LAPSE:2023.6031
Published Article
LAPSE:2023.6031
Predictive Process Adjustment by Detecting System Status of Vacuum Gripper in Real Time during Pick-Up Operations
Sujeong Baek, Dong Oh Kim
February 23, 2023
Abstract
In manufacturing systems, pick-up operations by vacuum grippers may fail owing to manufacturing errors in an object’s surface that are within the allowable tolerance limits. In such situations, manual interference is required to resume system operation, which results in considerable loss of time as well as economic losses. Although vacuum grippers have many advantages and are widely used in the industry, it is highly difficult to directly monitor the current machine status and provide appropriate recovery feedback for stable operation. Therefore, this paper proposes a method to detect the success or failure of a suction operation in advance by analyzing the amount of outlet air pressure in the Venturi line. This was achieved by installing an air pressure sensor on the Venturi line to predict whether the current suction action will be successful. Through empirical experiments, it was found that downward movements in the z-axis of the vacuum gripper can easily rectify a faulty gripper suction operation. Real-time monitoring results verified that predictive process adjustment of the pick-up operation can be performed by modifying the z-position of the vacuum gripper.
Keywords
Fault Detection, predictive process adjustment, real-time monitoring, sensor data, vacuum gripper
Suggested Citation
Baek S, Kim DO. Predictive Process Adjustment by Detecting System Status of Vacuum Gripper in Real Time during Pick-Up Operations. (2023). LAPSE:2023.6031
Author Affiliations
Baek S: Department of Industrial Management Engineering, Hanbat National University, 125 Dongseo-Daero, Yuseong-Gu, Daejeon 34158, Korea
Kim DO: Department of Industrial Management Engineering, Hanbat National University, 125 Dongseo-Daero, Yuseong-Gu, Daejeon 34158, Korea
Journal Name
Processes
Volume
9
Issue
4
First Page
634
Year
2021
Publication Date
2021-04-05
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr9040634, Publication Type: Journal Article
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LAPSE:2023.6031
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https://doi.org/10.3390/pr9040634
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Feb 23, 2023
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CC BY 4.0
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Feb 23, 2023
 
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