This article outlines an integrated functional safety and cybersecurity evaluation approach within a framework for business continuity management (BCM) in energy companies, including those using Industry 4.0 business and technical solutions. In such companies, information and communication technology (ICT), and industrial automation and control system (IACS) play important roles. Using advanced technologies in modern manufacturing systems and process plants can, however, create management impediments due to the openness of these technologies to external systems and networks via various communication channels. This makes company assets and resources potentially vulnerable to risks, e.g., due to cyber-attacks. In the BCM-oriented approach proposed here, both preventive and recovery activities are considered in light of engineering best practices and selected international standards, reports, and domain publications.

The aim of this study was to analyze the effectiveness of implementing an automated appointment confirmation system in a mental health clinic and to assess its impact on patient attendance, which may indirectly support the patient recovery process. The study was conducted at a mental health outpatient clinic in Gdańsk, Poland, and focused on medical appointments across three affiliated outpatient units. Data from 2019 and 2023 were compared, focusing particularly on the rate of missed appointments (relationship between number of visits that did not take place and total number of visits that were scheduled in the software), form return rates (the relationship between the number of forms returned by patients and the total number sent), and patient opinions regarding the usability of the new system. The results showed a significant reduction in no-show rates—from 18.55% to 7.01%—confirming the high effectiveness of the automated system. The form return rate reached 55.41%, with the highest engagement observed among individuals aged 35–44. Patient evaluation of the system was highly positive—over 93% found it intuitive and meeting their expectations. A proprietary software solution developed in Python, alongside databases and Microsoft Office Access/Excel tools, was used for data collection and analysis. The study demonstrated that a comprehensive approach, combining automated reminders with the ability for quick patient response and telephone support, is an effective tool for improving the accessibility and quality of healthcare services. The analysis also considered limitations related to digital barriers and identified directions for further research, including studies on how patient abstention from appointments affects their recovery process.

This article addresses current problems of risk analysis and probabilistic modelling for functional safety management in the life cycle of safety-related systems. Two main stages in the lifecycle of these systems are distinguished, namely the design and operation. The risk analysis and probabilistic modelling differ in these stages in view of available knowledge and data. Due to the complexity and uncertainty involved, both qualitative and quantitative information can be useful in risk analysis and probabilistic modelling. Some methodological aspects of the functional safety assessment are outlined that include modelling of dependent failures or cybersecurity and verifying the safety integrity level (SIL) under uncertainty. It is illustrated how the assumptions in the process of risk analysis and probabilistic modelling influence results obtained and, therefore, potentially the decisions taken in functional safety management. Programmable control and safety systems play an important role in mitigating and controlling risks in the operation of hazardous installations. This paper presents ways to deal with safety hazards involving such systems to be considered in risk analysis and integrated functional safety and cybersecurity management.

In the process of designing safety systems, an integrated approach in safety and cybersecurity analysis is necessary. The paper describes a new technique of increasing resilience through integrated analysis of functional safety and cybersecurity. It is a modeling methodology based on the combination of the multifactor method utilizing modified risk graphs, used previously for Safety Integrity Level (SIL) assessment, and the Non-Functional Requirements (NFR) approach. The NFR approach, based on the analysis of graphical representation of conceptual and physical components of the system, contributes a technique to include cybersecurity through the Softgoal Interdependency Graph. The assessment methodology is outlined in detail and applied to a case study involving an industrial control system. The analysis turns out to be effective in both aspects: confirming the findings of the multifactor approach based on modified risk graphs and complementing the traditional analysis to increase resilience in discovering and mitigating security vulnerabilities for SIL assessment by the use of NFR.