Robots in machining

Robotic machining centers offer diverse advantages: large operation reach with large reorientation capability, and a low cost, to name a few. Many challenges have slowed down the adoption or sometimes inhibited the use of robots for machining tasks. This paper deals with the current usage and status of robots in machining, as well as the necessary modelling and identification for enabling optimization, process planning and process control. Recent research addressing deburring, milling, incremental forming, polishing or thin wall machining is presented. We discuss various processes in which robots need to deal with significant process forces while fulfilling their machining task

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

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Robotic machining evaluation of the positioning accuracy and the machined surface quality

Due to the importance of the surface quality of machined parts, many research works have been devoted to the surface irregularities and their generating mechanisms. However, the surface quality of the robotic machining operations has not been sufficiently investigated. Indeed, the relative works are restricted to the finishing operations such as grinding and deburring. In this work, the surface quality of the slot milling operation which is executed by an industrial robot on an aluminum block is investigated. For this purpose, several slots at different directions are machined on the block by applying various cutting parameters. In order to investigate the surface quality of the slots, the machined surfaces are evaluated by a mechanical profiler, and then the results are analyzed using the power spectrum density method. Moreover, to monitor the machining conditions, the machining forces are measured with a dynamometer table. To identify the generating factors of the irregularities, both the kinematic and the dynamic properties of the robot are experimentally examined. The kinematic properties of the robot are investigated by measuring its straightness using a laser tracker, and the dynamic properties are evaluated by applying the impact test. Lack of accuracy is one of the difficulties restricting the usage of robotic machining. Indeed, the poor accuracy of industrial robots makes the off-line programming uneffective. Consequently, the operators are forced to use on-line method which is a time consuming approach. However, if a robot is calibrated properly, the off-line method could be effectively applied. To this end, before analyzing the surface quality, the accuracy of the robot is investigated and improved using a hybrid calibration model considering both the geometric errors and the joint compliances

Acquisition and reconstruction of 3D objects for robotic machining

With the evolution of the techniques of acquisition of Three-Dimensional (3D) image it became possible to apply these in more and more areas, as well as to be used for research and hobbyists due to the appearance of low cost 3D scanners. Among the application of 3D acquisitions is the reconstruction of objects, which allows for example to redo or remodel an existing object that is no longer on the market. Another rise tech is industrial robot, that is highly present in the industry and can perform several tasks, even machining activities, and can be applied in more than one type of operation. The purpose of this work is to acquire a 3D scene with low-cost scanners and use this acquisition to create the tool path for roughing a workpiece, using an industrial robot for this machining task. For the acquisition, the Skanect software was used, which had satisfactory results for the work, and the exported file of the acquisition was worked on the MeshLab and Meshmixer software, which were used to obtain only the interest part for the milling process. With the defined work object, it was applied in Computer Aided Manufacturing (CAM) software, Fusion 360, to generate the tool path for thinning in G-code, which was converted by the RoboDK software to robot code, and this also allowed to make simulation of the machining with the desired robot. With the simulation taking place as expected, it was implemented in practice, performing the 3D acquisition machining, thus being able to verify the machining technique used. Furthermore, with the results of acquire, generation of toolpath and machining, was possible to validate the proposed solution and reach a conclusion of possible improvements for this project.Com a evolução das técnicas de aquisição de imagem 3D tornou-se possível aplicá-las em cada vez mais áreas, bem como serem utilizadas por pesquisadores e amadores devido ao surgimento de scanners 3D de baixo custo. Entre as aplicações de aquisições 3D está a reconstrução de objetos, o que permite, por exemplo, refazer ou remodelar um objeto existente que não está mais no mercado. Outra tecnologia em ascensão é o robô industrial, que está muito presente na indústria e pode realizar diversas tarefas, até mesmo atividades de fabrico, e ser aplicado em mais de um tipo de operação. O objetivo deste trabalho é adquirir uma cena 3D com scanners de baixo custo e utilizar esta aquisição para criar o caminho da ferramenta para o desbaste de uma peça, utilizando um robô industrial nesta tarefa de usinagem. Para a aquisição foi utilizado o software Skanect, que obteve resultados satisfatórios para o trabalho, e o arquivo exportado da aquisição foi trabalhado nos softwares MeshLab e Meshmixer, os quais foram utilizados para obter apenas a parte de interesse para o processo de fresagem. Com o objeto de trabalho defino, este foi aplicado em software CAM, Fusion 360, para gerar o caminho de ferramentas para o desbaste em G-code, o qual foi convertido pelo Software RoboDK para código de rôbo, e este também permitiu fazer simulação da maquinação com o rôbo pretendido. Com a simulação ocorrendo de acordo com o esperado, esta foi implementada em prática, realizando a maquinação da aquisição 3D, assim podendo verificar a técnica de maquinação utilizada. Além disso com os resultados de aquisição, geração de toolpath e maquinação, foi possível validar a solução proposta e chegar a uma conclusão de possíveis melhorias para este projeto

