1,3,*,
- Marlene Brito 1,
- Alexandra Gavina 1,3,
- Isabel P. Figueiredo 1,3
Author Information
Received: 26 Nov 2025 | Revised: 23 May 2026 | Accepted: 22 Jun 2026 | Published: 28 Sep 2026
Abstract
Graphical Abstract
Keywords
overall equipment effectiveness (OEE) | automotive industry | electric cable cutting | design science research | process optimization
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