Active vibration control and real-time cutter path modification in rotary wood planing

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

Towards an automated polishing system: capturing manual polishing operations

Advancements in robotic and automation industries have influenced many manual manufacturing operations. With a great level of success, robots have taken over from man in many processes such as part manufacturing, transfer and assembly. However, in other traditionally manual operations such as polishing, automation has only partially been successful, typically limited to parts with simple geometry and low accuracy. Automated polishing systems using robots have been attempted already by a number of industrial and research groups; however, there are few examples of deploying such a system as a part of a routine production process in high-technology industries, such as aerospace. This is due to limitations in flexibility, speed of operation, and inspection processes, when compared with manual polishing processes. The need for automated polishing processes is discussed in this article and the problem with the existing system was explained to be a lack of understanding and the disconnect from manual operations. In collaboration with industrial partners, a mechatronic based data capturing device was developed to accurately capture and analyze operational variables such as force, torque, vibration, polishing pattern, and feed rates. Also reported in this article is a set of experiments carried out to identify the polishing parameters that a manual operator controls through tactile and visual sensing. The captured data is interpreted to the operators’ preferences and polishing methods and should then be included in the design of an automated polishing system. The research results reported in this article are fed back to an ongoing research project on developing an integrated robotic polishing system

An intelligent and confident system for automatic surface defect quantification in 3D

Automatic surface defect inspection within mass production of high-precision components is growing in demand and requires better measurement and automated analysis systems. Many manufacturing industries may reject manufactured parts that exhibit even minor defects, because a defect might result in an operational failure at a later stage. Defect quantification (depth, area and volume) is a key element in quality assurance in order to determine the pass or failure criterion of manufactured parts. Existing human visual analysis of surface defects is qualitative and subjective to varying interpretation. Non-contact and three dimensional (3D) analyses should provide a robust and systematic quantitative approach for defect analysis. Various 3D measuring instruments generate point cloud data as an output, although they work on different physical principles. Instrument’s native software processing of point cloud data is often subject to issues of repeatability and may be non-traceable causing significant concern with data confidence. This work reports the development of novel traceable surface defect artefacts produced using the Rockwell hardness test equipment on flat metal plate, and the development of a novel, traceable, repeatable, mathematical solution for automatic defect detection and quantification in 3D. Moreover, in order to build-up the confidence in automatic defect analysis system and generated data, mathematical simulated defect artefacts (soft-artefact) have been created. This is then extended to a surface defect on a piston crown that is measured and quantified using a parallel optical coherence tomography instrument integrated with 6 axis robot. The results show that surface defect quantification using implemented solution is efficient, robust and more repeatable than current alternative approaches

Inspection of wood surface waviness defects using the light sectioning method

Surface waviness variations are a major type of defect on planed wood products. A number of methods have been investigated for the inspection of waviness defects on wood surfaces. This paper describes a new implementation of the light sectioning method with the latest structured lighting and machine vision techniques for this purpose. As a reference, a laser profilometer is used. The data from the light sectioning method and from the profilometer are highly correlated

A theoretical analysis of billiard ball dynamics under cushion impacts

The last two decades have seen a growing interest in research related to billiards. There have been a number of projects aimed at developing training systems, robots, and computer simulations for billiards. Determination of billiard ball trajectories is important for all of these systems. The ball’s collision with a cushion is often encountered in billiards and it drastically changes the ball trajectory, especially when the ball has spin. This work predicts ball bounce angles and bounce speeds for the ball’s collision with a cushion, under the assumption of insignificant cushion deformation. Differential equations are derived for the ball dynamics during the impact and these equations are solved numerically. The numerical solutions together with previous experimental work by the authors predict that for the ball–cushion collision, the values of the coefficient of restitution and the sliding coefficient of friction are 0.98 and 0.14, respectively. A comparison of the numerical and experimental results indicates that the limiting normal velocity under which the rigid cushion assumption is valid is 2.5 m/s. A number of plots that show the rebound characteristics for given ball velocity–spin conditions are also provided. The plots quantify various phenomena that have hitherto only been described in the billiards literature

