A vision system for an automatic assembly machine of electronic components

You, Bum-Jae; Oh, Yung-Hwan; Bien, Zeungnam

doi:10.1109/41.103429

Cited by 14 publications

(1 citation statement)

References 13 publications

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“…Computer vision has become increasingly important in regulated industrial applications over time, and it now offers innovative approaches for the sector of industrial automation. Computer vision applications have greatly assisted a number of industries, including the manufacturing of electronic components, including more effective manufacturing processes [11,12], fabric defect and detection inspection [12], automated food sorting system or techniques [13][14][15], flexible automated assembly systems [16], incorporating circuits inspection [17]. Machine vision systems are often classified into four categories [18]: automatic visual inspection systems, parts recognition, robotic supervision, and process control.…”

Section: Previous Studies In Vision Inspection Systemmentioning

confidence: 99%

Implementing circularity measurements in industry 4.0-based manufacturing metrology using MQTT protocol and Open CV: A case study

Saif,

Yusof,

Rus

et al. 2023

PLoS ONE

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In the context of Industry 4.0, manufacturing metrology is crucial for inspecting and measuring machines. The Internet of Things (IoT) technology enables seamless communication between advanced industrial devices through local and cloud computing servers. This study investigates the use of the MQTT protocol to enhance the performance of circularity measurement data transmission between cloud servers and round-hole data sources through Open CV. Accurate inspection of circular characteristics, particularly roundness errors, is vital for lubricant distribution, assemblies, and rotational force innovation. Circularity measurement techniques employ algorithms like the minimal zone circle tolerance algorithm. Vision inspection systems, utilizing image processing techniques, can promptly and accurately detect quality concerns by analyzing the model’s surface through circular dimension analysis. This involves sending the model’s image to a computer, which employs techniques such as Hough Transform, Edge Detection, and Contour Analysis to identify circular features and extract relevant parameters. This method is utilized in the camera industry and component assembly. To assess the performance, a comparative experiment was conducted between the non-contact-based 3SMVI system and the contact-based CMM system widely used in various industries for roundness evaluation. The CMM technique is known for its high precision but is time-consuming. Experimental results indicated a variation of 5 to 9.6 micrometers between the two methods. It is suggested that using a high-resolution camera and appropriate lighting conditions can further enhance result precision.

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