Reducing the acquisition cost of the next fighter jet using automation

The acquisition cost of fast-jets has increased exponentially since WWII, placing defence budgets under severe pressure. Fleet sizes are contracting as fewer new aircraft are ordered, and with new programmes few and far between the methods of assembling airframes have hardly changed in fifty-years. Modern airframes rely on traditional welded steel assembly fixtures and high accuracy machine tools, which represent a significant non-recurring cost that cannot be reconfigured for re-use on other programmes. This research investigates the use of automation to reduce the acquisition cost. Its aim is to demonstrate innovations, which will collectively assist in achieving the twin goals of Tempest, to be manufactured 50-percent faster and 50-percent cheaper, through the re-configuration and re-use of automation, creating a flexible factory-of-the-future. Two themes were explored, the UK-MOD’s acquisition process, to position this research in the timeframe of the next generation of fast-jet, and the use of automation in airframe assembly globally, specifically focusing on Measurement Assisted Assembly (MAA), part-to-part methods and predictive processes. A one-to-one scale demonstrator was designed, manufactured and assembled using MAA; and from the measurement data additively manufactured shims for the structure’s joints were produced. The key findings are that; metrology guided robots can position parts relative to one-another, to tolerances normally achieved using welded steel fixtures, maintaining their position for days, and can then be reconfigured to assemble another part of the structure. Drilling the parts during their manufacture on machine tools, using both conventional and angle-head tooling, enables them to be assembled, negating the requirement to use traditional craft-based skills to fit them. During the manufacture of the parts, interface data can be collected using various types of metrology, enabling them to be virtually assembled, creating a Digital Twin, from which any gaps between parts can be modelled and turned into a shim using an additive manufacturing process with the limitation that current AM machines do not produce layers thin enough to fully meet the shimming requirement. The acquisition process requires, a technology to be demonstrated at technology readiness level (TRL) 3 during the concept phase, and have a route-map to achieve TRL 6 in the development phase, following the assessment phase. The novel use of automation presented in this thesis has the potential to enable manufacturing assets to be re-configured and re-used, significantly reducing impacting the acquisition costs of future airframe programmes. Collectively the innovations presented can significantly reduce the estimated 75 percent of touch labour costs and 9 percent of non-recurring costs associated with assembling an airframe. These innovations will help to enable a digital transformation that, together with other Industry 4.0 technologies and methods, can collectively enable the automated manufacture of customised aerospace products in very-low volumes. This is of relevance not only to next generation fighter jets, but also to emerging sectors such as air-taxis

Automated freeform assembly of threaded fasteners

Over the past two decades, a major part of the manufacturing and assembly market has been driven by its customer requirements. Increasing customer demand for personalised products create the demand for smaller batch sizes, shorter production times, lower costs, and the flexibility to produce families of products - or 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. However, many of these automated systems, which are involved with robot-based, repeatable assembly automation, require component- specific fixtures for accurate positioning and extensive robot programming, to achieve flexibility in their production. Threaded fastening operations are widely used in assembly. In high-volume production, the fastening processes are commonly automated using jigs, fixtures, and semi-automated tools. This form of automation delivers reliable assembly results at the expense of flexibility and requires component variability to be adequately controlled. On the other hand, in low- volume, high- value manufacturing, fastening processes are typically carried out manually by skilled workers. This research is aimed at addressing the aforementioned issues by developing a freeform automated threaded fastener assembly system that uses 3D visual guidance. The proof-of-concept system developed focuses on picking up fasteners from clutter, identifying a hole feature in an imprecisely positioned target component and carry out torque-controlled fastening. This approach has achieved flexibility and adaptability without the use of dedicated fixtures and robot programming. This research also investigates and evaluates different 3D imaging technology to identify the suitable technology required for fastener assembly in a non-structured industrial environment. The proposed solution utilises the commercially available technologies to enhance the precision and speed of identification of components for assembly processes, thereby improving and validating the possibility of reliably implementing this solution for industrial applications. As a part of this research, a number of novel algorithms are developed to robustly identify assembly components located in a random environment by enhancing the existing methods and technologies within the domain of the fastening processes. A bolt identification algorithm was developed to identify bolts located in a random clutter by enhancing the existing surface-based matching algorithm. A novel hole feature identification algorithm was developed to detect threaded holes and identify its size and location in 3D. The developed bolt and feature identification algorithms are robust and has sub-millimetre accuracy required to perform successful fastener assembly in industrial conditions. In addition, the processing time required for these identification algorithms - to identify and localise bolts and hole features - is less than a second, thereby increasing the speed of fastener assembly

