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The subject of digitization is currently very widely described. Implementing digitization is a complex task and there are many variants of its implementation. The authors of this article asked themselves what current trends affect the digitization of processes and what factors resulting from the characteristics of production enterprises affect the development of operational processes. The CAWI method was used in the study. In the analysis of the results, the following methods were used: Partial Least Squares Path Modeling (PLS), Mood’s Median Test, or visualization using a box plot. The analysis of the results allowed us to conclude that the development of operational processes of production enterprises is related to digitization trends, but this relationship is not direct. It is necessary to link digitalization trends with software development trends. The conducted research also indicated that there are company characteristics that determine the degree of use (absorption) and the perception of significance for digitalization trends. These characteristics are the type of a company and the age of a company.

The use of educational robots is new in terms of their utilization for designing logistic systems. The current methodology for designing logistic systems is not directly oriented towards the use of educational robots. This indicates the need to develop a methodology is directly oriented toward the use of educational robots in logistic system design. The aim of this article is to highlight the possibilities of creating a new methodology for designing logistic systems applying using educational robots or small physical models in general. This article brings a new perspective on the possibilities of designing logistic systems. We consider educational robots, infinite conveyor belts, and so on, such as small physical models. From these elements, we can assemble a functional logistic system for study. This method is necessary solution for the accredited field of study industrial logistics.

Integrated process planning and scheduling in networked manufacturing systems plays a crucial role nowadays and in the forthcoming context of Industry 4.0 to enable effective and efficient decisions, and to improve the business market, based on collaboration, along with computer-based distributed manufacturing and management functions. In this paper some insights regarding a literature review carried out about this main subjects analysed are presented and discussed. Moreover, a framework for integrated process planning and scheduling in networked manufacturing systems is proposed and briefly described, along with some main underlying issues, which are further discussed. Thus, the main purpose of this research consists on presenting a proposed methodology, based on the study conducted, to enable to further assist either academia or industry to develop new tools, techniques and approaches for integrated process planning in networked manufacturing environments. The findings and contributions of this research can help in the implementation and improvement in distributed manufacturing environments, to be linked with small and medium enterprises, to further expand their potentialities through well suited integrated process planning and scheduling decision making processes.

This study explores enhancing decision-making processes in inventory management and production operations by integrating a developed system. The proposed solution improves the decision-making process, managing the material supply of the product and inventory management in general. Based on the researched issues, the shortcomings of modern enterprise resource planning systems (ERPs) were considered in the context of Warehouse 4.0. Based on the problematic areas of material accounting in manufacturing enterprises, a typical workplace was taken as a basis, which creates a gray area for warehouse systems and does not provide the opportunity of quality-managing the company’s inventory. The main tool for collecting and processing data from the workplace was the neural network. A mobile application was proposed for processing and converting the collected data for the decision-maker on material management. The YOLOv8 convolutional neural network was used to identify materials and production parts. A laboratory experiment was conducted using 3D-printed models of commercially available products at the SmartTechLab laboratory of the Technical University of Košice to evaluate the system’s effectiveness. The data from the network evaluation was obtained with the help of the ONNX format of the network for further use in conjunction with the C++ OpenCV library. The results were normalized and illustrated by diagrams. The designed system works on the principle of client–server communication; it can be easily integrated into the enterprise resource planning system. The proposed system has potential for further development, such as the expansion of the product database, facilitating efficient interaction with production systems in accordance with the circular economy, Warehouse 4.0, and lean manufacturing principles.

Product assembly is often the last step in the manufacturing process. This task is usually performed by an assembly worker who needs to have practical experience and expertise. For complex products, the assembly may require a long time to study assembly plans. This paper presents a custom-designed Pick-to-Light system using Poka Yoke principles to make this activity easier. The created modular system with two-stage verification serves to guide the assembler precisely. It shows him on the display which parts he should use in a strictly defined assembly step. Our proposal aims to shorten assembly time and reduce the number of errors, which was supported by a case study in a small company with 30 employees. After analysing the data, we can declare that the proposed system significantly reduces the time required for assembly from 7 to 35% and reduces the error rate by 35%. The solution is scalable and flexible, as it can be easily adapted to display assembly steps for a different product.

