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.

Niniejszy artykuł przedstawia metodyczne podejście do budowy repozytorium dobrych praktyk na przykładzie studium przypadku dla obszaru publicznego zarządzaniu kryzysowego. Wyniki uzyskane w ramach prowadzonego projektu rozwojowego umożliwiły określenie kluczowych wymiarów klasyfikacji dobrych praktyk zgromadzonych w repozytorium, określenie sposobu opisu (metryki) każdej dobrej praktyki zakwalifikowanej do repozytorium z punktu widzenia procesu planowania cywilnego, zarządzania kryzysowego oraz zarządzania ryzykiem, jak również budowania dojrzałości organizacji. Opisane w artykule podejście jest uniwersalne - może być wykorzystane do budowy repozytorium dobrych praktyk dla innych obszarów zarządzania. Koncepcja struktury repozytorium jest przygotowana do zaimplementowania w środowisku cyfrowym.

The study aimed to identify and analyze measures used in manufacturing enterprises to protect workers from COVID-19 infection and maintain business continuity. Measures were identified based on literature studies, recommendations presented in the guidelines of international and national organizations, information from manufacturing companies, and the study authors’ expertise. Measures were classified into five groups. A survey was conducted using a mixed model Computer Assisted Web Interview/Computer Assisted Telephone Interview (CAWI/CATI) on a representative group of 600 manufacturing companies in Poland. Measures were analyzed according to the occurrence or non-occurrence of COVID-19 in the enterprise. It was confirmed that the vast majority of identified measures were being applied, and enterprises implemented other solutions developed in-house. Legal and regulatory measures, individual protective measures, and protective measures for groups of workers were mainly applied at similar levels, both in the occurrence or non-occurrence of COVID-19. The implementation measures of work organization and production organization are mostly higher in enterprises without COVID-19. The proposed approach can be the basis for developing a methodology for studies of crisis events of a similar nature. The results can be used to select and implement a set of measures for an individual enterprise.