Abstract Prescriptive maintenance extends predictive maintenance by not only forecasting potential failures, but also recommending concrete maintenance actions, explicitly accounting for operational, organizational, and resource-related constraints. Existing approaches in this area are often fragmented, as they typically focus either on technical diagnostics or on isolated optimization criteria, without integrating production schedules, resource availability, and organizational decision constraints into a unified decision- making framework. This creates a research gap in the integration of diagnostic and organizational data, thereby limiting real-time decision-making. The aim of this study was to develop and validate a hybrid prescriptive maintenance algorithm, combining fuzzy logic, neural network classification, and Analytic Hierarchy Process (AHP)-based scenario evaluation, aligned with the principles of Industry 4.0. The algorithm was implemented in MATLAB. A central design feature was the integration of sensor-based measurement data with organizational inputs to dynamically generate decision scenarios, accounting for time, cost, and resource constraints. This integration enabled the algorithm to consistently generate recommendations that respected budgetary and temporal constraints, demonstrating its effectiveness in translating combined technical and organizational data into actionable maintenance decisions. The algorithm was validated using real-world production data, achieving decision accuracy in the range of 94–99%, defined as consistency with expert-validated reference decisions, with a relative prediction deviation below 0.05%. It was further observed that when organizational and contextual data were not considered (such as production schedules, resource availability, and personnel qualifications), over 85% of the recommended maintenance scenarios deviated from the reference decisions determined based on realized production outcomes, with deviation assessed in terms of completion time and cost. The findings demonstrate that the developed prescriptive maintenance algorithm significantly improves decision accuracy, optimizes resource utilization, and reduces both downtime and operational costs, highlighting its practical impact and value for industrial maintenance management.

Abstract The roller shutters are an important factor for improving the energy efficiency of buildings, since their application could contribute to direct economic and environmental benefits. Their proper use allows for a significant reduction of heat loss in winter and excessive heat accumulation in summer, which is associated with a reduction in costs related to heating and air conditioning. The ability to adjust the degree of shading, allows the external shutters to control the sunlight, as well as the heat inside the room, which is especially important on hot summer days. As a result of shading regulation, rooms do not overheat, which reduces the need for air conditioning and makes everyday life more comfortable. In this article are presented results of an experiment conducted on the two rooms in a residential building in the city of Kragujevac, Central Serbia. The two rooms are placed on the East building’s façade; the first being the so-called test room, which had the roller shutters installed on a window and lowered during the test period, while the second room – the reference one – had no shutters lowered. The objective of the experiment was to investigate the influence of the lowered roller shutters on the room’s interior temperature, and consequently the energy consumption for the room’s heating and cooling. It was established that the lowered blinds significantly contributed to the comfort of staying in the room, as well as to savings of the energy consumed for the room’s heating in the winter and cooling in the summer.

Abstract This study applied the DMAIC (Define, Measure, Analyze, Improve, Control) methodology to improve the operational efficiency of a facility’s bottle cleaning process. The Define Phase identified critical issues, including a high rework rate (15%), inconsistent cleaning quality (84% efficiency), and excessive water and detergent consumption. The Measure Phase established baseline data to quantify these inefficiencies. Root causes were identified in the Analyze Phase using a Fishbone Diagram and Failure Mode and Effects Analysis (FMEA), highlighting manual detergent dosing, unstable wash temperatures, lack of standard operating procedures (SOPs), and inconsistent employee performance as major contributors. During the Improve Phase, remedies that were specific to the problem were put into place. These included automating the delivery of detergent and controlling the temperature, adding real-time monitoring, updating standard operating procedures (SOPs), and giving employees more training. Because of this, the cleaning efficiency went up to 92%, the rework rate went down to 7.5%, and the inspection pass rate went up to 92%. Resource usage decreased significantly – detergent by 23% and water by 20% – resulting in annual cost savings of $23,404.24. These gains were sustained through the Control Phase via continuous monitoring, regular audits, and periodic staff retraining. The project shows that DMAIC may help improve operations and lower costs in a way that lasts. It gives other plants a model to follow if they want to improve their manufacturing processes while making them better for the environment and quality. Combining automation, data collection, analysis, and a standardized workflow within a framework for improvement led to rapid gains and long-term process control.

