Measurement uncertainty is a crucial indicator of the quality of measurement results. Before expressing the value of measurement uncertainty, a comprehensive assessment of the impact of all parameters on the measurement process is conducted, followed by the establishment of a mathematical model describing the measured quantity. In the context of atomic force microscopy, where numerous influential parameters exist and functional relationships between the output and input quantities are nonlinear, the measurement uncertainty of the results has not been estimated. Atomic force microscopy operates on the principle of scanning the surface of samples and is employed in various scientific disciplines. The measurement result obtained through atomic force microscopy provides a topographic image of the measured sample surface in both 2D and 3D formats, along with associated surface topography parameters. Chapter 1: Introduction The first chapter encompasses an elaborate account of motivation for the research, objectives and hypotheses, as well as an in-depth exposition of the research methods and plan. Additionally, it outlines the anticipated scientific contributions stemming from this study. A comprehensive literature review is provided, underscoring the significance of measurement uncertainty on measurement outcomes. Currently, the measurement uncertainty of industrial, commercial atomic force microscope results has not been evaluated. Additionally, there are no existing guidelines or instructions in the field of atomic force microscopy that analyze the impact of input parameters on the quality of measurement outcomes. Chapter 2: Atomic force microscope in dimensional nanometrology This chapter comprehensively explores the AFM measurement system, detailing its operational modes (contact, non-contact, tapping) and the intricate forces between the probe and sample at the atomic level. Post-measurement image processing involves leveling and sophisticated filters to extract precise surface roughness parameters and address artifacts. The chapter presents essential surface parameters, facilitating comprehensive analysis of sample topography. Emphasis is placed on artifact impact and strategies for identification and mitigation, ensuring accurate AFM measurements. Overall, the AFM technique emerges as a potent tool for nanoscale surface analysis with broad scientific applications. Chapter 3: Measurement uncertainty This chapter elucidates the concept of measurement uncertainty and highlights the significance of its application. Three methods for estimating measurement uncertainty are described: the Guide to the Expression of Uncertainty in Measurement (GUM) method, Monte Carlo simulation method and Bayesian method. The GUM method requires knowledge of uncertainty components, which can be categorized into two groups: Type A and Type B uncertainties. The process of calculating measurement uncertainty using the GUM method is detailed. The Monte Carlo simulation method is a numerical technique based on generating numerous random values and analyzing the resulting data to obtain information about the best estimate of the output variable. This method allows the consideration of various sources of uncertainty and the generation of many sample measurements, making it a more accurate and comprehensive approach to estimating measurement uncertainty compared to the GUM method. In the Bayesian method, the parameter distribution is treated as a random variable with its own distribution, referred to as the prior distribution. When new measurements are taken while having prior knowledge of input data, the Bayesian formula can be used to determine the posterior distribution of the new set of measurement results. This approach allows for an iterative updating of measurement uncertainty as new data becomes available. Chapter 4: Experimental research The fourth chapter is dedicated to the description of the conducted experimental investigations. The experimental investigations were focused on exploring the influential parameters present throughout the entire measurement process. Experimental research was conducted on AFM reference standards. A well-designed experiment plan was executed to determine the influential input parameters during scanning. The study explored the influence of the probe on measurement outcomes. The repeatability and reproducibility of the measurement results were thoroughly analyzed. Additionally, the impact of filtering on measurement outcomes was investigated. Moreover, inter-laboratory comparative measurements were carried out between four laboratories. The calculated agreement factor, En, was used to compare the measurement results with known reference values. These comprehensive experimental efforts contribute to a better understanding of measurement accuracy and reliability in AFM, ensuring the quality and trustworthiness of the obtained results. Chapter 5: Measurement uncertainty evaluation This chapter provides an evaluation of the measurement uncertainty of the reference standard's step height h and areal topography parameters Sa and Sz. A mathematical model dependent on input parameters was formulated and probability density functions were provided for each input variable. The measurement uncertainty was assessed using both the Monte Carlo simulation and Bayesian methods. To represent the comprehensive measurement results, a 95 percent coverage interval was determined for the output variable. These advanced analytical techniques contribute to a thorough understanding of measurement accuracy and provide a comprehensive portrayal of the obtained results. Chapter 6: Conclusion The last chapter of the doctoral thesis encompasses a comprehensive summary of the conducted research, where ultimate conclusions are derived and propositions for future investigations are proposed.