The purpose of this study is to examine the projectile penetration resistance of the base metal and heat-affected zones of armor steel weldments. To ensure the proper quality of armor steel welded joints and associated ballistic protection, it is important to find the optimum heat input for armor steel welding. A total of two armor steel weldments made at heat inputs of 1.29 kJ/mm and 1.55 kJ/mm were tested for ballistic protection performance. The GMAW welding carried out employing a robot-controlled process. Owing to a higher ballistic limit, the heat-affected zone (HAZ) of the 1.29 kJ/mm weldment was found to be more resistant to projectile penetration than that of the 1.55 kJ/mm weldment. The ballistic performance of the weldments was determined by analyzing the microstructure of weldment heat-affected zones, the hardness gradients across the weldments and the thermal history of the welding heat inputs considered. The result showed that the ballistic resistance of heat affected zone exist as the heat input was decreased on 1.29 kJ/mm. It was found that 1.55 kJ/mm does not have ballistic resistance.

A significant number of recent scientific papers have raised awareness of changes in the biological world of bees, problems with their extinction, and, as a consequence, their impact on humans and the environment. This work relies on precision beekeeping in apiculture and raises the scale of measurement and prediction results using the system we developed, which was designed to cover beehive ecosystem. It is equipped with an IoT modular base station that collects a wide range of parameters from sensors on the hive and a bee counter at the hive entrance. Data are sent to the cloud for storage, analysis, and alarm generation. A time-series forecasting model capable of estimating the volume of bee exits and entrances per hour, which simulates dependence between environmental conditions and bee activity, was devised. The applied mathematical models based on recurrent neural networks exhibited high accuracy. A web application for monitoring and prediction displays parameters, measured values, and predictive and analytical alarms in real time. The predictive component utilizes artificial intelligence by applying advanced analytical methods to find correlation between sensor data and the behavioral patterns of bees, and to raise alarms should it detect deviations. The analytical component raises an alarm when it detects measured values that lie outside of the predetermined safety limits. Comparisons of the experimental data with the model showed that our model represents the observed processes well.

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The present study was undertaken to investigate, the level of volatile organic compounds (VOCs) in working zone of flex printing facility in Novi Sad, Serbia. The levels of VOCs were determined at four sampling position: at the machine; at a distance of 3 m from the machine; at the outlet of machine, entrance in digester and at the exit of the digester. The quantitative determination of VOCs compounds was performed using portable Voc Pro Photovac. The VOCs concentrations varied within 8h sampling period and they differ between sampling position. The highest concentration was measured at the outlet of machine, entrance in digester, while the lowest at a distance of 3 m from the machine. The obtained levels of VOCs exceed their level advised by OSHA and NIOSH standard. Therefore, this paper provide propositions on improving the process of flexographic printing, and therefore, human health and environmental.

The area of maintenance has for long not been simple replacement of a part after its failure. The trend in maintenance today is to keep up with the development of computer technologies, which are increasingly being used. The education in the field of maintenance should also take this direction. This paper points to such an orientation, its goal being to point at the possibility of applying modern technologies, above all, information technologies, to the traditional areas, such as machine maintenance. The paper provides empirical data reflecting the chronology of modernizing the teaching methods in the subject Graphic Machinery and Maintenance.