TY - GEN
T1 - Low-Cost Automated Visual Screw Inspection System
AU - Li, Yiran
AU - Li, Jiayi
AU - Yang, Xiaoying
AU - Li, Cheng'ao
AU - Xiong, Xihan
AU - Fang, Yutong
AU - Ding, Shusheng
AU - Cui, Tianxiang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Despite the significant achievements in the development of automation technologies, the application of autonomous robots to improve the production efficiency of small-scale indus-tries has been largely ignored. While there has been excellent progress in industrial image processing systems implementation, most of the work has focused on a unique aspect of specific objects rather than introducing a general inspection system. Thus, this paper discusses the critical industrial topic of quality control, which develops rapidly through the use of autonomous systems. Given the high cost of implementing automated systems, this paper presents an affordable low-budget solution for the visual inspection system. This method of inspecting screw dimensions consists of four visual inspection parts and a special mechanical supporting structure. The designed system was able to check the overall screw dimensions, including screw head diameter, screw head driven type, screw length, screw thread length, and screw head thickness. It could also separate the qualified screws from the unqualified ones after the inspection process. The accuracy of most inspection cases is 100%, meaning the error ranges within 0.1mm, which meets all the non-negotiable requirements and most of the target requirements. The visual inspection parts can be further enhanced by building a template matching library that includes different angles of the screw head or by using Hough Transform to identify the defect types of the screw thread.
AB - Despite the significant achievements in the development of automation technologies, the application of autonomous robots to improve the production efficiency of small-scale indus-tries has been largely ignored. While there has been excellent progress in industrial image processing systems implementation, most of the work has focused on a unique aspect of specific objects rather than introducing a general inspection system. Thus, this paper discusses the critical industrial topic of quality control, which develops rapidly through the use of autonomous systems. Given the high cost of implementing automated systems, this paper presents an affordable low-budget solution for the visual inspection system. This method of inspecting screw dimensions consists of four visual inspection parts and a special mechanical supporting structure. The designed system was able to check the overall screw dimensions, including screw head diameter, screw head driven type, screw length, screw thread length, and screw head thickness. It could also separate the qualified screws from the unqualified ones after the inspection process. The accuracy of most inspection cases is 100%, meaning the error ranges within 0.1mm, which meets all the non-negotiable requirements and most of the target requirements. The visual inspection parts can be further enhanced by building a template matching library that includes different angles of the screw head or by using Hough Transform to identify the defect types of the screw thread.
KW - Automated quality control
KW - Computer-assisted visual inspection
KW - Industrial computer vision
KW - Low-cost
UR - http://www.scopus.com/inward/record.url?scp=85182950476&partnerID=8YFLogxK
U2 - 10.1109/SSCI52147.2023.10371885
DO - 10.1109/SSCI52147.2023.10371885
M3 - Conference contribution
AN - SCOPUS:85182950476
T3 - 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
SP - 1735
EP - 1740
BT - 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
Y2 - 5 December 2023 through 8 December 2023
ER -