Abstract An Information Security Management System (ISMS) compliant with ISO/IEC 27001 requires the development and implementation of an effective system to guarantee the protection of information from threats. The aim of the study was to propose a set of indicators to measure the effectiveness of SZBI safeguards in manufacturing companies. A model for analysing the effectiveness of the SMS was built, which requires significant involvement of the company’s management. Systemic information security management produces the best results, as it involves treating as a whole all processes taking place in the organisation and is consistent with them. A way to measure the degree of information security was defined using indicator analysis and the application of key performance indicators (KPIs). The metrics addressed key areas such as malware protection, quality of passwords and authentication, updating systems and applications, data handling and training. The implementation of a set of indicators makes it possible to diagnose the security system currently in place and identify critical areas for improvement. The model and set of indicators presented in the study can be a helpful tool in maintaining an effective SMS and safeguarding the interests of manufacturing enterprises and their stakeholders.

Abstract The global demand for ballistic protection systems within civilian armored vehicles (CAVs), particularly in high-security environments, necessitates focused research. Given the paucity of literature addressing the ballistic enhancements design of non-military passenger vehicles, this work concerns the analysis of quality assurance during the armoring process of a standard civilian passenger vehicle while maintaining its original functionality and consumer guarantees. To achieve these metrics, the article presents the Design for Assembly and Armoring (DfA2) methodology in a case study, examining the protection of a front door system of a worldwide compact sport utility vehicle (SUV). This systematic framework optimizes lightweight ballistic systems for CAVs through empirical evaluations and engineering principles. Integrating manufacturing acumen with Design for Excellence (DfX) principles, quality assurance protocols, automotive performance criteria, and ballistic defense requirements, DfA2 addresses the development and integration of armoring solutions with product and process quality in CAVs. Through field research, this study demonstrates the efficacy of the proposed method in refining armoring operations, minimizing armor material mass, and reducing production and design expenditures. Consequently, the findings of this case study with the adoption of DfA2 suggest that the method can be replicated or adapted for diverse vehicle categories, encompassing hatchbacks, notchbacks, SUVs, and commercial vehicles. This research sought to standardize vehicle armoring production, ensuring rigorous quality control while preserving original vehicle functionalities and consumer warranties.

Abstract The article explores the impact of the Russo-Ukrainian war on sustainable consumption and production systems, with a focus on adaptive strategies of industrial enterprises and consumer behaviour. The study analyses how wartime conditions have caused significant changes in resource management, supply chain reconfiguration, and industrial efficiency. The research highlights a shift in consumption patterns towards essential goods, a reduction in energy consumption, and a prioritization of resource conservation. The war has led to increased industrial relocation, transformation of production processes, and a reassessment of sustainable development principles, including the traditional 3R model of ‘Reuse-Reduce-Recycle,’ supplemented by ‘Rethink.’ The findings of the study contribute to a better understanding of sustainable production and consumption strategies in crisis conditions, emphasizing innovative solutions for maintaining industrial operations and achieving sustainable development goals in extreme environments.

Abstract Although the importance of Performance Measurement Systems (PMS) is recognized by organizations in general, it is found that many of these systems are ineffective and end up being discredited. The research question inherent to this work is: how to develop a PMS capable of mitigating the main barriers to the effectiveness of this kind of system? Subsequently, the main objective of this paper is to present a new PMS, called PMS_UM, together with the respective implementation methodology, capable of reducing the impact of the most common barriers to effectiveness, something that the current PMS do not achieve. The research was conducted in the period 2021-2024, and, in terms of methodology, this paper relies on the designated Grounded Theory as it systematically brings together the knowledge needed to develop a robust and effective PMS model and implementation methodology from a set of four studies previously carried out and published by the authors. The methodology begins with identifying barriers to PMS effectiveness through scientific articles, interviews and questionnaires. It then focuses on recognizing existing PMS (and their characteristics) that can mitigate some of these barriers and developing solutions (and necessary PMS characteristics) for unaddressed barriers. All characteristics are classified into groups and their relationships are mapped to develop an effective PMS model. The process integrates theoretical research with practical organizational insights. The main results of this work are (i) the PMS_UM model, which encompasses the critical characteristics needed to be an effective PMS, along with (ii) the corresponding practical methodology for development, implementation and maintenance. Both the model and the methodology are evaluated based on their ability to mitigate or eliminate the most common barriers to PMS effectiveness, thus demonstrating the better performance of PMS_UM compared to existing PMS. As for practical implications, this work provides managers with the means to, step by step, obtain a robust and effective PMS that truly reflects the state of the company and is therefore an essential tool not only for day-today management but also to support any improvement intervention. The PMS_UM model and methodology have not yet been tested in real-world scenarios, which is, at the moment, the main limitation of this work.

