This master’s thesis deals with a description of Laser Welded Common Rail, which is produced by the company Bosch Diesel, s. r. o. in Jihlava. The theoretical part is focused primarily on a proposal for an industrial robot which would be manipulated with Common Rail during the laser welding process. The practical section is concerned with changes in the current paths of the robot to reduce production times, and to avoid using the same parts of the robot for the whole duration it is being manipulated with the Common Rail. At the end of this master's thesis is a techno-economic evaluation of previous alternatives, and it determines the appropriate option for robotic manipulation with the Common Rail during the laser welding process.

This thesis is focused on design of a robotic cell for load testing purposes. At the beginning the aim of work is determined by objective testing. Next part is description of a test object, current work station and the present state of work. Further is determined one variant of solutions and are selected elements of the robotic cell. The design of layout follows especially with regards to safety and is processed simplified risk analysis. The second half of the work consists of developing a driverless robot design of the measuring device. The end of thesis is price calculation.

The theme of the thesis is a structural design of the robotic system SCARA. Thesis at the start clarifies the definition of robots and industrial robots. Next it deals with kinematic structures, from basic to more advnced structures, including SCARA type robot. The next chapter describes parts used in design of industrial robots. In the fourth chapter, the table provides an overview of currently available SCARA robots and their attributes. The rest of the thesis itself consists of machine design from determining the required parameters to 3D design. This section also contains extensive computational parts and justifies the choice of the components.

The object of this diploma work is to project a manipulator for the chaffs of glass, which will be mounted to the cutting machine RKP 01. The function of this manipulator will be a transposition of the chaffs of glass from the supply table to the haul. This manipulator check by calculations. RPK is the cutting machine for the circular-shaped cutouts, from which the saucers are made. Everything will be operated automatically, position of a handling moulding will be located by the sense organs and everything will be controlled by the automat, which was already designed by the firma FESTO FEC 30.

A Machine Learning approach for error recovery in an industrial robot for the plastic mold industry isproposed in this master thesis project. The goal was to improve the present error recovery method byproviding a learning algorithm to the system instead of using the traditional algorithm-based control.The chosen method was the Support Vector Machine (SVM) due to the robustness and the goodgeneralization performance in real-world applications. Furthermore, SVM generates good classifierseven with a minimal number of training examples. In production, there will be no need for a humanoperator to train the SVM with hundreds or thousands of training examples to achieve goodgeneralization. The advantage with SVM is that good accuracy can be achieved with only a couple oftraining examples if the training examples are well designed.Firstly, the algorithm proposed was evaluated experimentally. The experiments consisted of correcthandling of classification performance on training examples, which was a hand-coded data set createdwith defined in- and output signals. Secondly, the results from the experiments were tested in asimulated environment. By using only a few training examples the SVM reached perfect performance.In conclusion, SVM is a good tool for classification and a suitable method for error recovery on theindustrial robot for the plastic mold industry. / En maskininlärningsstrategi för felhantering på industrirobotar inom plastformindustrin presenteras idetta examensarbete. Målet var att förbättra den nuvarande felhanteringen genom att applicera eninlärningsalgoritm istället för det traditionella förprogrammerade systemet till roboten. Den valdametoden är Support Vector Machine (SVM), då SVM är en robust metod som ger bra prestanda iverkliga tillämpningar. SVM genererar bra klassificerare även med ett minimalt antal träningsexempel.Fördelen med SVM är att god precision kan uppnås med bara ett par träningsexempel förutsatt attträningsexemplen är väldesignade. Detta betyder att operatörerna i produktionen inte behöver tränahundratals eller tusentals träningsexempel med SVM för att uppnå en god generalisering.I projektet utvärderasdes SVM metoden experimentellt varefter den testades i ett simuleringsprogram.Resultatet visade att SVM metoden gav en perfekt precision med hjälp av endast ett fåtal träningsdata.En slutsats från denna studie är att SVM är en bra metod för klassificering och lämplig för felhanteringpå industrirobotar inom plastindustrin.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24606号 / 工博第5112号 / 新制||工||1978(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 松野 文俊, 教授 松原 厚, 教授 泉井 一浩 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