An automated solution for fixtureless sheet metal forming

Manual forming of sheet metal parts through traditional panel beating is a highly skilled profession used in many industries, particularly for sample manufacturing or repair and maintenance. However, this skill is becoming gradually isolated mainly due to the high cost and lack of expertise. Nonetheless, a cost-effective and flexible approach to forming sheet metal parts could significantly assist various industries by providing a method for fast prototyping sheet metal parts. The development of a new fixtureless sheet metal forming approach is discussed in this article. The proposed approach, named Mechatroforming®, consists of integrated mechanisms to manipulate sheet metal parts by a robotic arm under a controlled hammering tool. The method includes mechatronics-based monitoring and control systems for (near) real-time prediction and control of incremental deformations of parts. This article includes description of the proposed approach, the theoretical and modelling backgrounds used to predict the forming, skills learned from manual operations, and proposed automation system being built

Data-driven bending angle prediction of soft pneumatic actuators with embedded flex sensors

In this paper, resistive flex sensors have been embedded at the strain limiting layer of soft pneumatic actuators, in order to provide sensory feedback that can be utilised in predicting their bending angle during actuation. An experimental setup was prepared to test the soft actuators under controllable operating conditions, record the resulting sensory feedback, and synchronise this with the actual bending angles measured using a developed image processing program. Regression analysis and neural networks are two data-driven modelling techniques that were implemented and compared in this study, to evaluate their ability in predicting the bending angle response of the tested soft actuators at different input pressures and testing orientations. This serves as a step towards controlling this class of soft bending actuators, using data-driven empirical models that lifts the need for complex analytical modelling and material characterisation. The aim is to ultimately create a more controllable version of this class of soft pneumatic actuators with embedded sensing capabilities, to act as compliant soft gripper fingers that can be used in applications requiring both a ‘soft touch’ as well as more controllable object manipulation

Yarn twist measurement using digital imaging

Digital image analysis techniques in the spatial and frequency domains for twist measurement of yarns are described. A spatial technique is developed to extract the twist angle through the analysis of the yarn core image. Then, a Fourier transformation technique is applied to yarn images to measure the orientation of the fibre on the yarn surface. Finally, a hybrid method that incorporates frequency domain filtering prior to spatial analysis is proposed. The trials show that spatial analysis is a fast method and can successfully predict the twist in the yarn. Fourier transformation technique is quite sensitive to the protruding fibres obstructing the yarn surface, which may result in measurements having high variations. For yarns having little amount of hairs protruding from the core, the results agreed reasonably well with actual twist levels. Frequency domain filtering in conjunction with the spatial analysis of the yarn surface is found to be superior in terms of accuracy. The twist values calculated using the more reliable diameter measurements with back-lit images together with twist angles from the front-lit images are found to be more accurate when compared with the actual values

In-process surface profile assessment of rotary machined timber using a dynamic photometric stereo technique

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

Development of an intelligent automated polishing system

In high-value manufacturing sectors, many manufacturing processes are still performed manually, such as polishing operations for small metallic parts. Increasing volume, the need for consistency in quality, and health and safety issues are some of the reasons for industry to search urgently for alternative solutions for manual polishing processes. This article reports the development of an intelligent automated polishing system to achieve consistent surface quality and removal of superficial defects from high-value components, such as those used in aerospace industry. The article reports an innovative method to capture manual polishing processes by skilled operators. The captured polishing parameters are then used to develop and control a robotic polishing system that can adopt various polishing patterns. A brief summary of existing fully and semi-automated polishing systems and their inadequacy for industrial applications are discussed. The need for building automation system based on manual operations are explained and a systematic data capturing process for a specific aerospace-based component is defined. The development of the process capturing device is explained, the data analysis and interpretations are discussed and the migration from manual operation to an automated polishing system is reported. Further detailed information is given in relation with combining data from various sensors and building of an automated system based on learning from manual operations. The research results are also briefly discussed and conclusions are drawn regarding applicability of automated systems for highly skilled manual operations