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 publication reflects the current situation concerning the possibilities of using augmented reality (AR) technology in the field of production technologies with the main intention of creating a tool to increase production efficiency. It is a set of individual steps that respond in a targeted manner to the possible need for assisted service intervention on a specific device. The publication chronologically describes the procedure required for the preparation and processing of a CAD model. For this preparatory process, the PTC software package is used which meets the requirements for each of the individual operations. The first step is the routine preparation of CAD models and assemblies. These are prepared based on real models located on the device, and their shape and dimensions correlate with the dimensions of the model on the device. The second phase is the creation and timing of the disassembly sequence. This will provide the model with complete vector data, which is then paired with the CAD models in AR. This phase is one of the most important. It determines the location of the model concerning its relative position on the device, provides information on the relocation of parts of the model after the sequence is started, and essentially serves as a template for the interactive part of the sequence. The last two phases are used to connect CAD models with vector data, determine their position for the position mark, and prepare the user interface displayed on the output device. The result of this procedure is a functional disassembly sequence, used for assisted service intervention of a worker in the spindle drive of the Emco Mill 55 device.

Dynamically occurring changes in the economy and social environment require enterprises to monitor and improve the effectiveness of their production processes in order to remain competitive. The paper describes a research project aimed at improving the flow of materials by changing the organization of production and using Lean Manufacturing tool in a manufacturing company from the food industry, which is characterized by specific requirements and legal standards. Among others, a tool for organizing the workplace and a tool allowing to shorten the time of changeovers, taking into account the specific requirements of the food industry, were used in the research project. The effect of the implemented changes is an increase in production efficiency by 11% and obtaining annual financial benefits in excess of EUR 100,000. It should be noted that the implementation of the project did not require any capital expenditure. All tasks were completed within the working hours of the company’s employees.

The rapid development of manufacturing in recent years has led to a significant expansion of the technological capabilities of modern metal-cutting equipment. Therefore, the modern approach to intensifying production requires an advanced fixture design. Design and manufacture of flexible fixtures capable of machining similar shapes and sizes of complex geometry parts reduce setup time. The article aims to design flexible fixtures for parts such as one-piece connecting rods under incomplete locating conditions. The advantages are the minimum number of parts and tool availability for multi-axis machining connecting rods in one setup. This approach, combined with up-to-date machining centers and industrial robots, can increase the production efficiency of manufacturing non-removable connecting rods. This effectiveness is in a decrease in the number of operations by 5–7 times, fixtures—by 3–4 times, and machine tools—by 3–5 times, depending on the type of a non-removable connecting rod and its design features. The numerical simulation results of the proposed fixture design confirmed the comprehensive technological capabilities and dynamic characteristics. Particularly, a decrease in displacements and oscillation amplitudes up to 7% compared to the full-basing locating chart was provided. It is determined that the system “fixture–workpiece” entirely meets all the strength, accuracy, and rigidity parameters, which allows you to perform machining with intensive cutting modes. The amplitudes of oscillations do not exceed the tolerances on the dimensions of these surfaces, established by requirements for non-removable connecting rods, and all displacements are elastic. During numerical simulation, the workpiece position remained stable at all machining steps.

The paper presents ways to reduce the vibrations of special cantilever boring bars mounted on spindle heads of finishing and boring machines. Special cantilever boring bars are designed for machining holes in non-standard conditions, for example, when boring deep holes with l/d>3 (l–hole length, d-hole diameter) or holes with a discontinuous surface. The results of the experiments and theoretical developments, as well as the schemes of the experimental stands, are presented. The investigated methods for reducing fluctuations are the following: the use of a dynamic damper with intermittent cutting elements; the suppression of the normal vibrations of the cutter to the workpiece surface due to the excitation of vibrations directed tangentially to the workpiece surface and not causing processing errors; increased damping in the cutting zone when changing the design of the boring bar. The tuning parameters of the dynamic damper, the logarithmic decrement of vibrations, as well as the conditions for effective damping of vibrations during the interaction of their two coupled forms are given. The results are shown in the tables and graphs.