scholarly journals Autonomous Robot-Guided Inspection System Based on Offline Programming and RGB-D Model

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4008 ◽  
Author(s):  
Amit Kumar Bedaka ◽  
Alaa M. Mahmoud ◽  
Shao-Chun Lee ◽  
Chyi-Yeu Lin
Keyword(s):  
Visual Information ◽  
Industrial Robot ◽  
Interactive System ◽  
Inspection System ◽  
Present System ◽  
Inspection Planning ◽  
Automatic Optical Inspection ◽  
Industrial Manipulator ◽  
Optical Inspection ◽  
Offline Programming

Automatic optical inspection (AOI) is a control process for precisely evaluating the completeness and quality of manufactured products with the help of visual information. Automatic optical inspection systems include cameras, light sources, and objects; AOI requires expert operators and time-consuming setup processes. In this study, a novel autonomous industrial robot-guided inspection system was hypothesized and developed to expedite and ease inspection process development. The developed platform is an intuitive and interactive system that does not require a physical object to test or an industrial robot; this allows nonexpert operators to perform object inspection planning by only using scanned data. The proposed system comprises an offline programming (OLP) platform and three-dimensional/two-dimensional (3D/2D) vision module. A robot program generated from the OLP platform is mapped to an industrial manipulator to scan a 3D point-cloud model of an object by using a laser triangulation sensor. After a reconstructed 3D model is aligned with a computer-aided design model on a common coordinate system, the OLP platform allows users to efficiently fine-tune the required inspection positions on the basis of the rendered images. The arranged inspection positions can be directed to an industrial manipulator on a production line to capture real images by using the corresponding 2D camera/lens setup for AOI tasks. This innovative system can be implemented in smart factories, which are easily manageable from multiple locations. Workers can save scanned data when new inspection positions are included based on cloud data. The present system provides a new direction to cloud-based manufacturing industries and maximizes the flexibility and efficiency of the AOI setup process to increase productivity.

Development of an Automatic Optical Inspection System and its Application to Defect Examination

2013 ◽  
Vol 479-480 ◽  
pp. 636-640
Author(s):  
Jong Hann Jean ◽  
Chia Hong Chen ◽  
Tyng Bin Huang ◽  
Sheng Hong Tsai
Keyword(s):  
Inspection System ◽  
Large Object ◽  
Support Functions ◽  
Automatic Optical Inspection ◽  
Optical Inspection ◽  
Detection Tool ◽  
Measurement And Analysis ◽  
Processing Measurement ◽  
Inspection Machine ◽  
Optical Inspection System

In this paper, we have designed and integrated an automatic optical inspection system, emphasizing on software implementation of the image processing, measurement and analysis utilities. As for the hardware equipments, we design an LED illumination unit and the custom-tailored machinery. By comparing the support functions of several main import brands of the optical inspection machine, we propose an optical inspecting procedure. By using the Windows-based user interface, we implement nine inspecting software tools, namely, the average gray level tool, the thresholding tool, the positioning tool, the edge detection tool, the binary large object (BLOB) tool, the template building tool, the smart matching tool, the inspection sequence tool, and the platform operation tool. All these tools can be used in an inspection with single operation and can also be arranged in a proper sequence of operations to fulfill a complicated inspection procedure. We use several part sample images with defects provided by the supplier to verify our fulfilled system.

Statistical Process Monitoring System for SMT Industry Using Automatic Optical Inspection System

2008 ◽  
Vol 580-582 ◽  
pp. 561-564 ◽  
Author(s):  
Hee Y. Kim ◽  
Seung Soo Han ◽  
Sung Bok Hong ◽  
Sang Jeen Hong
Keyword(s):  
Quality Control ◽  
Control Method ◽  
Statistical Quality Control ◽  
Inspection System ◽  
Measured Variable ◽  
Statistical Process ◽  
Automatic Optical Inspection ◽  
Optical Inspection ◽  
Variable Data ◽  
Board Level

As the demand of higher throughput in high volume surface mounting technology (SMT) industry, inspection and testing have been notably emphasized. To alleviate concerns associated with board level soldering inspection, automatic optical inspection (AOI) has been actively used in SMT industry [1]. In this paper, statistical quality control method has been applied for board level inspection to maximize the performance of a commercially available AOI system. Considering its complication of SMT assembled board, implementing the quality control scheme for the measured variable data is fairly expensive. However, the proposed system efficiently utilizes both attribute and variable data collected for the daily/weekly based production yield reports, and further utilize as a method for in-line diagnostics in SMT manufacturing process.

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