Functional Resonance Analysis Method Research Articles

Towards decision-making support for complex socio-technical system safety assessment: A hybrid model combining FRAM and dynamic Bayesian networks

Effectively managing system safety and resilience in critical infrastructures requires addressing emergent risks and critical resonances. This study introduces a quantitative model that merges Monte Carlo Simulation (MCS) of the Functional Resonance Analysis Method (FRAM) and Dynamic Bayesian Network (DBN) to assess technological, organizational, and human performance variability in complex social-technical systems. FRAM identifies system taxonomy and functional variability, while MCS pinpoints critical coupling, supplying prior probabilities for functional resonance. This information feeds into the DBN, facilitating the modeling of causal relationships and probabilistic inferences regarding risk uncertainties and system resonances. The model underwent rigorous testing and validation on a preheater cyclone system within the cement industry. This process involved the utilization of historical field data gathered from six prominent cement industries and input from thirty subject matter experts. The integrated approach deeply analyzes emerging risk indicators, unveiling interactions within organizational, human, and technical subsets, alongside performance variability. Furthermore, the model incorporates system learning parameters, aiding decision-making under uncertainty. These findings advance system safety and resilience management, offering insights for risk assessment and accident prevention across diverse scenarios in complex socio-technical systems.

Why are emergency responses ineffective and inefficient? Lessons learnt from past events

Effective and efficient emergency responses can significantly reduce damage to personnel, properties, and the environment. However, responses to emergencies are not always satisfactory. The Functional Resonance Analysis Method (FRAM) is a powerful tool for modeling and analyzing sociotechnical systems and processes, such as emergency responses. This study aimed to investigate real emergency responses using FRAM. First, a FRAM model of the emergency response process, including 21 functions, was built to explain how it is accomplished. Then, three case studies were investigated to demonstrate the applicability of the FRAM model to emergency responses. Functional variability-based analyses were conducted to identify weak points in each response. The results of this study showed that two functions with significant variability appeared in all three case studies: "developing Incident Action Plan (IAP)" and "assigning roles and responsibilities". The variability of these two functions should be managed; otherwise, it can propagate in the emergency response process, affect downstream functions, and result in negative outcomes. Effective implementation of Incident Command System (ICS) and enhancing the improvisation capacity of the organization both deem to be damping factors for successfully managing variability during emergency responses.

Entangled in complexity: An ethnographic study of organizational adaptability and safe care transitions for patients with complex care needs.

The aim of this study was to visualize vulnerabilities and explore the dynamics of inter-professional collaboration and organizational adaptability in the context of care transitions for patients with complex care needs. An ethnographic design using multiple convergent data collection techniques. Data collection involved document review, participant observations and interviews with healthcare and social care professionals (HSCPs). Narrative analysis was employed to construct two illustrative patient scenarios, which were then examined using the Functional Resonance Analysis Method (FRAM). Thematic analysis was subsequently applied to synthesize the findings. Inconsistencies in timing and precision during care transitions pose risks for patients with complex care needs as they force healthcare systems to prioritize structural constraints over individualized care, especially during unforeseen events outside regular hours. Such systemic inflexibility can compromise patient safety, increase the workload for HSCPs and strain resources. Organizational adaptability is crucial to managing the inherent variability of patient needs. Our proposed 'safe care transition pathway' addresses these issues, providing proactive strategies such as sharing knowledge and increasing patient participation, and strengthening the capacity of professionals to meet dynamic care needs, promoting safer care transitions. To promote patient safety in care transitions, strategies must go beyond inter-professional collaboration, incorporating adaptability and flexible resource planning. The implementation of standardized safe care transition pathways, coupled with the active participation of patients and families, is crucial. These measures aim to create a resilient, person-centred approach that may effectively manage the complexities in care transitions. The recommendations of this study span the spectrum from policy-level changes aimed at strategic resource allocation and fostering inter-professional collaboration to practical measures like effective communication, information technology integration, patient participation and family involvement. Together, the recommendations offer a holistic approach to enhance care transitions and, ultimately, patient outcomes. Findings are reported per the Consolidated Criteria for Reporting Qualitative research (COREQ). No patient or public contribution.

