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Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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S&M2963 Research Paper of Special Issue

Multi-objective Optimization of Lighting System Design for Automatic Image Measurement and Inspection Machine

Jian-Long Kuo

(Received December 6, 2021; Accepted April 7, 2022)

Keywords: lighting system, automatic image measurement, image inspection machine, multi-objective optimization

A 3D automatic sensing measurement system was developed to improve image processing technology for inspecting electronic parts. The developed system can automatically and rapidly measure a small workpiece, such as the width and center position of a circular aperture, and the distance, length, and angle of a geometrical shape. Through the optimization of the light system design, the 3D automatic measurement system can maximize the efficiency of the measurement. This measurement system includes two parts. The first part is an optics servo system including a standardized system, a turret-type magnification, and a zoom lens. The second part is a photo source servo system including an objective table, coaxial light, four-split ring light, and colored photo source. Each measurement routine of the testing workpiece must be programmed in advance by using QVPAK software. QVPAK controls multiple sensors such as a vision sensor, touch probe, continuous scanning devices, and special UMAP or LNP probes. The moving position of the 3D platform of the system can be controlled. The developed program can be transformed into a Visual Basic program. The system can automatically measure a large processed workpiece. Two objective functions, measuring precision and measuring time, are selected to improve the design. The response surface method is combined with a multiple performance characteristic index for multi-objective optimization, which is carried out using orthogonal particle swarm optimization. This experiment confirmed the short measuring time of the system. Human error can be avoided when using this system, and the accuracy may reach up to 0.002 mm. The proposed multi-objective optimization technique for detecting workpieces of electronic parts can increase the image processing efficiency. The discussed algorithm can be uploaded onto a cloud server to provide a 3D automatic measurement system for sensing and inspecting the workpieces of electronic parts. Intelligent manufacturing via a cloud server can be achieved in the era of Industry 4.0.

Corresponding author: Jian-Long Kuo




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