Gears are essential machine elements that are exposed to heavy loads. In some cases, gearboxes are critical elements since they serve as machine drivers that must operate almost every day for a more extended period, such as years or even tens of years. Any interruption due to gear failures can cause significant losses, and therefore it is necessary to have a monitoring system that will ensure proper operation. Tooth surface damage is a common occurrence in operating gears. One of the most common types of damage to teeth surfaces is pitting. It is necessary for normal gear operations to regularly determine the occurrence and span of a damaged tooth surface caused by pitting. In this paper, we propose a machine vision system as part of the inspection process for detecting pitting and monitoring its progression. The implemented inspection system uses a faster R-CNN network to identify and position pitting on a specific tooth, which enables monitoring. Prediction confidence values of pitting damage detection are between 99.5–99.9%, while prediction confidence values for teeth recognized as crucial for monitoring are between 97–99%.

Nowadays, most disinfection robots have a bulky design or large dimensions, making it harder for them to operate in small, tight and narrow spaces from the medical environment and other facilities. The solution for disinfecting the hard-to-reach areas is to use disinfection robots with folding mechanism. They can operate in different configurations, making it easier for them to access the areas where the space is limited. More specifically, their folded position (minimum position) can be used to disinfect the area under the hospital beds, which is known to be a reservoir of infectious agents, while their extended position (maximum position) can be used for the general disinfection. The paper presents the characteristics of the currently available disinfection robots and how using robots with folding mechanism would overcome their limitations and improve the overall quality and efficiency of the disinfection process.

The five-bar linkage, used in the form of a planar manipulator, benefits from easy controllability and relatively simple kinematic structures, which mean that it can be used in several applications in robotics, rehabilitation, and haptic devices, etc. This paper proposes an optimal synthesis method for a symmetrical five-bar linkage of type 5-RRRRR, with a singularity-free dexterous workspace, based on workspaces with predefined shapes, like squares, rectangles, triangles, circles, and ellipses. The synthesis conditions, to avoid singularities, are given as inequations, which can be further substituted with a system of equations, by introducing the supraunitary coefficient, k. The analytical solutions of the resulting system of equations enable the computation of the link lengths of the five-bar linkage. The optimization method provides the optimal value of the supraunitary coefficient, in order to obtain a maximum value for the minimum input transmission angle and a minimum value for the manipulator size. In this paper, the authors present an analytical approach to the optimal synthesis of a symmetrical five-bar linkage for different shapes of workspace, with the same surface and coordinates in terms of the mass center, as well as the resulting link lengths. In regard to the numerical examples, the authors considered and compared performance indices, such as manipulability, the condition number, and stiffness. The considered examples showed that an equilateral triangle-shaped workspace achieved higher global manipulability, a square-shaped workspace achieved higher global dexterity and the minimum input transmission angle, and circular workspaces achieved the highest mean stiffness and total surface size. It was observed that the synthesis method generates structures that are well-suited to singularity-free dexterous workspaces, with nonzero stiffness values.

Currently, artificial intelligence and intelligent algorithms for the control of dynamic systems are the main focus for building Industry 4.0 services and developing novel, innovative industrial solutions. This paper proposes a novel intelligent control structure specifically tailored for treating environmental stimuli and disturbances in operational environments of dynamic systems. The structure is based on the Orthogonal Endocrine Neural Network (OENN) and Artificial Orthogonal Glands (AOGs). The operational mechanism of each AOG acquires and processes environmental stimuli and generates artificial hormone concentration values at the gland output. These values are introduced to the appropriate OENN layer to provoke the network with collected environmental insights. To verify the applicability of the proposed structure on a complex dynamical nonlinear system, it was tested in a laboratory environment on the laboratory magnetic levitation system (MLS). The main experimental goal was to test the tracking performance of a levitation object when the new control logic was applied. The results were compared with two additional intelligent algorithms and a default linear quadratic (LQ) control logic. OENN + AOG structure showed improved tracking performances compared with traditional LQ control and better adaptability to environmental conditions compared with similar existing solutions.

Mechanical behavior and characteristics of two different types of materials: cast iron with lamellar graphite EN-GJL-250 and cast iron with spheroidal graphite EN-GJS-400-15 which were cast in ceramic molds using gravitational casting method has considered in this research. The ceramic molds were obtained by 3D printing method. First, a finite element analysis was developed to determine Tresca and von Mises stresses and the deformations of the ceramic molds under an applied pressure of 25 MPa. Samples were produced by gravitational casting using two types of cast iron materials. Mechanical tests were made using samples produced from these two types of materials and microstructure analysis evaluation of fractured zones was realized by scanning electron microscopy. Obtained results were finally used for designing, developing, and producing of one ‘hydraulic block’ of a railway installation by the Benninger Guss company of Switzerland.