Optimization of Mold Changeover Times in the Automotive Injection Industry Using Lean Manufacturing Tools and Fuzzy Logic to Enhance Production Line Balancing

The main thrust of the study is the need to cut down the time taken for mold changes in plastic injection molding which is fundamental to the productivity and efficiency of the process. The research encompasses Lean Manufacturing, DMAIC, and SMED which are improved using fuzzy logic and AI for rapid changeover optimization on the NEGRI BOSSI 650 machine. A decrease in downtime by 65% and an improvement in the Process Cycle Efficiency by 46.8% followed the identification of bottlenecks, externalizing tasks, and streamlining workflows. AI-driven analysis could make on-the-fly adjustments, which would ensure that resources are better allocated, and thus sustainable performance is maintained. The findings highlight how integrating Lean methods with advanced technologies enhances operational agility and competitiveness, offering a scalable model for continuous improvement in industrial settings.

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Publication Details

Published
2025-07-30
DOI
https://doi.org/10.3390/engproc2025097054
Citations
1
Primary Topic
Assembly Line Balancing Optimization
Type
article
Field-Weighted Citation Impact
1.24
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article

Optimization of Mold Changeover Times in the Automotive Injection Industry Using Lean Manufacturing Tools and Fuzzy Logic to Enhance Production Line Balancing

Omar Cherkaoui, Samir Tetouani, Aziz Soulhi, Abdelfattah Mouloud et al.
1 citations
Assembly Line Balancing Optimization
1.24
article

Optimization of Mold Changeover Times in the Automotive Injection Industry Using Lean Manufacturing Tools and Fuzzy Logic to Enhance Production Line Balancing

Omar Cherkaoui, Samir Tetouani, Aziz Soulhi, Abdelfattah Mouloud, Yasmine El Belghiti, Mehdi El Bouchti
article en
1 citations

Abstract

The main thrust of the study is the need to cut down the time taken for mold changes in plastic injection molding which is fundamental to the productivity and efficiency of the process. The research encompasses Lean Manufacturing, DMAIC, and SMED which are improved using fuzzy logic and AI for rapid changeover optimization on the NEGRI BOSSI 650 machine. A decrease in downtime by 65% and an improvement in the Process Cycle Efficiency by 46.8% followed the identification of bottlenecks, externalizing tasks, and streamlining workflows. AI-driven analysis could make on-the-fly adjustments, which would ensure that resources are better allocated, and thus sustainable performance is maintained. The findings highlight how integrating Lean methods with advanced technologies enhances operational agility and competitiveness, offering a scalable model for continuous improvement in industrial settings.

École Supérieure des Industries du Textile et de l'Habillement (MA), National School of Mineral Industry (MA)
Industry, innovation and infrastructure
Openalex Percentile: Top 17%
Assembly Line Balancing Optimization
1.24
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Optimization of Mold Changeover Times in the Automotive Injection Industry Using Lean Manufacturing Tools and Fuzzy Logic to Enhance Production Line Balancing — Omar Cherkaoui, Samir Tetouani, et al. · (2025) | TGRS Research Map | TGRS