The integration of machine vision systems with programmable logic controllers (PLCs) is increasingly crucial for automated quality assurance in Industry 4.0 environments. This paper presents an applied case study of vision–PLC integration, focusing on real-time synchronization, deterministic communication, and practical industrial deployment. The proposed platform combines a Cognex In-Sight 2802C smart camera (Cognex Corporation, Natick, MA, USA) with an Allen-Bradley Compact GuardLogix PLC through Ethernet/IP implicit cyclic exchange. Three representative case studies were investigated: 3D-printed prototypes with controlled defects, automotive electrical connectors inspected using Cognex ViDi supervised learning tools, and fiber optic tubes evaluated via a custom fixture-based heuristic method. Across all scenarios, detection accuracy exceeded 95%, while PLC-level triple verification reduced false classifications by 28% compared to camera-only operation. The work highlights the benefits of PLC-driven inspection, including robustness, real-time performance, and dynamic tolerance adjustment via HMI interfaces. At the same time, several limitations were identified, including sensitivity to lighting variations, limited dataset size, and challenges in scaling to full production environments. These findings demonstrate a replicable integration framework that supports intelligent manufacturing. Future research will focus on hybrid AI–PLC architectures, extended validation on industrial production lines, and predictive maintenance enabled by edge computing.

Automated monitoring of cutting tool wear is of paramount importance in the manufacturing industry, as it directly impacts production efficiency and product quality. Traditional manual inspection methods are time-consuming and prone to human error, necessitating the adoption of more advanced techniques. This study explores the application of ViDiDetect, a deep learning-based defect detection solution, in the context of machine vision for assessing cutting tool wear. By capturing high-resolution images of machining tools and analyzing wear patterns, machine vision systems offer a non-contact and non-destructive approach to tool wear assessment, enabling continuous monitoring without disrupting the machining process. In this research, a smart camera and an illuminator were utilized to capture images of a car suspension knuckle’s machined surface, with a focus on detecting burrs, chips, and tool wear. The study also employed a mask to narrow the region of interest and enhance classification accuracy. This investigation demonstrates the potential of machine vision and ViDiDetect in automating cutting tool wear assessment, ultimately enhancing manufacturing processes’ efficiency and product quality. The project is at the implementation stage in one of the automotive production plants located in southern Poland.

In this article, an application of a three-dimensional scanner for building a special diagnostic stand is described. An experimental method of detection of material defects is discussed. The considered defects are connected with cooperation of particular surfaces of machine parts. In the discussed experiments, particularly the dimensions of pitting holes can be evaluated. Availability of laboratory facilities required that the investigations were performed using geared wheels. The three-dimensional model which represents a degenerated surface, obtained based upon the diagnostic measurements, was compared with the pattern of an undamaged surface. The latter was generated by means of our pre-processor. The pre-processor enables generation of files which are compatible with the majority of the computer-aided design system formats. Therefore, the analyses were performed by means of commercial system inventor and computer-aided three-dimensional interactive application.

So far it is believed that, for every series-parallel planetary gear system (PGS), as a coupled gear, a very harmful phenomenon of power circulation must occur in at least one of its closed circuits. In this paper (Part I) and in the next two (Part II and Part III), it will be shown that it is possible to construct a three-row series-parallel PGS in which this phenomenon can be avoided. For this purpose, in Part I, a detailed analysis of the kinematics and statics of a planetary gear with power circulation inside a closed loop was carried out. The determination of the angular velocities of gears and carriers is carried out using Willis formulas and the graphical-analytical method (for verification), while the torques are determined using free body diagrams. The magnitudes of angular velocities and torques were used to determine the directions of power flows with improved energy balance equations in the reference frame related to the stationary gear body and, additionally, only to verify the energy balance equation in the mobile reference frame related to the carrier ${\mathrm{h}}_{\mathrm{i}}$ ($\mathrm{i}=2,5,8$). The improvement of the methods was based on the use of the original concept of distinguishing active torque from reactive torque, as well as active power from reactive power, which made it very easy to determine the directions of the power flow. The determined paths of the power flow, including the power circulation in the analysed PGS, are presented graphically.

This paper presents a comprehensive comparative analysis of the measurement tools in the Cognex D900 vision system, applied within an industrial manufacturing environment focused on quality control. Initially, issues related to vision systems, including their definition, history, and development path, are discussed. The benefits of using vision systems in such industrial scenarios are presented. The analysis examines the operation of selected functions offered by the vision system, comparing two methods of program preparation for inspection: user-configured functions performing the indicated measurements and image analysis using deep learning. The first method allows for the omission of non-critical defects, providing specific dimension values for further analysis by other systems, and features straightforward function configuration with low hardware requirements, with modification times ranging from 30 to 200 ms depending on image detail placement. Conversely, the ViDi tool offers comprehensive image analysis without the need to specify detail features, enabling the detection of any deviations from a reference pattern. Through a series of tests conducted in a high-precision manufacturing environment, this research highlights the strengths, limitations, and practical implications of using advanced vision systems in automated inspection and quality control processes.

In the present paper, the diagnostics problems of gears and air-compressors are discussed. The diagnostics has been performed by means of wireless system WiViD. This system is a unique design solution, in which several functions are divided and performer by two separate devices. The mentioned device functions are as follows: data handling, processing, their analysis and presentation. In the paper, own measurement procedures were created, checked and presented. The evaluation of technical conditions of some devices was done based upon the registered diagnostic symptoms, which were compared with the allowable limits.