Development of an integrated robotic polishing system

This thesis presents research carried out as part of a project undertaken in fulfilment of the requirements of Loughborough University for the award of Philosophical Doctorate. The main focus of this research is to investigate and develop an appropriate level of automation to the existing manual finishing operations of small metallic components to achieve required surface quality and to remove superficial defects. In the manufacturing industries, polishing processes play a vital role in the development of high precision products, to give a desired surface finish, remove defects, break sharp edges, extend the working life cycle, and meet mechanical specification. The polishing operation is generally done at the final stage of the manufacturing process and can represent up to a third of the production time. Despite the growth automated technology in industry, polishing processes are still mainly carried out manually, due to the complexity and constraints of the process. Manual polishing involves a highly qualified worker polishing the workpiece by hand. These processes are very labour intensive, highly skill dependent, costly, error-prone, environmentally hazardous due to abrasive dust, and - in some cases - inefficient with long process times. In addition, the quality of the finishing is dependent on the training, experience, fatigue, physical ability, and expertise of the operator. Therefore, industries are seeking alternative solutions to be implemented within their current processes. These solutions are mainly aimed at replacing the human operator to improve the health and safety of their workforce and improve their competitiveness. Some automated solutions have already been proposed to assist or replace manual polishing processes. These solutions provide limited capabilities for specific processes or components, and a lack of flexibility and dexterity. One of the reasons for their lack of success is identified as neglecting the study and implementing the manual operations. This research initially hypothesised that for an effective development, an automated polishing system should be designed based on the manual polishing operations. Therefore, a successful implementation of an automated polishing system requires a thorough understanding of the polishing process and their operational parameters. This study began by collaborating with an industrial polishing company. The research was focused on polishing complex small components, similar to the parts typically used in the aerospace industry. The high level business processes of the polishing company were capture through several visits to the site. The low level operational parameters and the understanding of the manual operations were also captured through development of a devices that was used by the expert operators. A number of sensors were embedded to the device to facilitate recording the manual operations. For instance, the device captured the force applied by the operator (avg. 10 N) and the cycle time (e.g. 1 pass every 5 sec.). The capture data was then interpreted to manual techniques and polishing approaches that were used in developing a proof-of-concept Integrated Robotic Polishing System (IRPS). The IRPS was tested successfully through several laboratory based experiments by expert operators. The experiment results proved the capability of the proposed system in polishing a variety of part profiles, without pre-existing geometrical information about the parts. One of the main contributions made by this research is to propose a novel approach for automated polishing operations. The development of an integrated robotic polishing system, based on the research findings, uses a set of smart sensors and a force-position-by-increment control algorithm, and transpose the way that skilled workers carry out polishing processes

Posture Dependent Vibration Resistance of Serial Robot Manipulators to Applied Oscillating Loads

There are several advantages to replacing CNC machinery with robotic machine tools and as such robotic machining is emerging into the manufacturing and metal cutting industry. There remain several disadvantages to using robots over CNC stations primarily due to flexibility in robotic manipulators, which severely reduces accuracy when operating under high machining forces. This flexibility is dependent on configuration and thus the configuration can be optimised through posture selection to minimise deflection. In previous work little has been done to account for operating frequency and the additional complications that can arise from frequency dependent responses of robotic machine tools. A Fanuc S-360 manipulator was used to experimentally investigate the benefits of including frequency compensation in posture selection. The robot dynamics first had to be identified and experimental modal analysis was selected due the inherent dependency on frequency characteristics. Specifically, a circle fit operation identified modal parameters and a least squares optimisation generated dynamic parameters for a spatial model. A rigid-link flexible-joint model was selected and a pseudo-joint was used to create an additional DOF to accommodate link flexibility. Posture optimisation was performed using a gradient-descent algorithm that used several starting points to identify a global minimum. The results showed that a subset of modal data that excluded the mode shape vectors could be used to create a model to predict the manipulator vibration response. It was also found that the receptance variation of the manipulator with configuration was insufficient to verify the optimisation throughout the entire selected workspace; however the model was shown to be useful in regions containing multiple peaks where the modelled dynamics were dominant over the highly volatile measured data. Simulations were performed on a redundant planar manipulator to overcome the lack of receptance variation found in the Fanuc manipulator. These simulations showed that there were two mechanisms driving the optimisation; overall amplitude reduction and frequency specific amplitude reduction. Using a stiffness posture measure for comparison, the results of the frequency specific reduction could be separated and were found to be particularly beneficial when operating close to resonant frequencies

Adaptive and reconfigurable robotic gripper hands with a meso-scale gripping range

Grippers and robotic hands are essential and important end-effectors of robotic manipulators. Developing a gripper hand that can grasp a large variety of objects precisely and stably is still an aspiration even though research in this area has been carried out for several decades. This thesis provides a development approach and a series of gripper hands which can bridge the gap between micro-gripper and macro-gripper by extending the gripping range to the mesoscopic scale (meso-scale). Reconfigurable topology and variable mobility of the design offer versatility and adaptability for the changing environment and demands. By investigating human grasping behaviours and the unique structures of human hand, a CFB-based finger joint for anthropomorphic finger is developed to mimic a human finger with a large grasping range. The centrodes of CFB mechanism are explored and a contact-aided CFB mechanism is developed to increase stiffness of finger joints. An integrated gripper structure comprising cross four-bar (CFB) and remote-centre-of-motion (RCM) mechanisms is developed to mimic key functionalities of human hand. Kinematics and kinetostatic analyses of the CFB mechanism for multimode gripping are conducted to achieve passive-adjusting motion. A novel RCM-based finger with angular, parallel and underactuated motion is invented. Kinematics and stable gripping analyses of the RCM-based multi-motion finger are also investigated. The integrated design with CFB and RCM mechanisms provides a novel concept of a multi-mode gripper that aims to tackle the challenge of changing over for various sizes of objects gripping in mesoscopic scale range. Based on the novel designed mechanisms and design philosophy, a class of gripper hands in terms of adaptive meso-grippers, power-precision grippers and reconfigurable hands are developed. The novel features of the gripper hands are one degree of freedom (DoF), self-adaptive, reconfigurable and multi-mode. Prototypes are manufactured by 3D printing and the grasping abilities are tested to verify the design approach.EPSR

Research and development of a reconfigurable robotic end-effector for machining and part handling.

Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF