Article deals with the application of selected tools of statistical process control, through which we can achieve continuous quality improvement. The advantage of these tools is that they can identify the effects of the processes that cause unnatural variability in processes that result of errors and poor quality. Tools like capability index, histogram, model DMAIC, control chart, etc. can reliably determine the anomalous variability in the process and thereby contribute to quality improvement. In the paper through histograms and Shewhart control charts action exposing the systemic implications of the processes and therefore unnatural variability in processes, which result in non-compliance. The results clearly show that through the DMAIC model can systematically improve quality. Histograms show the contribution of the normal distribution of frequencies monitored quality characteristics while Shewhart control charts show that the investigated processes are under statistical control. Use of DMAIC model as well as other statistical quality tools is a way to achieve continuous quality improvement.

This paper deals with the issue of increasing the quality and sustainability of education at universities regarding the requirements of employers. Employers’ expectations of university graduates in terms of soft skills are analysed and outlined. The employers participating in this study answered a questionnaire survey focused on understanding university graduates’ soft skills. The collected results were subjected to the method of mathematical–statistical analysis by nonparametric testing of significance of the mean value difference. The significance of the difference for individual skills was confirmed, demonstrating that the surveyed enterprises required and anticipated a level of soft skills development on the part of recent graduates that was insufficient. This finding implies the necessity of improving university education to match the expected and real state of soft skill mastery.

This research paper examines the issue of quality management practices (QMPs) as a supporting tool for managing and improving the performance and competitiveness of enterprises. The aim of the paper is to present the interconnection of the practical use of QMPs concerning the performance in the Slovak manufacturing enterprises. One of the main causal factors that may influence the different utilization of QMPs is the capital structure of the surveyed enterprises. The consequence factor is the achieved performance, parameterized in this research through Return on Sales. During the period 2020 to 2021, 364 manufacturing enterprises were interviewed through a questionnaire. In order to keep the population, the industrial structure stratified sampling method was applied and the sample representativeness was assessed by using the Chi-square goodness-of-fit test. Pearson’s chi-square test, interval estimates of proportions, and analysis of contingency were implemented to test the stated research hypotheses. The results of performed analyses revealed the existence of significant relations among capital structure, the scale of the use of QMPs and performance measured by Return on Sales. The survey results also point to differences in the practical use of quality management within the analysed industries. The difference factor is the size of the enterprise, the industry itself, and partly also the technology and performance of the industry given by the added value. At the same time, space for the implementation of selected approaches and concepts related to quality management in manufacturing enterprises that have the potential for more effective management has been identified to increase competitiveness.

The main aim of this paper is to illustrate the application of selected methods and procedures in the implementation of the Six Sigma Methodology in the furniture manufacturing processes, specifically in the wood veneer pressing, to verify the application and to evaluate the benefits of using selected methods and procedures through a series of step DMAIC process improvement. The application of selected methods and tools within the Six Sigma Methodology, such as DPMO, efficiency and sigma levels, project charter, histogram of mistakes caused by the application of the adhesive, the SIPOC plot mapping process, reaction plans, Ishikawa diagram and control diagrams bring the system and clarity of measurable results into project management for process improvement and process change. The benefits of their use are the cost savings and performance improvement processes.

The aim of the paper is to point out the principles of process management and selected quality management tools, which are aimed at improving the processes of the wood processing industries of the Slovak Republic. The knowledge from these areas is based on the analysis of the theoretical origins from domestic and foreign sources and supported by the results of the research carried out in the first half of the year 2017. In the processing of the results, classical methods of research work were used such as analysis, synthesis, comparison, descriptive statistics, contingency tables, chi-quadrat test and graphic depiction. Based on the analysis of the research results, there was a slight dependence between the process optimization levels in the timber industry and other process improvement methods such as statistical process control methods and graphical analysis and problem solving tools.

The aim of the article is to present the results of a case study focused on the implementation of the Six Sigma methodology in order to improve the quality and increase the efficiency of furniture production processes. Positive results of implementation after the implementation of corrective measures were achieved in the values of process capability coefficients, reduction of nonconformities and subsequent reduction of DPMO, increase of the values of the level of efficiency and sigma of the critical process.In the processing of the results, classical methods of research work were used such as analysis, synthesis, comparison, descriptive statistics, coefficients Cp a Cpk, DPMO, level of efficienty and sigma,and also graphic methods.