Additive Manufacturing has brought about substantial benefits to the manufacturing industry due to the numerous advantages it provides, at the same time there are factors that can be improved upon. Temperature control is an important parameter during the build process as it affects build quality. The main objective of this thesis project was to investigate what sensors could be used for monitoring the temperature during the additive manufacturing processand to compare and evaluate their performance. This involved implementing two 2-color pyrometers and a short-wave infrared camera to monitor the temperature of the area behind the melt pool and then visualizing the respective data. Initial issues arose during test runs in the form of noise in the pyrometer data, this was solved by implementing a smoothing filter to the signal. Multiple runs were conducted to capture the required data as images produced by the camera were overexposed and out of focus during initial runs. This was solved by changing the camera position and exposure settings. Reading the temperature values from the images involved interpreting the Average Dark Units (ADU) values of the region of interest and then comparing those values to a reference chart. The data gathered with the help of LabVIEW software and the proprietary imaging software of the camera showed that the selected sensors were in fact suitable for the intended task and could be used in conjunction with each other. This data could then be used to create a closed-loop system in the future (not in the scope of this thesis work) and thus enable the increase in the level of automation for Robotized Laser Wire Additive Manufacturing.

The background for this thesis work emanates from a desire to drive the production of the VBG Truck Equipment factory in Vänersborg a step further to catch up with the Industry 4.0 standards. Discrete Event Simulation (DES) is a widely adopted tool within industries to model real-world systems to improve their processes. The concern of bottlenecks is a vital problem in optimizing and improving the efficiency of production processes. Finding and investigating bottlenecks is one of the primary considerations of all manufacturing industries.The company aims to enhance its logistics by using automation in its processes. This work focusses on the Paint shop part of the VBG factory. Thus, the VBG would like to analyse the methods to reduce the bottlenecks and the waiting time in the Paint shop production process. There were no simulation models available to analyse the existing paint shop pro duction flow; therefore, a Discrete Event Simulation (DES) model of the VBG Paint shop was built to investigate the bottlenecks and improvement methods. In this thesis work, the DES model of the existing Paint shop that uses the Last in First Out (LIFO) method was investigated to find the throughput and lead time for the products. In comparison, a First in First Out (FIFO) method was used to get a balanced production flow, and its effects were studied. The company currently uses two shifts in their Paint shop, so the alternate arrangement of shifts using the same number of operators was analysed. The analysis of three shifts with the same number of operators gave more efficiency than the existing one, and three shifts with an increasing number of operators were also compared. The shift arrangements were compared with both the LIFO and FIFO methods, and FIFO provided more throughput and balanced production flow. The main bottleneck was identified in the forklift transport waiting time, so an alternate layout using a power and free conveyor system was developed. This alternate arrangement reduced the bottlenecks and produced an increased output. The alternate layout was also compared with LIFO and FIFO methods; FIFO was the most efficient one. The shift patterns were also analysed, and the three shifts with a 50 percent increase in staff can reduce the stock build-up during the start of the first shift. As of this study, it was identified that the alternate model with FIFO is the most suitable solution for the company, and in the coming years, they intend to implement that. From the experimental results obtained, DES can be chosen as a method to analyse the problems associated with limiting the capacity of production. The DES modelling can be extended to the other processes in the factory and can be used for improving logistics and inventory management. The company production flow can be further advanced by evaluating the changes that can be implemented in the factory with real-time data.

Industrial works in the sea, such as renewable energy or oil industries are dependent on underwater repairs which on great depths needs to be unmanned. Since the ability to sense and control applied forces is imperative to minimize damage on company property, the goal for this master thesis was toinvestigate and develop different force feedback control algorithms compatible with the Saab Seaeye eM1-7 electric manipulator, utilizing a 6-DOF load cell. This thesis addressed the conditions for the force feedback control and the behaviour of the control strategies in MATLAB and Gazebo. Tests with the manipulator concluded that force feedback control is possible with the suggested strategies but that the kinematic control needs further development in order to conduct simulations of assembly tasks which requires collaboration between the force feedback and kinematic control objectives.

