applied sciences Article Application of Statistical Methods to Analyze the Quality of Electronic Circuits Assembly [PERSON] 1,* and [PERSON] 2  
standards, the necessary documentation, the method of parameter control, and the appropriate actions to achieve them. It is important to develop appropriate methods, tools or systems to describe and set the required limits, within which a given process should take place [5; 6; 7; 8]. In order to ensure compliance with the standards, it is necessary to meet the requirements described in the standards and prove that the implemented solutions fully cover them. A qualitative approach to the development and manufacture of electronic devices is described in the paper [8]. Many papers concern the problem of the analysis of an influence of selected factors on electrical and thermal properties of soldering joints [9; 10; 11; 12; 13; 14; 15; 16]. The papers [9; 10; 11] describe the influence of selected ceramic additions to the soldering alloy on such properties. The structures of soldering joints are presented and discussed in [12; 13]. Some failures of soldering joints are analyzed in [14]. Thermal vias in PCBs are the aim of the paper [15]. Mechanical properties of the composite solder with TiO\({}_{2}\) nanoparticles are described in [16]. In the paper [17], the problem of the effective analysis of the properties of PCB using Ansys Electronics software is addressed. Particularly, the identification method of the parasitic elements of the PCB on the base of the layout of this PCB is described. The mathematical model of the PCB designed for the half-bridge module is presented. It is shown that, using the PCB CAD procedure, some parasitic effects of the considered module can be properly analyzed. The introduction of such standards in the field of the control of the parameters of production processes, or in the field of determining the limit values of technical parameters for the proper operation of a newly designed product, requires the measurement methods to also be standardized [18]. Statistical tools that accurately confirm that the obtained results are not only related to the measurements for one prototype are introduced, but they attribute the obtained results to the entire population of such products. One of the most frequently used tools of this type is the methodology based on statistical assumptions called the Six Sigma (6 Sigma). This methodology was introduced in the mid-1980s by [PERSON] and [PERSON] from Motorola [19], for which the company received the American Quality Award in 1988 [20]. The described methodology was derived from the Motorola philosophy, which stated: \"quality cannot cost\" [19]. In order to define what exactly 6 Sigma is, many scientific papers have been written [1; 2; 3; 21; 22]. There are several trends informing this methodology, which offers a set of statistical tools adopted as part of quality management in order to develop a framework for improving processes in an enterprise [1; 2; 3]. Six Sigma is a structured, data-driven, problem-solving method that focuses on reducing errors and variability in business-critical processes. As a result, it serves to improve customer satisfaction. A statistical measure of process variability is the standard deviation \(\sigma\). The 6 Sigma methodology is characterized by 6 standard deviations between the process mean and the closest specification limit [21]. The use of the 6 Sigma method in an enterprise to analyze the conducted processes is a guarantee of the involvement of the top management and employees in the organization. The application for performing research and statistical analyses of the collected data is the Mini-tab Statistical Software [22; 23; 24]. In the soldering process of electronics modules, the problem of the control of void size is very important.