Laser Scanning Based Object Detection to Realize Digital Blank Shadows for Autonomous Process Planning in Machining

The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted CAD/CAM (computer-aided design/computer-aided manufacturing) planning. Thereby, a laser-triangulation sensor is integrated into the machine tool. For an automatic raw-part detection and a workpiece origin definition, a dedicated algorithm for creating a digital blank shadow is introduced. The algorithm generates adaptive scan paths, merges laser lines and machine axis data, filters interference signals, and identifies part edges and surfaces according to a point cloud. Furthermore, a dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC (computer numerical control) machine. The results of this study show that the applied method can identify the positions, dimensions, and shapes of different raw parts autonomously, with deviations less than 1 mm, in 2.5 min. Moreover, the measurement and process data can be transferred without errors to different hardware and software systems. It was found that the proposed approach can be applied for rough raw-part detection, and in combination with a touch probe for accurate detection

A framework to support automation in manufacturing through the study of process variability

In manufacturing, automation has replaced many dangerous, mundane, arduous and routine manual operations, for example, transportation of heavy parts, stamping of large parts, repetitive welding and bolt fastening. However, skilled operators still carry out critical manual processes in various industries such as aerospace, automotive and heavy-machinery. As automation technology progresses through more flexible and intelligent systems, the potential for these processes to be automated increases. However, the decision to undertake automation is a complex one, involving consideration of many factors such as return of investment, health and safety, life cycle impact, competitive advantage, and resources and technology availability. A key challenge to manufacturing automation is the ability to adapt to process variability. In manufacturing processes, human operators apply their skills to adapt to variability, in order to meet the product and process specifications or requirements. This thesis is focussed on understanding the ‎variability involved in these manual processes, and how it may influence the automation solution. ‎ Two manual industrial processes in polishing and de-burring of high-value components were observed to evaluate the extent of the variability and how the operators applied their skills to overcome it. Based on the findings from the literature and process studies, a framework was developed to categorise variability in manual manufacturing processes and to suggest a level of automation for the tasks in the processes, based on scores and weights given to the parameters by the user. The novelty of this research lies in the creation of a framework to categorise and evaluate process variability, suggesting an appropriate level of automation. The framework uses five attributes of processes; inputs, outputs, strategy, time and requirements and twelve parameters (quantity, range or interval of variability, interdependency, diversification, number of alternatives, number of actions, patterned actions, concurrency, time restriction, sensorial domain, cognitive requisite and physical requisites) to evaluate variability inherent in the process. The level of automation suggested is obtained through a system of scores and weights for each parameter. The weights were calculated using Analytical Hierarchical Process (AHP) with the help of three experts in manufacturing processes. Finally, this framework was validated through its application to two processes consisting of a lab-based peg-in-a-hole manual process and an industrial process on welding. In addition, the framework was further applied to three processes (two industrial processes and one process simulated in the laboratory) by two subjects for each process to verify the consistency of the results obtained. The results suggest that the framework is robust when applied by different subjects, presenting high similarity in outputs. Moreover, the framework was found to be effective when characterising variability present in the processes where it was applied. The framework was developed and tested in manufacturing of high value components, with high potential to be applied to processes in other industries, for instance, automotive, heavy machinery, pharmaceutical or electronic components, although this would need further investigation. Thus, future work would include the application of the framework in processes in other industries, hence enhancing its robustness and widening its scope of applicability. Additionally, a database would be created to assess the correlation between process variability and the level of automation

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