This article presents a methodology for assessing investment projects representing the sequence of steps necessary for a comprehensive assessment and optimization of an investment project. The assessment process starts with the quantitative forecasting of stochastic input factors, with the selection of risk factors and the definition of their uncertainty. That is followed by the design of a mathematical model for calculating the criterion of economic efficiency of investment, its calculation mathematically, and forecasting by Monte Carlo simulation. The simulation output is assessed from the point of view of risk, and in case of an unacceptable result, the possibilities for project optimization are proposed. Finally, the proposed methodology was applied to an investment project model, where individual principles are practically demonstrated.

The role and position of the manufacturing sector changes over time. Its importance in the sustainable growth of the economy, innovations, trade, reducing energy demand, and environmental problems is currently being shown again. The study underlines the significance and importance of the manufacturing sector in the economy of countries, and the generally applicable economic principles are explicitly examined in regard to the manufacturing sector. It examines whether selected economic indicators of the manufacturing sector in the region of the Visegrad Group countries can affect the level of average wages in the sector. Wages represent a key determinant of attractiveness, as well as the potential to increase the standards of living and the long-term sustainability of a given sector. The selected economic indicators for the period 2008–2019 concerning average wages in the manufacturing sector were: FDI Flow, GDP, labour productivity, employment, and the number of hours worked in the manufacturing sector. The source of secondary data was the OECD database. A multiple regression model was used and tested. The suitability of the proposed model was tested using the ANOVA method. A significant effect was shown in the case of two of the examined variables, namely the GDP and employment in the manufacturing sector. Based on the findings of the study, it can be assumed that the sectoral GDP can positively affect average wages in the sector and the level of employment in manufacturing can negatively affect them. The summary of implications and proposals indirectly supports the need to develop and introduce innovations, new technologies, automation, and robotization, as well as for further implementation and support of Industry 4.0 and 5.0.

The current mechanical engineering is inconceivable without the implementation of CAx systems in design and manufacturing process of individual components. The automotive industry is a clear evidence of how CAx systems affect the innovation cy...

The purpose of this article is to point out the need to use software simulation tools in industrial practice to optimize the production process and assess the economic effectiveness of investment, including risk. The goal of the research is to find an optimal investment variant to ensure an increase in the production volume of at least 50% and to achieve the maximum economic efficiency of the investment, even considering the risk. The article presents a comprehensive approach that enables the achievement of the set research goal. The selection of the optimal version of the investment is carried out in three steps. Firstly, the versions of the investment variants are assessed from the production point of view using the program Tecnomatix Plant Simulation. Subsequently, the versions of the investment variants are assessed from an economic point of view and from a risk point of view. Economic efficiency is assessed using the financial criteria net present value (NPV), profitability index (PI), and discounted payback period (DPP), and risk analysis is carried out using Monte Carlo simulations. Finally, the accepted outputs are evaluated overall using a multi-criteria method, namely the method of partial order.