Version 1
: Received: 26 August 2023 / Approved: 28 August 2023 / Online: 29 August 2023 (08:43:57 CEST)
How to cite:
Silva, J.; Coelho, P.; Saraiva, L.; Vaz, P.; Martins, P.; Henriques, J. Validating the Use of Mixed Reality in Industrial Quality Control: A Case Study. Preprints2023, 2023081909. https://doi.org/10.20944/preprints202308.1909.v1
Silva, J.; Coelho, P.; Saraiva, L.; Vaz, P.; Martins, P.; Henriques, J. Validating the Use of Mixed Reality in Industrial Quality Control: A Case Study. Preprints 2023, 2023081909. https://doi.org/10.20944/preprints202308.1909.v1
Silva, J.; Coelho, P.; Saraiva, L.; Vaz, P.; Martins, P.; Henriques, J. Validating the Use of Mixed Reality in Industrial Quality Control: A Case Study. Preprints2023, 2023081909. https://doi.org/10.20944/preprints202308.1909.v1
APA Style
Silva, J., Coelho, P., Saraiva, L., Vaz, P., Martins, P., & Henriques, J. (2023). Validating the Use of Mixed Reality in Industrial Quality Control: A Case Study. Preprints. https://doi.org/10.20944/preprints202308.1909.v1
Chicago/Turabian Style
Silva, J., Pedro Martins and João Henriques. 2023 "Validating the Use of Mixed Reality in Industrial Quality Control: A Case Study" Preprints. https://doi.org/10.20944/preprints202308.1909.v1
Abstract
Quality control is a critical component in industrial manufacturing, directly influencing efficiency, product reliability, and ultimately, customer satisfaction. In the dynamic environment of industrial manufacturing, traditional methods of inspection may not adequately meet the evolving complexity, necessitating innovative approaches to bolster precision and productivity.
In this study, we explore the application of mixed reality (MR) technology for real-time quality control in the assembly process. Our methodology involved the integration of smart glasses with a server-based image recognition system, designed to conduct real-time component analysis. The innovative aspect of our study lies in the harmonization of MR and computer vision algorithms, providing immediate visual feedback to inspectors and thereby improving the speed and accuracy of defect detection.
YOLOv8 have been adopted in this study for detection object model.
The project implementation occurred in a controlled environment to enable a comprehensive evaluation of the system functionality, the identification of possible problems and improvements in the system performance.
The results indicated the viability of mixed reality as a powerful tool for enhancing traditional inspection processes. The fusion of MR and computer vision offers possibilities for future advancements in industrial quality control, paving the way for more efficient and reliable manufacturing ecosystems.
Computer Science and Mathematics, Computer Vision and Graphics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
