The contribution deals with current situation in modern manufacturing enterprises, which is affected by digital virtualization of different parts of the production process. The overview part of this article points to the fact, that wide informatization of all areas causes substitution of real elements and relationships between them with their digital, often virtual images, in real practice. Key characteristics of the systems implemented using digital twin technology along with essential conditions for intelligent products deployment were identified across many published studies. The goal is to outline an option for the production system realization using digital twin technology as a supplement of standardized concepts for Industry 4.0. The main resulting idea leads to the statement that the current trend of implementation of the new technologies and ways of communication between industrial facilities erases the boundaries between the real environment and the virtual world. The final part of the paper is devoted to implementing the proposed concept using the AVEVA Wonderware software tool.

Global progress in the industrial field, which has led to the definition of the Industry 4.0 concept, also affects other spheres of life. One of them is the education. The subject of the article is to summarize the emerging trends in education in relation to the requirements of Industry 4.0 and present possibilities of their use. One option is using augmented reality as part of a modular learning system. The main idea is to combine the elements of the CPS technology concept with modern IT features, with emphasis on simplicity of solution and hardware ease. The synthesis of these principles can combine in a single image on a conventional device a realistic view at the technological equipment, complemented with interactive virtual model of the equipment, the technical data and real-time process information.

The utilization of a specific priority rule in scheduling operations in flexible job shop systems strongly influences production goals. In a context of production control in real practice, production performance indicators are evaluated always en bloc. This paper addresses the multi-criteria evaluating five selected conflicting production objectives via scalar simulation-based optimization related to applied priority rule. It is connected to the discrete-event simulation model of a flexible job shop system with partially interchangeable workplaces, and it investigates the impact of three selected priority rules—FIFO (First In First Out), EDD (Earliest Due Date), and STR (Slack Time Remaining). In the definition of the multi-criteria objective function, two scalarization methods—Weighted Sum Method and Weighted Product Method—are employed in the optimization model. According to the observations, EDD and STR priority rules outperformed the FIFO rule regardless of the type of applied multi-criteria method for the investigated flexible job shop system. The results of the optimization experiments also indicate that the evaluation via applying multi-criteria optimization is relevant for identifying effective solutions in the design space when the specific priority rule is applied in the scheduling operations.

Communication and possibilities of flexible manufacturing systems control through a variety of communication protocols are described in this article. The main core of the article is to design robotic cells control by using the standard Ethernet (non-RT) while maintaining safety and quality of production, and the system is able to dynamically respond to changes in the production process. The core of the practical part is to design communication via the TCP/IP and socket technology, robot software design and the result of trials performed under real conditions in a heterogeneous environment of the production line with multiple types of robots and conveyor belt.

The article addresses an approximate solution to the multi-objective optimization problem for a black-box function of a manufacturing system. We employ the surrogate of the discrete-event simulation model of a batch production system in an analytical form. Integration of simulation, Design of Experiments methods, and Weighted Sum and Weighted Product multi-objective methods are used in an arrangement of a priori defined preferences to find a solution near the Pareto optimal solution in a criterion space. We compare the results obtained through the analytical approach to the outcomes of simulation-based optimization. The observed results indicate a possibility to apply the suitable analytical model for quickly finding the acceptable approximate solution close to the Pareto optimal front.

Augmented Reality is a progressive tool in the field of education and learning systems. The subject of the article is the introduction of a learning system focused on the teaching of subjects from the field of industrial automation. However, the modularity and versatility of its design mean that the system is universally applicable to the teaching of any technical subject matter. The solution is built on an open source platform, which underlines the low cost of the system. The use of the A-Frame framework in combination with the AR.js project allows for a combination of learning information and real-world images on commonly available mobile devices in augmented reality to be offered. Additionally, the information is supplemented by real-time process information from the process level control elements of selected subsystems of the complex production line AFB Factory by Festo Didactics.