Can machine vision inspection replace human eye inspection?

The visual inspection system uses industrial cameras instead of human eyes to complete functions such as identification, measurement, and positioning. The general visual inspection system is composed of a camera, lens, and light source. It can replace manual inspection of barcode characters, cracks, packaging, surface layer integrity, dents, etc. The use of visual inspection systems can effectively improve the inspection speed and accuracy of the production line, greatly improve output and quality, reduce labor costs, and prevent misjudgments due to human eye fatigue.

To discuss this issue, it needs to be divided into two aspects, one is cost and the other is technology.

Cost Considerations

If an enterprise wants to carry out machine vision inspection instead of human eye inspection, it needs to be upgraded. This is a difficult expenditure for small and medium-sized enterprises. At the same time, after using machine vision inspection, relevant talents are also needed, which is another expense. Therefore, at present, machine vision inspection instead of human eye inspection only appears in some large and powerful enterprises. Small and medium-sized enterprises will not consider it unless there is a need to upgrade and replace.

Technological Limitations

Compared with cost, technology is the key reason that limits the replacement of human eye detection by machine vision detection. Currently, lighting is a difficult point in the application of machine vision detection. If the obtained pictures require careful consideration before the results can be given, then the algorithm will be too difficult to implement. On the other hand, if the lighting is done well in the early stage and the features to be detected are highlighted, the algorithm is not difficult.

Machine vision inspection is currently much more intelligent than humans, mainly reflected in the identification of unexpected defects. At present, machine vision is given some specific defect patterns to identify whether they have occurred. This means that sometimes there are some obvious defects, just because they have not occurred before or the occurrence patterns are diverse, so no specific information is stored in the machine vision system, leading to missed inspections in machine vision inspections. When such errors are manually inspected, even if the defect has not been discovered before, there is still a high probability of discovery through one's own judgment.

There are currently many smart camera suppliers, as well as many analysis software suppliers. Although the software algorithms released by each have their own characteristics, they are actually very similar in practicality and have very similar functions. But they all process the pictures obtained by the camera according to fixed patterns and steps, analyze certain expected features from the pictures, and then give the judgment results. No one has a revolutionary intelligent algorithm.

Machine vision inspection will not be able to achieve human-like intelligent recognition in the short term because the theories related to image analysis algorithms are not yet ready.

Advantages and Future Outlook

However, the biggest advantage of machine vision inspection compared to human eye inspection is stability. When manual inspection is performed with the naked eye, even if a good reward and punishment system is designed, there may still be a missed detection rate. However, machine vision inspection will not cause missed detection due to negligence. Therefore, in terms of stable detection that is most needed for factory inspection, machine vision inspection is better than human eye inspection. Even if the special non-algorithm defects mentioned above occur, it is a small probability event after all. Machine vision inspection can still detect frequently occurring defects.

At the same time, in terms of cost, with the development of machine vision, the price will decline, and it will be more popular. For now, four shifts in a general factory require four operators, and the annual cost is more than 200,000, and 200,000 is enough to build a set of machine vision.