The modern painting process in automotive industry is complex and a lot of factors affect the result. The trial and error method is used today to control the quality and introduce new colours. This method takes a lot of time and does not show any clear numbers of how the process is affected by changing the parameters. During this thesis, we have investigated a delimited number of parameters. The work is based on experiments performed on samples that represents a flat surface of the cab, to reduce experimental costs. Our master thesis is done at Scania in Oskarshamn, where all the cabs for the European production is produced. The objectives with this thesis has been to explain how the process parameters of the robotic applicator affect the paint distribution, paint thickness and the colour of the top coat. We also optimised the process by finding which settings gives an even paint distribution, a correct thickness and an accepted colour of the top coat. We have been using Design of Experiments to achieve the goals of this study. Design of Experiments is a statistic method that is used to perform experiments effectively. It also shows the effect of changing the factors from a low to a high level. We have chosen to divide the workflow into three parts: screening, optimisation and confirmation. The experiments are performed during the daily production to replicate the real circumstances. The shape air, paint flow and high rotation is the most important parameters to control. Paint flow also seems to have a linear impact on the thickness of the top coat layer. The Shape air and the high rotation on the other hand mainly affect the distribution of the top coat layer. Different levels are needed for the shape air and high rotation depending on what paint flow is used. The optimal settings of the factors for our colour were found to be paint flow at 82 %, the shape air at 90 %, the high rotation at 90 % and high voltage at 100 %. The optimal settings give a result of 1,535 μm in spread and 40,08 μm in mean thickness. Our settings compared to today’s results contributes to a reduced paint consumption, better quality and therefore less rework.

Reliability experiments provide important information regarding the life of a product, including how various factors may affect product life. Current analyses of reliability data usually assume a completely randomized design. However, reliability experiments frequently contain subsampling which is a restriction on randomization. A typical experiment involves applying treatments to test stands, with several items placed on each test stand. In addition, raw materials used in experiments are often produced in batches. In some cases one batch may not be large enough to provide materials for the entire experiment and more than one batch must be used. These batches lead to a design involving blocks. This dissertation proposes two methods for analyzing reliability experiments with random blocks and subsampling. The first method is a two-stage method which can be implemented in software used by most practitioners, but has some limitations. Therefore, a more rigorous nonlinear mixed model method is proposed. / Ph. D.

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Flood cooling is primarily used to cool and lubricate the cutting tool and workpiece interface during a machining process. But the adverse health effects caused by the use of flood coolants are drawing manufacturers' attention to develop methods for controlling occupational exposure to cutting fluids. Microlubrication serves as an alternative to flood cooling by reducing the volume of cutting fluid used in the machining process. Microlubrication minimizes the exposure of metal working fluids to the machining operators leading to an economical, safer and healthy workplace environment. In this dissertation, a vegetable based lubricant is used to conduct mist, microstructure and wear analyses during end milling AISI 1018 steel using microlubrication. A two-flute solid carbide cutting tool was used with varying cutting speed and feed rate levels with a constant depth of cut. A full factorial experiment with Multivariate Analysis of Variance (MANOVA) was conducted and regression models were generated along with parameter optimization for the flank wear, aerosol mass concentration and the aerosol particle size. MANOVA indicated that the speed and feed variables main effects are significant, but the interaction of (speed*feed) was not significant at 95% confidence level. The model was able to predict 69.44%, 68.06% and 42.90% of the variation in the data for both the flank wear side 1 and 2 and aerosol mass concentration, respectively. An adequate signal-to-noise precision ratio more than 4 was obtained for the models, indicating adequate signal to use the model as a predictor for both the flank wear sides and aerosol mass concentration. The highest average mass concentration of 8.32 mg/m3 was realized using cutting speed of 80 Surface feet per minute (SFM) and a feed rate of 0.003 Inches per tooth (IPT). The lowest average mass concentration of 5.91 mg/m3 was realized using treatment 120 SFM and 0.005 IPT. The cutting performance under microlubrication is five times better in terms of tool life and two times better in terms of materials removal volume under low cutting speed and feed rate combination as compared to high cutting speed and feed rate combination. Abrasion was the dominant wear mechanism for all the cutting tools under consideration. Other than abrasion, sliding adhesive wear of the workpiece materials was also observed. The scanning electron microscope investigation of the used cutting tools revealed micro-fatigue cracks, welded micro-chips and unusual built-up edges on the cutting tools flank and rake side. Higher tool life was observed in the lowest cutting speed and feed rate combination. Transmission electron microscopy analysis at failure for the treatment 120 SFM and 0.005 IPT helped to quantify the dislocation densities. Electron backscatter diffraction (EBSD) identified 4 to 8 µm grain size growth on the machined surface due to residual stresses that are the driving force for the grain boundaries motion to reduce its overall energy resulting in the slight grain growth. EBSD also showed that (001) textured ferrite grains before machining exhibited randomly orientated grains after machining. The study shows that with a proper selection of the cutting parameters, it is possible to obtain higher tool life in end milling under microlubrication. But more scientific studies are needed to lower the mass concentration of the aerosol particles, below the recommended value of 5 mg/m3 established by Occupational Safety and Health Administration (OSHA).

