In intelligent manufacturing, the phase content and physical and mechanical properties of construction materials can vary due to different suppliers of blanks manufacturers. Therefore, evaluating the composition and properties for implementing a decision-making approach in material selection using up-to-date software is a topical problem in smart manufacturing. Therefore, the article aims to develop a comprehensive automated material selection approach. The proposed method is based on the comprehensive use of normalization and probability approaches and the linear regression procedure formulated in a matrix form. As a result of the study, analytical dependencies for automated material selection were developed. Based on the hypotheses about the impact of the phase composition on physical and mechanical properties, the proposed approach was proven qualitatively and quantitively for carbon steels from AISI 1010 to AISI 1060. The achieved results allowed evaluating the phase composition and physical properties for an arbitrary material from a particular group by its mechanical properties. Overall, an automated material selection approach based on decision-making criteria is helpful for mechanical engineering, smart manufacturing, and industrial engineering purposes.

The article is focused on the comprehensive analysis of the aerodynamics of air distribution devices with the combined heat and mass exchange, with the aim to improve the following hydro- and thermodynamic parameters of ventilation systems: flow rate, air velocity, hydraulic losses, and temperature. The inadequacy of the previously obtained characteristics has confirmed the need for more rational designs of air distribution systems. Consequently, the use of perforated plates was proposed to increase hydraulic losses for reducing the average velocity and ensuring a uniform distribution of the velocity field on the outlet of the device. The effectiveness of one of the five possible designs usage is confirmed by the results of numerical simulation. The coefficient of hydraulic losses decreased by 2.5–3.0 times, as well as the uniformity of the outlet velocity field for the air flow being provided. Based on the three-factor factorial experiment, the linear mathematical model was obtained for determining the dependence of the average velocity on the flow rate, plate’s area, and diameter of holes. This model was significantly improved using the multiparameter quasi-linear regression analysis. As a result, the nonlinear mathematical models were obtained, allowing the analytical determination of the hydraulic losses and average velocity of the air flow. Additionally, the dependencies for determining the relative error of measuring the average velocity were obtained.

This article is devoted to a detailed description of the developed physical model of the pneumatic classification process for detecting the rotating suspended layer and ensuring the frequency of loading and unloading of a pneumatic classifier. The related mathematical model is developed for estimating the non-stationary concentration of fine particles in a gas-dispersed flow with respect to time and height of the working space of the apparatus. The research is aimed at developing a pneumatic classification method for granular materials using a rhomb-shaped apparatus and ensuring the reliability of the operating process based on the influence of the flow on the granular material concentrations. The obtained experimental results allow evaluating the rational geometrical parameters of the working space in pneumatic granulators, as well as verifying the proposed mathematical model based on the implementation of the quasi-linear regression procedure. It is shown that the rhomb-shaped pneumatic classifier provides effective separation of granular material, reaching up to 95% of the target fraction. As a result, the proposed methodology can be implemented for optimizing geometrical profiles of pneumatic classifiers in terms of defining the required technological parameters of the pneumatic classification process.

The article deals with the possibility of efficient control of small and medium-scale biomass-fired boilers by implementing low-cost sensors to sense the trend of carbon monoxide emissions into control of the biomass combustion process. Based on the theoretical analysis, a principle block diagram of the process control system was designed for the possibility of providing near-optimal control of the biomass combustion regardless of its quality parameters. A cost-effective hardware solution to obtain the dependence of CO emissions on O₂ concentration in flue gas during combustion and new control algorithms was implemented into the process control and monitoring system of the biomass-fired boilers to test them in the real operation. A description of the designed control system, a data analysis of the monitored values and their impact on combustion process, and some results of the implemented control of the real biomass combustion process are presented in the article.

Permanently increasing requirements for the accuracy of abrasive jet machining (AJM) predetermine a need to increase requirements for the rational choice of the related energy-efficient technological equipment. Due to the relatively cheap and high-quality cleaning of materials from contaminants using AJM, the problem of increasing the energy efficiency of the corresponding equipment based on the rational choice of nozzle geometry becomes more topical. This is also because the working nozzle is a consumable part that requires periodic replacements. Therefore, this article deals with rational designing working nozzles as a reliable way to decrease the power consumption of the compressor equipment while engaging in AJM. For this purpose, experimental and numerical studies of the operating processes in the nozzle were carried out. The main idea of increasing the nozzle’s efficiency was to reduce the contact area between the working flow and the nozzle. Due to this, the friction of the abrasive material with its walls was decreased. As a result, the AJM was accelerated, and the energy consumption of the corresponding compressor equipment was reduced. The research showed that a decrease in the nozzle’s length up to 4 mm increased the flow ratio by 84% and decreased the energy consumption of the 40 kW compressor unit by 4.5 times.

The paper deals with the special filtration method using a filter with membership function. The paper presents a model of a filter, its specific characteristics and some parameters that have an impact on quality of filtration. A filter with different membership functions (Gauss, Bell, Power and Triangle) was designed and tested for specific demands, which followed from the experience with the realization of a biomass combustion control system. Data obtained from the combustion process were extremely noisy (influenced by various transfer errors, disturbances and external interferences) and, therefore, had to be properly filtered. The paper also describes some results of filter simulation in the Matlab Simulink environment and its implementation into an on-line monitored process control system of biomass combustion. It was proven by implementation that such a filter can be useful for the signal filtering of oxygen concentration and carbon monoxide emission sensing and it can be very useful in reducing signal interferences arising in biomass combustion.