Abstract Lean methodologies have been implemented in various sectors, helping to improve the overall efficiency and performance of organisations. The aim of this research is to investigate the relationship between Lean and occupational safety and its impact on people’s behaviour. To this end, a survey was developed and a statistical study carried out. The survey was sent to 4381 companies, from which 289 responses were received from 12 different countries. The Cronbach’s alpha value obtained was greater than 0.86, which indicates that the internal reliability/consistency of the results is very good. Through the statistical study it was possible to conclude that the approaches with the greatest contribution to cultural change in terms of occupational safety are 5S, Standard Work and TPM. It was also concluded that the implementation of Lean practices has a positive impact on people’s behaviour, and that these results differ depending on whether the company is located in Portugal or not. Furthermore, Lean proved to have a very positive impact on performance indicators, especially in companies located in Portugal, regardless of the sector of activity. The results also show that the contribution of Lean management to occupational safety system is very important in different sectors and is influenced by the sector of activity and by the company’s location, and that the impact of the occupational safety system on people’s behaviour was considered very important, with little influence from the company’s location and no influence from the sector of activity. This comprehensive research provides a body of knowledge that is expected to provide positive insights for Lean practitioners, managers and academics.

Abstract The article analyses studies on the impact of the COVID-19 pandemic on outpatient services in a large hospital, aiming to provide insights for resource management amidst disruptive events. The objectives include identifying challenges and proposing solutions to optimize service delivery and address spatial constraints using discrete-event simulation. Utilizing a case study approach, the research employs simulation as a key methodology to analyse outpatient service scenarios. Scenarios are generated by combining different probabilities of patient return to check-in with various team parameterizations. The researchers analysed historical data and key performance indicators from the simulation. The study focuses on a collaborative approach with the hospital team to ensure the relevance and applicability of proposed solutions. The research identifies bottlenecks induced by social distancing measures, particularly in patient reception and check-in areas. Uneven service distribution throughout the day leads to a misallocation of resources and reduction of available physical space. Telemedicine emerges as a significant response, effectively addressing both service optimization and physicians’ workload despite spatial constraints. Additionally, the study underscores the role of simulation in crisis decision-making for hospital operations management. Practical applications emanating from the study emphasize the need for healthcare institutions to adopt adaptable strategies and leverage simulation tools for effective resource management during disruptive events. Hospital administrators can draw insights to inform resource reallocation and workflow optimization, with a focus on negotiating flexible scheduling and exploring telemedicine to enhance service delivery.

Abstract The study focuses on the design and modernization of a feed mixer and demonstrates the impact of what might seem like a non-primary machine in the technological line for producing vitamin-enriched salt lick blocks (SLB) on the quality of the final product, the salt block. Furthermore, it examines the effect of SLBs themselves on animal growth and productivity, including increased milk yields and weight gain. Original recipes and ingredients of the feed salt mixture with their granulometric composition, moisture content, and mass fraction in the composition of the vitamin-enriched salt premix lick block are provided. The design of the mixing shaft is shown, and the operation of the modernized mixer is described. Experimental equipment from the technological line for the production of premix lick blocks is presented. The results of statistical regression analysis are given, adequately describing the working process of the mixer and allowing the calculation of the specific productivity of the new mixer, energy consumption, and mixing homogeneity within the selected intervals of variation of input factors. The component composition ratios of the SBL were found, which allowed achieving maximum specific productivity and homogeneity, as well as minimum energy consumption in a wide range of input parameters of the mixing process in the new mixer. The effect of the final product, vitamin-enriched salt premix lick blocks, on the growth and productivity of animals was studied.