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While wind energy has emerged as a popular source of renewable energy, the traditional wind turbine has an inherent limitation, namely that it only generates power in the presence of sufficiently high and consistent wind speeds. As a result, wind farms are typically built in areas with a high probability of the required wind speeds, which are geographically sparse. One way of overcoming this drawback is to tap into the energy available in winds at high altitudes which are not only consistent and of high magnitude, but also globally pervasive. An airborne wind energy device based upon the phenomenon of autorotation could potentially be used to exploit the abundance of wind of energy present at high altitudes. The work in this thesis first presents our study of a tethered-airfoil system as a candidate airborne wind energy (AWE) system. A mathematical model was used to show the feasibility of energy capture and the stability of the device in a wind field. Subsequently, the research identified the principle of autorotation to be better suited for high altitude energy harvesting. To this end, the thesis first presents a theoretical basis of the principle of autorotation, which is developed from existing models in literature. The model was adapted to predict aerodynamic conditions when used for harvesting energy. Encouraging simulation results prompted the main emphasis of this thesis, namely design of an experimental framework to corroborate the theory. Several experiments were devised to determine basic performance characteristics of an autogyro rotor and the data from each experiment is presented. A lab-scale experimental setup was developed as part of this thesis. The setup, consisting of a flapping-blade autogyro rotor and sensors, was used to acquire preliminary aerodynamic performance data. It is envisioned that refinements to this setup will ultimately provide a means of directly comparing analytical and experimental data. In this regard, we provide conclusions and make comments on improvements for future experiments.

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Electrical cabinet fires occur frequently in commercial and industrial facilities. However, the severity of these fire events varies widely, making it difficult to estimate the fire growth and size with certainty. This study aims to identify the significant parameters that affect electrical cabinet fires, which are quantified as the heat release rate (HRR), and properly categorize them. With this knowledge, optimal parameter-response relationships can be developed to predict the electrical cabinet fire behavior. Statistical analysis conducted in this study on historical fire incident data revealed that the fires in Nuclear Power Plants (NPP) were primarily associated with electrical cabinets. The database used in this research was an electronic version of the publicly available Updated Fire Event Database developed by Electric Power Research Institute, including 2,111 fire events. 540 of these events were labeled as being challenging fires with 74.2% of these challenging fire events being due to eleven selected fire types. Electrical cabinets were found to represent a majority (40.7%) of all the challenging fire events. Although historically conducted electrical cabinet fire experiments sought to explore the influence of parameters on HRR, the parameters were not systematically varied to statistically quantify which parameters were most important/relevant. Research in this study used statistical analysis on a series of simulation results on electrical cabinet fires from the computational fluid dynamics code Fire Dynamic Simulator (FDS). Simulation matrices were developed and evaluated using fractional factorial Design of Experiments (DOE) to screen the importance of different parameters on the electric cabinet HRR. Based on statistical analysis of the results, the combustible material surface area was found to be the most significant parameter followed by cabinet volume, combustible configuration, burning duration, and combustible material heat release rate per unit area. Material ignition temperature was found to not be statistically significant. The last phase of this research assessed the robustness of the electrical cabinet parameters on the predicted HRR with more detailed simulations. Two investigations were undertaken. To identify the nonlinear effects of parameters on the electrical cabinet fire HRR, a Response Surface Methodology (RSM) based Central Composite Design (CCD) was used to create a simulation matrix that would allow statistical analysis of important parameters as well as their effects on the fire heat release rate while keeping the combustible configuration inside the cabinet constant. A series of simulations were conducted to explore the impact of combustible configuration and ignition source location while keeping all other variables consistent. The analysis revealed that all variables had a statistically significant effect on peak HRR. For the average HRR, both the ventilation area into the cabinet and the ignition source HRR were found to be statistically insignificant. For both output variables, the cabinet volume, material heat release rate per unit area, and material surface area were the most significant parameters. Combustible configuration and ignition source location were also found to be statistically significant. / Master of Science / Electrical cabinet fires are a significant concern for industries, commercial electric plants, telecommunication buildings, and nuclear power plant (NPP) facilities. These cabinets typically represent a metallic enclosure of varying sizes. Additionally, several different electronic components of heterogenous composition and configuration are included within this cabinet. As a result, the fires within the cabinet can propagate to several other nearby components, resulting in large fires that are difficult to suppress. Thus, it becomes necessary to understand the fire behavior of electrical cabinets and the factors influencing fire propagation. Knowing the factors influencing the electrical cabinet fires will enable facilities to have better fire resilience and further prevent multiple components and structures from being damaged by these fires. Statistical analysis of historic fire events validated that the most frequently challenging fires in NPP involve electrical cabinets.Therefore, aA detailed study was conducted to investigate what parameters most significantly affect the size of the electrical cabinet fire, which is quantified as the heat release rate (HRR). The parameters in the study included cabinet volume, ventilation area, combustible fuel detail (ignition temperature, heat release rate per unit area (HRRPUA), burning duration), fuel configuration inside the cabinet, and size of the ignition source. To determine which of these factors significantly impacted the electrical cabinet HRR, a computational fluid dynamics code Fire Dynamic Simulator (FDS), was used to predict the fire growth of electrical cabinet fires. After employing a rigorous statistical analysis of the FDS results, the combustible material surface area was found to be the most significant parameter, followed by cabinet volume, combustible configuration, burning duration, and flammable material HRRPUA. The last phase of the research sought to explore the significance of the parameters while developing a nonlinear expression to predict the fire HRR based on cabinet parameters. Given the wide range of electrical cabinet parameters, especially combustible configuration, two studies were conducted where the configuration was fixed or varying with respect to other parameters. For fixed combustible configuration, simulations were conducted with FDS systematically varying the other parameters so their importance could be ranked. Simulations were also performed with all parameters fixed except the combustible configuration and ignition source location. The analysis revealed that all variables had a statistically significant impact on peak HRR. For the average HRR, both the ventilation area into the cabinet and the ignition source HRR were found to be statistically insignificant. For both output variables, the cabinet volume, material heat release rate per unit area, and material surface area were found to be the most significant parameters. Combustible configuration and ignition source location were also found to be statistically significant.