This paper studies a Virtual Reality (VR) training program for novice industrial robot operators. The VR training program is constructed using Unity and HTC Vive. The paper presents the result of comparative experiments allowing novices to learn and operate virtual and physical robots to complete simple industrial production tasks. The results include their time to complete the task, the pass rate of the task, and the results of the questionnaire survey as evidence of their learning efficiency and user satisfaction. Finally, through data analysis, we compare the impact the two methods have on novices. The two approaches are the VR training program and the conventional physical robot training method. The experiment results show that novices who use the VR training program at first show a high degree of user satisfaction, and they can more quickly and efficiently master the knowledge of manipulating industrial robots and apply it to practice. The findings of this article also show that the use of VR technology in industrial production improves y and is a feasible and reliable method which still has room‌‌‌ or improvement. / Den här uppsatsen undersöker ett Virtual Reality-träningsprogram för industriella robot operatörer som är nybörjare. VR-träningsprogrammet är skapat i Unity för HTC Vive. Uppsatsen presenterar resultaten av en jämförande studie där nybörjare fick lära sig att använda en VR och en fysisk robot för att slutföra enkla industriella produktionsuppgifter. Resultatet inkluderar deltagarnas tid att slutföra uppgifterna, andel lyckade försök samt resultaten av ett frågeformulär som bevis på deltagarnas inlärnings effektivitet samt användartillfredsställelse. Genom en dataanalys jämfördes de effekter ett VR- träningsprogram och en konventionell metod på fysiska robotar hade på nybörjare. Studiens resultat visar att nybörjare som använder VR-träningsprogrammet visar en högre grad av användartillfredsställelse och att dem är snabbare och effektivare när dem bemästrar kunskapen som behövs för att manipulera industrirobotar, samt att tillämpa detta i verkligheten. Resultaten visar också att användningen av VR i industriell produktion förbättrar effektiviteten och är en rimlig och trovärdig metod, men som fortfarande har rum för förbättringar.

Robotic automation has evolved to be an irreplaceable part of production lines. Orderly operation of the robots is a key factor. Yet robots often have to deal with unpredictable factors including human beings or possible failures that lead to unexpected behaviours. Collision avoidance mechanisms are therefore of outmost importance to prevent injuries and damage. A major challenge in the creation of a dependable collision avoidance system is the sensory system that could cover relevant parts of the robot and capacitive sensors are a promising solution. The burden is to overcome the nonlinearity and other limitations of the capacitive sensors and harness their potential to this end. It is cumbersome to estimate the proximity of surfaces of the robot from its environment (which could include other robots) from the capacitive readings, so a novel sensing approach is proposed in this thesis. For industrial applications where the motions are well-defined, a pre-recorded capacitive signature can be used to monitor for unexpected changes. In this thesis the capacitive signature of one or more robotic arms will be used to predict and prevent collisions in a robotic workcell. A short training cycle is used to create a signature that is used at runtime to monitor the robot operation. Capacitive electrodes are placed on strategic locations on the robot arms and the surrounding environments and a supervisor computer uses the readings to cease the operation in case of any abnormality. This thesis describes the details of generating the signature from the training data and the runtime software. The supervisor computer provides a pause and/or go signal to the robot(s). The native controller of each arm is kept in place and the only change needed is the ability of each controller to pause the arm at command when a collision is detected and continue from this paused state. This approach requires minimum changes to the existing robotic equipments and programmes. These hardware requirements are widely available on existing controllers. Signature creation is the process of finding the normal pattern of the capacitance readings from all sensors as well as some expected limits allowing for the variations that are to be expected. The algorithms, reasoning, and experimental data are provided throughout the text. The system is tested on a robotic workcell that includes an actively controlled robot and a passive revolute joint. While the algorithm is universal, the suggested hardware has been shown to provide sampling times of down to 20ms, and positional accuracies of ±2mm or better are achieved for the test setup. The thesis also proposes methods to expand the measurement hardware for increased protection and fault tolerance. / Thesis / Master of Applied Science (MASc)

In this study, a robotic software, which controls the robot, is developed. The robot considered is a six degree of freedom robot and it is designed and manufactured in METU. User can send the robot anywhere in space within its workspace, in any orientation. Forward and inverse kinamatics can be executed according to the needs. Simulation framework is embedded into the software for the 3D visualisation of the robot. Any movements can be simulated on the screen. Software also generates the path for the given points. Then generated path is simulated on the screen. All position, velocity and acceleration graphics of joints can be examined for the generated path.

This thesis is solving issues concerning deburring of hydraulic valve blocks with industrial robot. Thesis is focused on deburring of inside space of hydraulic valve blocks, although deburring of outer edges is marginally mentioned due to determining of approximate deburring time of all edges on the valve block. Search of deburring methods and tools suitable for deburring of inside and outside edges is made on the basis of valve blocks´ analysis. Paths of tools chosen for deburring of valve block B1 are programmed in CAM program. CAD program ProEngineer is used to create simplified model of robotic workplace and its layout. According to customer´s requirements, deburring method, which allows creating universal robotic workplace for deburring of hydraulic valve blocks, was chosen. Approximate deburring time of all edges on B1 block was set on the basis of tools´ paths and these were checked in the simplified model of robotic workplace in PowerMill Robot Interface. Deburring procedure, estimating of approximate deburring time of B1 block and layout of robotic workplace are main results of this thesis.