Redundant manipulators are widely used because they have a greater dexterity andversatility than nonredundant manipulators. In the redundant manipulators, thenumber of degrees of freedom are more than the required to manipulate objects atthe task space, which leads to a possibility to generate infinite number of solutions.For this reasons it has been a hot research topic to exploit the redundancy. Thisthesis work is focus on modeling and controlling redundant robot manipulator withseven degree of freedom (LWA 10 kg payload by Schunk). A literature review hasbeen prepared on the existing methods of exploiting the redundancy in the 7-DOFmanipulators at the velocity and position levels. The forward kinematic equationsare derived using the Denavit-Hartenberg method. The inverse kinematic problem issolved and the redundancy is exploited at the position level to avoid the computationalcomplexity and inaccuracy associated with exploiting the redundancy at the velocitylevel. The joint angles of the manipulator are computed in term of a redundancyparameter defining the self-motion in the manipulator. The relation between the jointangles and the redundancy parameter is exploited to avoid selecting the arm anglesthat violate the joint limits. The singularity configurations and robot workspace arealso studied in this thesis. An example is presented on how the self-motion of thearm appears when the end-effector is stationary. The methods are applied to followstraight line trajectories while preventing the joints to exceed the limits. The resultsfound showed how exploiting the redundancy at the position level is being exact withlow computational cost. The validity of the methods is verified by Robotics Toolboxsimulations.

Unmanned aerial systems have been widely used for variety of civilian applications over the past few years. Some of these applications require accurate guidance and control. Consequently, Unmanned Aerial Vehicle (UAV) guidance and control attracted many researchers in both control theory and aerospace engineering. Flying wings, as a particular type of UAV, are considered to have one of the most efficient aerodynamic structures. It is however difficult to design robust controller for such systems. This is due to the fact that flying wings are highly sensitive to control inputs. The focus of this thesis is on modeling and control design for a UAV system. The platform understudy is a flying wing developed by SmartPlanes Co. located in Skellefteå, Sweden. This UAV is particularly used for topological mapping and aerial photography. The novel approach suggested in this thesis is to use two controllers in sequence. More precisely, Linear Quadratic Regulator (LQR) is suggested to provide robust stability, and Proportional, Integral, Derivative (PID) controller is suggested to provide reference signal regulation. The idea behind this approach is that with LQR in the loop, the system becomes more stable and less sensitive to control signals. Thus, PID controller has an easier task to do, and is only used to provide the required transient response. The closed-loop system containing the developed controller and a UAV non-linear dynamic model was simulated in Simulink. Simulated controller was then tested for stability and robustness with respect to some parametric uncertainty. Obtained results revealed that the LQR successfully managed to provide robust stability, and PID provided reference signal regulation.

This thesis aimed to explore how to robotize the stacking of stator plates for an electric vehicle motor developed at Uppsala University. The solution developed should also enable easy implementation in future laboratory exercise. The project was conducted at Uppsala University’s Department of Electrical Engineering, where the current electric motor was being developed and utilized in the university’s engineering courses. The stacking process was manually performed and was repetitive, and the plates often got stuck in the threaded rods during assembly. Previous research at the university had developed a robotic stacking solution for two-meter-long stator plates for wave power generators, using electromagnets and inductive sensors to pick up and position the plates. An initial assessment was conducted to understand the project conditions fully, followed by a concept development phase and concept selection supported by a Pugh- matrix. A prototype of a robot stacking tool was developed and evaluated through various experiments and field tests. The tool was equipped with inductive sensors to identify the holes in the stator plate, thus ensuring correct orientation. The tool was designed to be compatible with either suction cups or electromagnets, enhancing flexibility, with suction cups proving more effective for this application. Two different stacking process flows were developed and later assessed through simulations in ABB Robotstudio, estimating the stacking times at 23 and 28 minutes for 200 stator plates. The tool demonstrated reliable gripping and stacking of the stator plates with good precision, provided that the variation in the search angle between the plates was low. The problem arising with larger search angles could be due to misaligned centers of the tool and stator plate, poor roundness of the tool, or improper centering of the tool on the robot arm. To achieve better precision, the use of guide pins can be considered and evaluated further.

This thesis investigates which cybersecurity strategies should be implemented in control systems to enhance cybersecurity. The study addresses three central questions, carefully designed to guide the research through its various phases and fulfill its purpose. The first question examines which cybersecurity strategies should be implemented in control systems in accordance with current requirements and established best practices. To answer this, a literature review of previous research and new cybersecurity requirements was conducted, identifying best practices for cybersecurity in control systems. The second question explores which cybersecurity strategies are currently implemented by actors in their management of products within the control system architecture. This was investigated through semi-structured interviews with five experts who deliver products within this architecture. To address the third question, which focuses on how actors within the control system architecture can streamline cybersecurity measures in their products, an analysis and comparison between best practices and current practices were conducted. This discussion revealed that a risk assessment and network segmentation should be implemented to enhance cybersecurity. Additionally, increased cybersecurity competence and the introduction of logging and monitoring of systems and components can further improve security.

