The purpose of the paper is to present the results of the study of solutions implemented in Polish manufacturing companies to ensure their business continuity under COVID-19 pandemic conditions. A questionnaire survey was conducted using the mixed-model CAWI/CATI (Computer Assisted Web Interview/Computer Assisted Telephone Interview) on a representative group of 600 manufacturing companies in Poland. The research was conducted in March 2021, more than a year after the first lockdown. The study included cases of companies in most industries and companies of different sizes. The subject of the survey was to identify legal, technical, and organisational protection measures implemented in manufacturing enterprises in response to the COVID-19 pandemic in manufacturing companies in Poland.

The process of technology management contains various stages, such as the identification, selection, acquisition, implementation, and maintenance of technologies. In the case of power generation companies, a key aspect of the selection stage is the choice of generation technologies for newly commissioned units. The investment decision depends on many factors, primarily economic, environmental, social, technological, and legal, and represents a complex multi-criteria problem. Currently, the decision is further complicated by the often unpredictable tightening of environmental standards, forcing the closure of conventional sources, on which many countries have so far based their energy security. The paper analyzes the problem of choosing one of the so-called clean coal technologies to be implemented in conditions of transformation of the power sector. In this paper, five selected clean coal technologies are characterized, and the SMART method is adopted to technology selection. The following technologies were considered: supercritical coal-fired power plant (with and without CCS), IGCC power plant (with and without CCS), and IGCC power plant with CCS and integrated hydrogen production. Nine practical criteria (in three main groups: environmental, technological, economic) for comparing technologies are defined, computational experiments performed, and conclusions from the research presented. The work was based on the literature study of multi-criteria decision support and an analysis of power sector needs based on the example of the Polish power sector. The conducted research, apart from the technology recommendation, led to the conclusion that the chosen method may be applied to decision-making in the field of power generation technology management. The study also indicated the potential direction of the development of a power generation structure in a situation where a component of ensuring energy security is the use of available coal fuels.

This paper addresses electricity consumption management in manufacturing enterprises. The research aims to provide manufacturing enterprises with an effective tool to control electricity costs. Recently, some factors have been observed to affect the rapid changes in the operating conditions of enterprises. These include the transformation of the power sector toward renewable energy, the disruption of supply chains resulting from a coronavirus pandemic, political crises, and process automation. A method for the analysis and management of electricity consumption in enterprises based on simulation modeling is proposed. The simulation model contains predefined objects representing physical system elements and the data processing algorithm. The production order execution time, energy consumption, employee overtime, and machine load are included in the model. The results show that it is possible to determine the level of power available for the process completion and its influence on the production volume and realization time. In the studied case, when the available power was reduced by half, there was an increase in order execution time of nearly 25 percent and an increase in energy consumption of nearly 15 percent. The method can be used in the operational activities of enterprises as well as extended to different types of production processes.

This paper presents a method for assortment–quantity production scheduling in a printing company. The company uses specialized machinery to make prints on clothing. The method is based on a study of the company’s practical operations and the production technologies used. It involves the construction of simulation and optimization models of the process. The simulation models reflect the technical aspects of the production process and the business requirements. Optimization models provide solutions that balance product sales revenue with appropriate production schedules. On this basis, managers can make resource-balanced decisions on the implementation of selected production plans, taking into account the current economic conditions of the company. The experiments used the FlexSim simulation program (by FlexSim Software Products, Inc., Orem, UT 84097 USA; v. 20.1.3.1) and the OptQuest optimization package (embedded in FlexSim), resulting in a cost-effective solution in a short time. The proposed method, thanks to the optimization of the production program, provides savings in the use of materials for production, as well as water and energy savings in the production process. Thanks to the possibility of analyzing the process without interfering with it, provided by simulation modelling, the method practically eliminates the costs and time needed to prepare the execution of new production orders. This contributes to the sustainable development of the company and provides an opportunity to assess the impact of potential business decisions in the company prior to their implementation. The method has been directly applied in a company to improve its performance. The method is scalable and can be applied to problems of varying complexity and production systems of different types and sizes. This is especially true for small- and medium-sized companies that use discrete manufacturing in the textile, metal, and furniture industries.

The paper aims to show the possibilities of using modern information technologies in production management. Successive stages of production process preparation...

Purpose: The objective of the paper is twofold: firstly, to analyze the applications of Digital Twin (DT) technology in ensuring cybersecurity in manufacturing processes; and secondly, to identify key thematic areas, research gaps, and potential practical applications. Design/methodology/approach: The research was conducted based on a systematic literature review, using bibliometric analysis and advanced data analysis tools such as VOSviewer and Latent Dirichlet Allocation (LDA). Findings: The literature analysis revealed that current studies focus on the analysis of DT use in risk management and security testing without interference in real manufacturing systems. DT facilitates the emulation of a variety of threat scenarios, the evaluation of the efficacy of implemented security measures, and the optimization of preventive strategies. However, the analysis also identified significant research gaps, including the lack of unified implementation methodologies and insufficient exploration of the impacts of DT deployment in cybersecurity at operational and strategic levels. Practical implications: The implementation of DT has the potential to enhance cybersecurity risk management in manufacturing enterprises by facilitating earlier threat detection, minimizing potential losses, and expediting incident response times. DT provides enterprises with tools for continuous monitoring of manufacturing processes, enabling proactive threat management and increasing system resilience. Originality/value: The study proposes an interdisciplinary approach, with a view to identifying a research niche related to the integration of DT with other information technologies. Furthermore, it outlines directions for developing methodologies and standards for DT implementation in manufacturing processes, with a view to ensuring their cybersecurity.