No abstract

There is a growing need to perform automated visual surface inspection in various manufacturing processes due to increased emphasis on quality control. A number of high-resolution three-dimensional metrology products are commercially available, but they are all very limited in their fields of view. The small field of view of the scanners makes inspection of relatively large parts a time-consuming operation, which has significant negative impacts on throughput. This article presents a two-stage inspection process in which a machine vision system, based on the photometric stereo principle, is used to detect potentially defective regions on parts over a much wider field of view than the one covered by the commercial products. The suspicious regions are then inspected using a high-resolution commercial three-dimensional surface measurement system, ignoring areas that are perceived to be defect free. Experimental tests on planar steel samples, having known surface defects, show that this approach is effective and it reduces the overall inspection time significantly.

Over the past two decades, a major part of the manufacturing and assembly market has been driven by the increasing demand for customised products. This has created the need for smaller batch sizes, shorter production times, lower costs, and the flexibility to produce families of products-or to assemble different parts-with the same sets of equipment. Consequently, manufacturing companies have deployed various automation systems and production strategies to improve their resource efficiency and move towards right-first-time production. Threaded fastening operations are widely used in assembly and are typically time-consuming and costly. In high-volume production, fastening operations are commonly automated using jigs, fixtures, and semi-automated tools. However, in low-volume, high-value manufacturing, fastening operations are carried out manually by skilled workers. The existing approaches are found to be less flexible and robust for performing assembly in a less structured industrial environment. This motivated the development of a flexible solution, which does not require fixtures and is adaptable to variation in part locations and lighting conditions. As a part of this research, a novel 3D threaded hole detection and a fast bolt detection algorithms are proposed and reported in this article, which offer substantial enhancement to the accuracy, repeatability, and the speed of the processes in comparison with the existing methods. Hence, the proposed method is more suitable for industrial applications. The development of an automated bolt fastening demonstrator is also described in this article to test and validate the proposed identification algorithms on complex components located in 3D space.

Machining operations have advanced in speed and there is an increasing demand for higher quality surface finish. It is therefore necessary to develop real-time surface inspection techniques which will provide sensory information for controlling the machining processes. This paper describes a practical method for real-time analysis of planed wood using the photometric stereo technique. Earlier research has shown that the technique is very effective in assessing surface waviness on static wood samples. In this paper, the photometric stereo method is extended to real industrial applications where samples are subjected to rapid movements. Surface profiles extracted from the dynamic photometric stereo method are compared with those from the static measurements and the results show that there is a high correlation between the two methods.