QUALITY CONTROL IN AUTOMOBILE FACTORIES: PROBLEMS AND SOLUTIONS
Section: GENERAL SECTION
Authors:
1.
LLC "Haval Motor Manufacturing Rus"
Russian Federation
Russian Federation
2.
Bauman Moscow State Technical University
Russian Federation
Russian Federation
3.
Voronezh State University of Forestry and Technologies
Russian Federation
Russian Federation
4.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation
Russian Federation
5.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
Type:
Сonference article
Pages:
from 67
to 77
Published:
12.12.2025
Subject area:
UDC 629.113
Language:
Russian
Keywords:
quality control, automotive industry, Industry 4.0, digital twin, machine vision, robotic systems, predictive analytics, quality management system (QMS), production processes, flaw detection, intelligent manufacturing, end-to-end traceability
Abstract (English):
This study provides a comprehensive analysis of modern quality control systems in the automotive industry, identifies key problem areas, and proposes scientifically based solutions. Using a systems approach, it examines the transformation of the quality control paradigm from reactive defect detection to proactive prevention using Industry 4.0 technologies. The theoretical principles are illustrated with a practical case study of implementing advanced techniques at the production site of Haval Motor Manufacturing Rus LLC. Particular attention is paid to the synergistic effect of integrating robotic systems, machine vision systems, and end-to-end digitalization of the production cycle. The results of this study can be applied to improving quality management systems at mechanical engineering enterprises.
This study provides a comprehensive analysis of modern quality control systems in the automotive industry, identifies key problem areas, and proposes scientifically based solutions. Using a systems approach, it examines the transformation of the quality control paradigm from reactive defect detection to proactive prevention using Industry 4.0 technologies. The theoretical principles are illustrated with a practical case study of implementing advanced techniques at the production site of Haval Motor Manufacturing Rus LLC. Particular attention is paid to the synergistic effect of integrating robotic systems, machine vision systems, and end-to-end digitalization of the production cycle. The results of this study can be applied to improving quality management systems at mechanical engineering enterprises.
Keywords:
quality control, automotive industry, Industry 4.0, digital twin, machine vision, robotic systems, predictive analytics, quality management system (QMS), production processes, flaw detection, intelligent manufacturing, end-to-end traceability
quality control, automotive industry, Industry 4.0, digital twin, machine vision, robotic systems, predictive analytics, quality management system (QMS), production processes, flaw detection, intelligent manufacturing, end-to-end traceability
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