Using a Metadata Approach to Extend the Functional Resonance Analysis Method to Model Quantitatively, Emergent Behaviours in Complex Systems

In an increasingly complex world there is a real, urgent need for methodologies to enable engineers to model complex sociotechnical systems, as these now seem to describe the majority of systems in use today. This is, of course, exacerbated by the increasing involvement and augmentation with “black box” AI contributions. Hollnagel produced a methodology (FRAM) which did allow the analyst insights into these systems’ behaviour, but the model-based system engineering applications demand numbers and a quantitative approach. In the last 10 years, this original approach, developed to model systems as sets of interactive, interdependent “functions” (abstracted from agent or component details), has been further developed to the point where it can take the basic data and structures from the current component-focussed system engineering “models”, and can pull them all together into dynamic models (as opposed to the static, fixed System Theoretic Process Accimaps) from which analysts can discern how they really work in practice, and predict the emergent behaviours characteristic of complex systems. This paper describes how the FRAM methodology has now been extended to provide these extra, essential attributes. It also describes its implementation using an open-source software, freely available for use and verification on the GitHub site.

Resilient performance in building maintenance: A macro-cognition perspective during sudden breakdowns

Building maintenance encompasses multiple tightly inter-connected agents (e.g., technicians, occupants, supervisors, and equipment). Variable working conditions and limited resources may affect the safety and sustainability of the activities. Although recent studies have explored how complex systems can perform resilient behavior in facing the complexity of everyday activities, the factors that effectively contribute to resilient performance are still paired with limited empirical evidence. We studied the performance of the maintenance team during sudden breakdowns of air-conditioning devices in a large university campus, using the Functional Resonance Analysis Method (FRAM). A FRAM diagram containing 30 functions was organized including six macro-cognitive functions (expertise, sensemaking, communication, coordination, collaboration, and adaptation/improvisation), examining their role in anticipating, and responding to emergencies, and eight functional units that are directly impacted by disturbances were analyzed in more detail. Results indicate that macro-cognitive functions can greatly impact the functionality of the maintenance team in pursuit of their goals. Moreover, we noted those macro-cognitive functions here analyzed depend on each other to produce resilient performance.

[Understanding complex processes better-A case study on increasing patient safety and efficiency in a central operating room].

Various professional groups are involved in the daily work of the central operating room with the aim of providing the best possible treatment for each individual using modern medical technology (sociotechnical system) in acost-effective manner. Ensuring perioperative patient safety is of particular importance. At the same time, the efficient use of the central operating room is essential for the economic success of ahospital. Preoperative preparation is acomplex process with many substeps that are often difficult to manage. Historically, the focus has been on retrospective learning from errors and incidents. More recent approaches take asystemic view. Acentral idea is to consider the mostly positive course of treatment and the adjustments to daily work that are currently required by the people involved (Safety-II). By taking greater account of how the many components of the system interact, processes can be better understood and specific measures derived. This strengthens the system's ability to adapt to changes and disturbances, thus ensuring that goals are achieved. The functional resonance analysis method (FRAM) is an internationally recognized method for modelling work as done compared to work as imagined. This paper presents the application of FRAM to preoperative preparation in a major regional hospital. Is FRAM suitable for improving process understanding in preoperative preparation? An interdisciplinary project team identified relevant functions of preoperative preparation through document analysis and walkthroughs. Based on this, more than 30guided interviews were conducted with functionaries. The results were presented graphically and specific information, such as safety-related statements or reasons for the variability of functions, were also presented textually. In the next phase, statements were evaluated and compared with the target model and the job descriptions. The FRAM revealed the process as acomplex network of relationships. During the modelling process, avarying degree of centrality and variability of certain functions became apparent. From the observations, the project team selected those with high relevance for patient safety and for the efficiency of the overall process in order to prioritize starting points for deriving measures to increase resilience. These starting points relate either to single functions, such as surgical site marking or to multiple functions that are variable in their execution, such as delays due to nonsynchronized duty times. The FRAM conducted provides valuable new insights into the functioning of complex sociotechnical systems that go far beyond classical linear methods. The awareness of operational processes gained and the resulting dynamic view of interactions within the system enable specific measures to be derived that promote resilient behavior and reduce critical variability, thus contributing to increased patient safety and efficiency.

