The article addresses an approximate solution to the multi-objective optimization problem for a black-box function of a manufacturing system. We employ the surrogate of the discrete-event simulation model of a batch production system in an analytical form. Integration of simulation, Design of Experiments methods, and Weighted Sum and Weighted Product multi-objective methods are used in an arrangement of a priori defined preferences to find a solution near the Pareto optimal solution in a criterion space. We compare the results obtained through the analytical approach to the outcomes of simulation-based optimization. The observed results indicate a possibility to apply the suitable analytical model for quickly finding the acceptable approximate solution close to the Pareto optimal front.

In an optimal processes control, where the considered goals are in general observed as concurrently conflicted, a multi-objective approach fits the best. Commonly used scalarization techniques in multi-objective optimization need a transformation of the individual single-objective functions involved into a scalar multi-criteria objective function. There are many parameters which can influence the optimization results solutions, including an unreachable utopia point value. In this study, the authors compare the multi-objective problem solutions found via two ways of the individual objectives transformation with the respect to setting the utopia point. The methods are used in the area of production control in a case study for a batch production system. To find the solutions, The Weighted Sum Method with a priori articulated preferences under specific constraints as the scalar multi-objective optimization method is applied in simulation optimization.

This work presents a comprehensive analysis of ball-end mill geometrical modification, with emphasis on surface quality and stability of the machining process. The study combines predictive modeling, analytical simulations, and experimental validation to evaluate the influence of cutting tool radius and process parameters on surface roughness. A composite factorial design of experiments was implemented to systematically investigate radius, stepover height, and inclination angle. Surface roughness was measured using a contact stylus profilometer, with secondary validation of selected samples by three-dimensional (3D) optical microscopy, ensuring robust verification of experimental outcomes. In addition, a two-dimensional (2D) computer-aided design (CAD)-based simulation model was developed to reconstruct toolpath overlaps and calculate roughness parameters for comparison. The predictive models were statistically compared with experimental and simulation results, showing consistent trends, while also highlighting deviations possibly due to process dynamics and cutting tool stability. Results indicate that ball-end mills with smaller radii demonstrate higher sensitivity to chatter and surface instability, while larger radii improve consistency as well as achievable roughness values. The combined methodology provides both practical and theoretical insights into optimizing cutting tool geometry for precision milling. The findings are relevant for cutting tool designers and manufacturing engineers seeking to balance productivity, cost, and surface integrity in finishing operations.

The paper deals with the solution of the first–order passive filters (low–pass and high–pass) applying electrotechnical elements (resistor, capacitor - analogue filter) and digital Butterworth filter type IIR (Infinite Impulse Response). Procedure of the filters design and implementation is described, and the analogue and digital filter outputs with the same input signal are compared. The designed filters have already served for education purposes with the intention to bring an explanation of techniques for designing required functionality of the signal processing filters.

The effort of universities is to prepare their graduates for their future career by providing them with sufficient knowledge and skills that can be used and further developed in their practice. In our contribution we focused on the use of the online computational tool Wolfram Alpha (Wolfram|Alpha) for increase of computation efficiency that could help future technical engineers in the realization of this goal. The utilization of this scientific search engine is presented by the way of an example of Laplace transform applied in ordinary differential equations solving, which is commonly used in theory of automation and processes control. Some problems related to the use of this tool are discussed too.