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.

Forced structural vibration and cutting tool inaccuracy have been identified to be the primary causes of surface defects in rotary wood planing. This paper presents the development of a control strategy used to compensate for the effects of both vibration and cutting tool inaccuracy on planed wood surface finish. The solution is based on active vibration control and real-time modification of the cutting tool trajectory using an optimal Linear Quadratic Gaussian tracking controller. A small-scale mechatronic wood planing machine, which has an actively controlled spindle unit, has been designed for practical investigation of the proposed technique. Experimental results show that the applied compensation increased the dynamic performance of the machine and the quality of the surface finish produced.

Robotic assembly systems either make use of expensive fixtures to hold components in predefined locations, or the poses of the components are determined using various machine vision techniques. Vision-guided assembly robots can handle subtle variations in geometries and poses of parts. Therefore, they provide greater flexibility than the use of fixtures. However, the currently established vision-guided assembly systems use 2D vision, which is limited to three degrees of freedom. The work reported in this paper is focused on flexible automated assembly of clearance fit machine components using 3D vision. The recognition and the estimation of the poses of the components are achieved by matching their CAD models with the acquired point cloud data of the scene. Experimental results obtained from a robot demonstrating the assembly of a set of rings on a shaft show that the developed system is not only reliable and accurate, but also fast enough for industrial deployment.

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.

The primary causes of defects in planed timber surfaces have been identified to be cutting tool inaccuracy and forced vibration during the machining process. It is noted that the current mechanical methods used in the woodworking industry to improve surface finish quality have disadvantages that defeat their original attractiveness. This article describes a mechatronic approach used to compensate for cutting tool inaccuracy in wood planing via cutting tool trajectory modification. The approach is based on real-time measurement of the angular spindle position, coupled with periodic vertical displacements of the rotating spindle. A small-scale wood planing machine, which has an actively controlled spindle unit, has been designed for practical investigation of the technique. Experimental results show that the dynamic performance of wood planing machines, and hence the surface finish quality, can be improved via this approach.

Rotary planing is one of the most valuable machining operations in the timber processing industry. It has been established that cutting tool inaccuracy and forced vibration during the machining process are the primary causes of surface quality degradation. The main aim of this thesis is to design a control architecture that is suitable for adaptive operation of a wood planing machining in order to improve the quality of its surface finish. In order to achieve the stated goal, thorough understanding of the effects of machine deficiencies on surface finish quality is required. Therefore, a generic simulation model for synthesising the surface profiles produced by wood planing process is first developed. The model is used to simulate the combined effects of machining parameters, vibration and cutting tool inaccuracy on the resultant surface profiles. It has been postulated that online monitoring of surface finish quality can be used to provide feedback information for a secondary control loop for the machining process, which will lead to the production of consistently high quality surface finishes. There is an existing vision-based wood surface profile measurement technique, but the application of the technique has been limited to static wood samples. This thesis extends the application of the technique to moving wood samples. It is shown experimentally that the method is suitable for in-process surface profile measurements. The current industrial wood planing machines do not have the capability of measuring and adjusting process parameters in real-time. Therefore, knowledge of the causes of surface finish degradation would enable the operators to optimise the mechanical structure of the machines offline. For this reason, two novel approaches for characterising defects on planed timber surfaces have been created in this thesis using synthetic data. The output of this work is a software tool that can assist machine operators in inferring the causes of defects based on the waviness components of the workpiece surface finish. The main achievement in this research is the design of a new active wood planing technique that combines real-time cutter path optimisation (cutting tool inaccuracy compensation) with vibration disturbance rejection. The technique is based on real-time vertical displacements of the machine spindle. Simulation and experimental results obtained from a smart wood planing machine show significant improvements in the dynamic performance of the machine and the produced surface finish quality. Potential areas for future research include application of the defects characterisation techniques to real data and full integration of the dynamic surface profile measurements with the smart wood planing machine.

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.

In-process surface inspection during wood machining has attracted great interest in recent years due to the growing desire to minimise wastage and the increasing demand for higher quality wooden products. In order to take advantage of the developments in machine vision technologies for surface quality inspection, it is necessary to investigate the reflectance properties of wood so that standard machine-vision based assessment methods can be established. This paper describes a method for estimating the surface albedo of wood using photometric stereo technique. It is revealed that the albedo of timber is highly variable, which can be attributed to its hygroscopic and anisotropic material nature.