Navigating complexity of the medication management system within the home setting-a functional resonance analysis method (FRAM) analysis of people with dementia and their carers' experiences.

There is a strong imperative to support people with dementia to live independently in their homes for as long as possible. A starting point is to understand how they manage medications on a daily basis. To understand how people with dementia and their informal carers manage medications within the home setting to inform the identification of opportunities to improve medication management. A qualitative study using the Functional Resonance Analysis Method (FRAM). Interview data with people with dementia and informal carers were analysed to (i) Identify and describe key functions, (ii) identify and describe variability in performing key functions, and its potential consequences and (iii) map performance variability to Resilient Healthcare capacities. A FRAM model was developed and consisted of 14 interdependent key functions. The interdependent nature of functions, and the different nature and sources of variability in how each key function was performed highlighted the level of complexity of the medication management system within the home setting. The medication system was managed almost entirely by the person with dementia and/or their informal carers. This shows the lack of system-level controls to support the safe functioning of the medication management system in the home setting. Future work will develop a comprehensive FRAM model that includes the perspectives of health and social care professionals and those from the third sectors to underpin the development of a range of system recommendations to strengthen resilience in the medication management system within the home setting.

Risk assessment methods for process safety, process security and resilience in the chemical process industry: A thorough literature review

This paper presents a systematic literature review of risk assessment methods in the chemical process industry (CPI), focusing on process safety, process security, and resilience. We analyzed peer-reviewed articles from 2000 to 2022 using the PRISMA methodology and identified twelve predominant methods. Our findings reveal a shift towards dynamic, systemic-based assessments like the Functional Resonance Analysis Method (FRAM) and System-Theoretic Accident Model and Processes (STAMP). These methods are particularly effective at capturing the complexities of sociotechnical systems in the CPI. However, a significant observation from our review is the limited emphasis on the resilience paradigm within many existing methods when addressing both process safety and process security risks, which is crucial for preventing and recovering from disruptions. Given the evolving challenges in system safety and security threats, there is an urgent need for holistic methods that integrate process safety, process security, and resilience. Our review highlights the opportunity for further research to better prepare the industry for future challenges, ensuring safer, more secure, reliable, and resilient operations.

Polyester Reçine Üretim Tesisinde Fonksiyonel Rezonans Analiz Yöntemi (FRAM) ile Risk Analizi

There are various hazards and risks in the workflow processes in polyester resin production facilities. The most important of these dangers and risks are; It is related to chemical processes, fire and explosion, equipment malfunctions and storage processes of the products obtained. This study aims to analyze the potential hazards and risks that may be encountered in a polyester resin production facility in the Marmara region, from the arrival of the raw material to the facility, to its processing and storage of the resulting products, with the Functional Resonance Analysis Method (FRAM) and to identify the stages that prevent the processes from being optimized. It has been prepared to make suggestions both for improving workflow processes and reducing risks in the process.

The Assessment and Response of Rehabilitation Professionals to Sudden Deterioration in Symptoms: An Analysis of the National Database in Japan.

