The significance of virtual commissioning for automation control systems is heightened by their increasing complexity and, frequently, their distributed nature. The authors propose a cloud-based testing framework that facilitates remote execution of tests over the Internet. This allows for collaboration among a variety of stakeholders while optimizing the use of computational resources. This framework is based on a scalable and fault-tolerant architecture, which maintains system responsiveness and efficiency even under concurrent usage by multiple users. The integration of this testing framework with the CloViC cloud virtual commissioning platform further increases its capabilities, providing enhancements to existing project administration, performance monitoring of virtual PLCs, and collaborative analysis across teams and projects, with Kubernetes orchestration optimizing system performance. To validate the proposed methodology, a group of students used the automated testing framework as part of their coursework.

In this paper, we propose a cloud-based virtual commissioning Web platform for IEC 61499 compliant distributed automation systems that support Create-Read-Update-Delete operations for SoftPLC containers from various versions and provide a remote engineering workstation with an embedded web Integrated Development Environment (IDE), Human Machine Interface (HMI), and 3D simulation models. A water tank use case demonstrates the platform's flexibility, enabling control software testing entirely via a Web browser without local installations.

With Industry 5.0, prioritizing worker well-being, the integration of human-related data into production processes poses challenges related to data privacy and compliance with regulations such as GDPR. This paper presents a comprehensive approach to anonymizing sensitive data collected from wearable devices. We propose a methodology that combines real-time processing and complex anonymization algorithms, ensuring end-to-end protection. We employ techniques such as normalization, hashing, and feature dropping. Our findings contribute to advancing privacy-preserving techniques in Industry 5.0 and underscore the importance of safeguarding user privacy in the era of advanced manufacturing.

This paper presents a methodology for increasing human-centric production systems flexibility using human factors-enabled digital twins. The paper includes an analysis of the relevant projects that incorporate human-related data collection and processing. The proposed system is capable of collecting human factors-related data from various sources and then use a decision-making algorithm to schedule the tasks according to assessed human operator conditions in real-time. The formed Digital Twin is able to depict the condition of the labourer and production system status in real-time using Visual Components simulation environment. Shown results prove that existing production systems are capable of adapting to the changing condition of the worker flexibly, optimising workflow, distributing tasks with AGVs and cobots, and applying changes in workplace ergonomics to achieve better safety and performance of the worker.

Voice interaction is helping to increase efficiency in many areas of human activity. However, most studies either research its general aspects or domestic applications. On the contrary, there is almost no research on using this technology in production field, although, the idea of retrieving data this way can be a successful solution for large production areas, where it is difficult to find the right display. The paper aims to develop the method of voice assistant's implementation as a part of Cyber-Physical Production System (CPPS) for production processes. The study includes creating a prototype of the voice assistant module based on Alice cloud voice service API from Yandex and Raspberry Pi 3 microcomputer. Main aspects of using voice assistants for accessing production data from a CPPS were described. A possible approach to the introduction of this technology is shown. And a working prototype has been successfully designed. The research shows the possibility of using voice control in production conditions and its potential effectiveness in data access automation.