This thesis aims to develop an automated process for the magnetization of a rotor for an electricmotor used in an electric car, using an industrial robot. The purpose is to outline how such a solutioncould be designed and to detail the steps taken to develop a design for the complete process. Apreliminary study was conducted to identify existing challenges and propose solutions. To gathermore information about the design process, experiments were carried out to determine the forcesneeded to place the magnets into the rotor, and the results were used in the subsequent design.The conclusion is that a theoretical solution is possible, and a robot tool has been designed in CAD.However, further studies are needed to validate a fully functional process for the magnetization ofthe studied rotor. / Detta arbete undersöker möjligheten att automatisera ett för närvarande manuellt moment i monteringen av en elmotor till en elbil med hjälp av en robot. Fokus ligger på utformningen av en sådan lösning och de utmaningar som behöver hanteras. Det moment som ska automatiseras är monteringen av magneter inuti den roterande delen av elmotorn, även kallad rotorn. Detta kräver en hög precision då det är små marginaler och magneterna är väldigt starka. Den största utmaningen är således att åstadkomma samma precision som en människa kan uppnå, fast med en robot. Människor kan enkelt göra små korrigeringar utan att tänka på det, med en robot behöver betydligt mer information och programmering för att utföra liknande uppgifter. Under arbetets gång har en design tagits fram där en robot, med hjälp av ett speciellt verktyg, kan föra in magneter i rotorn innan den monteras in i själva elmotorn. Genom att använda en robot för detta moment kan risker elimineras som annars uppstår när människor hanterar kraftfulla magneter för hand. Detta skulle inte bara förebygga skador för manuell personal, utan också skapa ett snabbare och effektivare monteringsmoment. Under arbetet har olika tekniska lösningar som finns idag undersökts som kan göra en robot lämplig för uppgiften. Det finns dock fortfarande utmaningar som behöver undersökas vidare innan en färdig lösning kan realiseras praktiskt. Sammanfattningsvis har en principiell design för en automationslösning tagits fram. Det krävs dock ytterligare forskning och utveckling för att kunna skapa en prototyp och implementera lösningen praktiskt.

Performance regression testing is a difficult task with several intricacies and complexities. In the absence of analysis tools, manual analysis must be conducted which is undoubtedly infeasible. Thereby, in this thesis, an automated performance analysis framework is proposed, aiming to mitigate the faced issues. To make this possible, the adequacy of the data needed to be established. Additionally, a fault detection algorithm had to be developed. From investigating the current state-of-the-art of performance anomaly detection, evidently, statistical models have been utilised far more than classical machine learning, and deep learning. Consequently, based on this knowledge and based on the types of anomalies present in the data, a cumulative sum based statistical method is proposed. The findings demonstrate that the data is adequate for detecting faults, and verifying their validity, as they are consistently observable in several test configurations. However, tests are not performed frequently enough which consequently leads to challenges in identifying the exact locations of faults. The algorithm was evaluated on artificial data with injected faults and could detect over 90 % of anomalies if they were prominent enough. Longer sequences before fault deviations occur, improved the ability of detecting the faults. Thus, further motivating the need to collect data more frequently. On a final note, the automated performance analysis framework successfully improved the efficiency of fault detection, and greater contextual data awareness were achieved through the visualization features. Manual analysis can however detect faults with greater accuracy. On that ground, these results should be interpreted with caution.

Robots have an underlying model to control their joints with the aim of reaching a specific pose. The accuracy of a robot is based on the underlying model and its parameters. The parameters of the underlying model of a robot are based on the ideal geometry and set by the manufacturer. If the parameters do not represent the physical robot accurately, the movements of the robot become inaccurate. Methods to optimize the parameters to represent the physical robot more accurately exist and result in an accuracy enhancement. Nevertheless, the underlying model of the manufacturer remains of analytical form and therefore has a limited complexity which hinders the model to represent arbitrary non-linearities and higher degree relations. To further enhance the accuracy of a robot by using a model with a higher complexity, this work investigates the use of a model of the inverse kinematics based on Artificial Intelligence (AI). The accuracy is investigated for a robot with an attached tool. In a first step, the development and initial evaluation of a suitable AI model is conducted in a simulated environment. Afterwards, the uncompensated accuracy of the robot with the tool is assessed and measurements are recorded. Using the measurements, an AI model based on the measurements of physical robot. The model is evaluated on the physical robot with a tool to quantify the achieved accuracy enhancement.