This document is the final report for an automated optical inspection system project. The system was designed to detect errors in printing up to 0.5mm at a rate of 1 image per 8 seconds while covering an area of 32" x 41". It uses an array of two cameras mounted on an adjustable arch to capture images which are processed by software on a laptop to detect errors and notify workers. The project was tested and modifications are suggested for future improvements.
7. 1. Detect the presence of multiple errors on a single label on a multilabel sheet
2. Detect the presence of dots and pin holes of 0.5mm diameter or greater
3. Detect the presence of dust particles or their results of 0.5mm diameter or greater
Beyond these error detection specifications, other specifications are necessary to be met
in order to create a system that will operate efficiently with Ampco’s current printing method.
The majority of errors occur during the screenprinting stage of label production. The error
detection system must, therefore, interface with the printer used by Ampco. The primary
integration specifications are:
1. Process images at the same rate as prints are produced (approximately 1 image per 8 seconds)
2. Selfsupport in such a way as to not interfere with the printing process
3. Process prints up to a maximum size of approximately 32” x 41”
Once the system detects an error, it is necessary to remove that print. Since most errors
are caused by a dirty screen with residue ink[2]
, screen cleaning is required. The cleaning is to be
done by a worker.
8. 1.3 Initial Design
Upon examining the needs and specifications, the problem was broken down into 5
categories or stages:
1. Acquire Ideal Label for Comparison (Optional)
2. Capture Label for Processing
3. Mount Capture Technology
4. Process Image to Detect Presence of Errors
5. Notify Worker of Error
Figure 1: Flowchart of the process
Multiple methods to detect labels, mount the system, and to analyze the labels were
investigated. These included which types of cameras to use, the shape and material needed for
the mount, and what system was required to run the code for analysis.
By comparing various aspects of three areas of interest (camera type and array, mounting
hardware, computer hardware) using design matrices, it was finalized to use a system comprised
of two Canon PowerShot ELPH130IS cameras to capture the image, a three piece arch to mount
the system, and a laptop running on Linux to process the image[3]
.