Author(s)

Wankun Shang ¹

Affiliation(s)

¹ Nke Safety Apparel, 16616 Chandler RD, East Lansing, MI, 48823, United States

Corresponding Author

Wankun Shang

ABSTRACT

With the rapid development of intelligent manufacturing and smart factories, assembly line production processes have placed higher demands on the timeliness, accuracy, and stability of quality inspection. Traditional manual inspection and contact-based detection methods are increasingly unable to meet the requirements of modern industrial quality control under conditions of high production speed, complex operating environments, and multi-variety manufacturing. Owing to its non-contact nature, high efficiency, and ease of system integration, machine vision technology has gradually become an important technical approach for quality inspection on intelligent factory assembly lines. This paper focuses on the application of machine vision in assembly line quality inspection within intelligent factories. First, the typical requirements and key characteristics of assembly line quality inspection are analyzed, followed by a systematic discussion of the basic principles and key technologies of machine vision systems. On this basis, a machine vision system architecture oriented toward assembly line quality inspection is constructed, and the inspection workflow and implementation methods are examined in detail. Through a practical application case, the performance of the machine vision inspection system is evaluated in terms of detection accuracy, inspection efficiency, and operational stability. The results indicate that machine vision technology can effectively enhance the level of automation and consistency in assembly line quality inspection, providing reliable technical support for quality management in intelligent factories.

KEYWORDS

Machine vision; Intelligent factory; Assembly line; Quality inspection; Automated inspection

CITE THIS PAPER

Wankun Shang. Application Analysis of Machine Vision in Quality Inspection of Intelligent Factory Assembly Lines. Information Systems and Economics (2026). Vol. 7, No.1, 22-30. DOI: http://dx.doi.org/10.23977/infse.2026.070103.

REFERENCES

[1] Maganioti, A.E., Chrissanthi, H.D., Charalabos, P.C., Andreas, R.D., George, P.N. and Christos, C.N. (2010) Cointegration of Event-Related Potential (ERP) Signals in Experiments with Different Electromagnetic Field (EMF) Conditions. Health, 2, 400-406.
[2] Kim, Seung-Ho, and Min-Jae Park. "Vision-based defect detection for automated assembly lines using convolutional neural networks." Robotics and Computer-Integrated Manufacturing 82 (2023): 102531.
[3] Li, Haoran, Qiang Wang, and Zhenyu Liu. "Machine vision–driven online inspection for complex assembly processes in smart factories." IEEE Transactions on Industrial Informatics 19.8 (2023): 8451–8462.
[4] Sun, Peng, Xiaoyu Zhao, and Lei Zhang. "Real-time visual inspection of assembly defects under complex illumination conditions." Measurement 213 (2023): 112746.
[5] Rossi, Marco, Luca Bianchi, and Andrea Marinelli. "Edge-enabled machine vision architecture for quality inspection in intelligent assembly lines." Computers in Industry 150 (2023): 103944.
[6] Wang, Jiajun, Yifan Zhou, and Hongbin Liu. "A hybrid machine vision and deep learning framework for assembly line quality monitoring." Sensors 23.18 (2023): 7832.
[7] Müller, Tobias, and Stefan Wirtz. "Automated quality inspection in smart factories: A machine vision perspective." Procedia CIRP 119 (2023): 356–361.
[8] Chen, Rui, Bo Huang, and Shuang Li. "Vision-based inspection of electronic assembly using deep convolutional networks." IEEE Access 12 (2024): 21467–21478.
[9] Singh, Arjun, and Pankaj Kumar. "Machine vision applications for intelligent assembly line inspection: A review and case study." International Journal of Advanced Manufacturing Technology 125.1–4 (2024): 987–1003.
[10] Luo, Ming, Kai Xu, and Jianfeng Sun. "Multi-task visual inspection for mixed-model assembly lines in smart manufacturing." Advanced Engineering Informatics 59 (2024): 102191.
[11] García, Pablo, and Elena Fernández. "Vision-based quality control systems for flexible assembly lines in Industry 4.0." Journal of Intelligent Manufacturing 35.2 (2024): 455–469.
[12] Zhou, Tian, Pengfei Li, and Xuan Zhang. "Cloud–edge collaborative machine vision system for real-time assembly quality inspection." Future Generation Computer Systems 150 (2024): 364–375.
[13] Park, Jae-Won, and Hyun-Soo Lee. "Robust machine vision inspection for high-speed assembly lines using deep neural networks." Neural Computing and Applications 36.9 (2024): 5123–5137.
[14] Huang, Yifan, Chao Deng, and Wei Liu. "Adaptive visual inspection framework for intelligent factory assembly quality control." Engineering Applications of Artificial Intelligence 129 (2025): 106814.
[15] Novak, Daniel, and Petr Svoboda. "Intelligent machine vision systems for assembly line quality inspection in smart factories." Manufacturing Letters 38 (2025): 25–30.

Sponsors, Associates, and Links

---

• Accounting, Auditing and Finance
  
  
• Industrial Engineering and Innovation Management
  
  
• Tourism Management and Technology Economy
  
  
• Journal of Computational and Financial Econometrics
  
  
• Financial Engineering and Risk Management
  
  
• Accounting and Corporate Management
  
  
• Social Security and Administration Management
  
  
• Population, Resources & Environmental Economics
  
  
• Statistics & Quantitative Economics
  
  
• Agricultural & Forestry Economics and Management
  
  
• Social Medicine and Health Management
  
  
• Land Resource Management
  
  
• Information, Library and Archival Science
  
  
• Journal of Human Resource Development
  
  
• Manufacturing and Service Operations Management
  
  
• Operational Research and Cybernetics