Surface roughness is an important parameter in the automotive Industry. This thesis is a study conducted in collaboration with QSO Interferometer systems AB (QSAB), Halmstad. The study is focused on the existing surface roughness parameters used in the automotive industry and the relationship to the CWS parameters of QISAB. The study also investigates the scope of CWS instrument developed by QISAB as a next-generation automated surface testing inline instrument. The initial study which has been conducted had 5 stages, those are the history of roughness measurement, the basic CWS parameters, the currently used surface testing instruments in the automobile industry, the use of surface metrology in the manufacturing industry and the basic principle and theory of the CWS. As the final stage to achieve the aim of the thesis a quantitative study has been conducted to compare the existing parameters with CWS parameters. The three type of comparison were done on a test piece having different range of surface roughness after different stages of grinding. These three comparisons that had been done were CWS v/s White light interferometer v/s visual inspection. The results from those quantitative analysis did support the results from the qualitative analysis.

This master´s thesis deals with calibration and determination of uncertainties of measurement for focus variation microscope Alicona Infinite Focus G4. Together with calibration, a measurement of chosen parameters with calculation of measurement uncertainties of a component was realised. The thesis also describes the whole calibration process and terminology used in calibration, as well as the calibrated instrument, it´s parameters and usage in practice. The measurements were realized on premises of Intemac Solutions s.r.o. Obtained data were than processed using MS Excel, Gwyddion and TalyMap software. At the end of the thesis, practical recommendations are formulated.

This master’s thesis deals with the use of a coordinate measuring machine probe for surface texture evaluation. The thesis’ goals were to describe the Renishaw’s SFP2 probe, to analyze the measurement system of the probe and a common stylus instrument, to carry out a demonstrative measurement, to analyze measurement results and to give practical recommendations. The measurement system analysis of the SFP2 consists in the evaluation of minimal specification limits of selected roughness parameters, for which gauge capability can be proven. The analysis results are compared with the results of the measurement system analysis of the Surtronic 25 profilometer. The differences in the measuring processes of mentioned devices are demonstrated by surface texture inspection of torque converter body. For the measurement result analysis, uncertainties in the selected surface texture parameters are calculated in two ways. Finally, recommendations for the producer of the probe and for its users are worked out. The results of this thesis may contribute to a wider use of a coordinate measuring machines for surface quality evaluation.

Surface quality plays a vital role in controlling the function performance of the workpiece. With the development of the measuring technique, areal surface measurement has been widely applied in the industry. However, estimating the uncertainty of areal surface measurement is still a challenge. Except for the metrological characteristics of the measurement system, measurement conditions should be considered for uncertainty evaluation. The dissertation investigates the influence of measurement settings on surface measurement. A silver-plated surface, three different rough grinding surfaces, and three different rough cylindrical grinding surfaces were measured using structured illumination microscopy. The measurements were at the different objective lenses, vertical scanning interval, exposure time, and sample tilt. The results show that the measurement settings influence the non-measured points, measurement noise, and areal surface texture parameters. Therefore, according to the investigation, the sample tilt and exposure time should also be included in the uncertainty budget. An approach was proposed to investigate the influence of non-measured points on the areal surface texture parameters. The relation between the non-measured points ratio and measurement settings was investigated, and how the areal surface texture parameters changed due to the non-measured points was studied. Moreover, an approach based on the metrological characteristic method was proposed to estimate the uncertainty due to the measurement noise. This method can be extended to the uncertainty evaluation due to other metrological characteristics. Additionally, an approach based on the Monte Carlo Method was proposed to estimate the measurement uncertainty due to different influences. This approach was verified as feasible in the practical measurement.

Additive Manufacturing (AM) is on the verge of causing a downfall to conventional manufacturing with its huge potential in part manufacture. With an increase in demand for customized product, on-demand production and sustainable manufacturing, AM is gaining a great deal of attention from different industries in recent years. AM is redefining product design by revolutionizing how products are made. AM is extensively utilized in automotive, aerospace, medical and dental applications for its ability to produce intricate and lightweight structures. Despite their popularity, AM has not fully replaced traditional methods with one of the many reasons being inferior surface quality. Surface texture plays a crucial role in the functionality of a component and can cause serious problems to the manufactured parts if left untreated. Therefore, it is necessary to fully understand the surface behavior concerning the factors affecting it to establish control over the surface quality. The challenge with AM is that it generates surfaces that are different compared to conventional manufacturing techniques and varies with respect to different materials, geometries and process parameters. Therefore, AM surfaces often require novel characterization approaches to fully explain the manufacturing process. Most of the previously published work has been broadly based on two-dimensional parametric measurements. Some researchers have already addressed the AM surfaces with areal surface texture parameters but mostly used average parameters for characterization which is still distant from a full surface and functional interpretation. There has been a continual effort in improving the characterization of AM surfaces using different methods and one such effort is presented in this thesis. The primary focus of this thesis is to get a better understanding of AM surfaces to facilitate process control and optimization. For this purpose, the surface texture of Fused Deposition Modeling (FDM) and Laser-based Powder Bed Fusion of Metals (PBF-LB/M) have been characterized using various tools such as Power Spectral Density (PSD), Scale-sensitive fractal analysis based on area-scale relations, feature-based characterization and quantitative characterization by both profile and areal surface texture parameters. A methodology was developed using a Linear multiple regression and a combination of the above-mentioned characterization techniques to identify the most significant parameters for discriminating different surfaces and also to understand the manufacturing process. The results suggest that the developed approaches can be used as a guideline for AM users who are looking to optimize the process for gaining better surface quality and component functionality, as it works effectively in finding the significant parameters representing the unique signatures of the manufacturing process. Future work involves improving the accuracy of the results by implementing improved statistical models and testing other characterization methods to enhance the quality and function of the parts produced by the AM process.