There are few analyses of the current status of and responses to acute deteriorations encountered by physiotherapists, occupational therapists, and speech-language pathologists (rehabilitation professions [RPs]). The purpose of this study was to analyze the responses of RPs to acute deterioration in patients using the functional resonance analysis method (FRAM) based on the descriptions in "the Medical Accident Database". Subjects were 413 cases with medical incidents reported by RPs to the database from 2012 to 2021. Life-threatening cases with changes in consciousness, circulation, and respiration were selected. Descriptions regarding findings assessed by RPs and support team, and requests for assistance were extracted. We also attempted to construct appropriate respond in RPs by using the FRAM. Thirty-nine cases of acute deterioration were included in the analysis, and descriptions by RPs of consciousness (35 cases), circulation (18 cases), and respiration (36 cases) were identified. Blood pressure and percutaneous oxygen saturation measurement were frequently presented in the assessment by RPs, whereas the support team assessed cardiac arrest and respiratory arrest in high frequency. The FRAM analysis indicated that appropriate and rapid post-response by RPs requires patient information in prior, appropriate assessment and integration/interpretation. We attempted to identify problems analyzing the response by RPs to acute deterioration using the database and construct an appropriate response model. It resulted that RPs need to obtain patient information in advance and integrate/interpret it appropriately based on accurate assessment of conscious, circulation and respiration for rapid response. A model including integration/interpretation for appropriate post-response by RPs was constructed using the FRAM.

Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments

Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments

Reflexive dialogues of multidisciplinary care professionals and clients as part of the development of integrated maternity care: bridging perspectives, building resilience

Background: Limitations of traditional structures and approaches in the health care system to further enhance patient safety, satisfaction and systemic sustainability, are becoming increasingly visible. Amplifying resilience is considered important to defy these issues in the complex adaptive system that health care has become. There is increasing recognition that embedding reflexive learning would contribute to realizing this. However, health care organizations are still reticent, and struggling with whether and how this could be implemented in health care practice. Through participatory action research (PAR), we aimed to develop a method with and for professionals and clients in maternity care, to systematically reflect on daily care practice and explore potential improvements, while balancing their values, interests and perspectives. 
 Methods: To improve quality of care, two groups of multidisciplinary and multiorganizational maternity care professionals and clients (n=30) from two regions in the Netherlands, participated in ‘reflexive learning meetings’. Cases from participants’ own practice were discussed, with a Safety-2 approach and using the functional resonance analysis method (FRAM) to explore variability in everyday performance. 22 meetings took place from 2020-2022, mostly online, supported by an independent chairperson and two researchers. Additionally, 22 participants were interviewed. All data were audio recorded, transcribed and thematically analyzed. Stakeholders (maternity care professionals, clients and managers from the participating regions) were engaged in all stages of the project; from the initial design, through constant monitoring and until the project evaluation and development of an ‘Intervision Toolkit’ to share lessons learned and practical tools with the field.
 Findings: Although critical about working with the FRAM, participants were generally positive about the meetings and Safety-2 approach. Learning from everyday care practice instead of adverse events (common in Safety-1) was considered valuable and motivating. Barriers for partaking predominantly related to organizational and systemic impediments, especially high workload and lacking support from superiors. In the meetings, participants felt psychologically safe and challenged to critically reflect on their own and each other’s care practices. Through this, insight in and understanding of alternative perspectives and approaches grew, as well as awareness of interpersonal and interorganizational similarities. This fostered mutual relationships and job satisfaction, and helped to discover potential for further alignment. Although implementing improvements beyond the individual level proved difficult within the time frame and context of the study, participants became more conscious of their acting and decision-making habits, which in turn stimulated them to experiment with alternatives and share new insights with colleagues and peers. Evaluating the project, participants articulated the wish to continue and embed multidisciplinary and multiorganizational reflexive meetings as standard practice in maternity care. Some initiated actions to contribute to realizing this.
 Conclusions: This study indicates that reflexive dialogues between multidisciplinary and multiorganizational professionals and clients foster alignment, quality, people centeredness and resilience in maternity care. By structurally stimulating, facilitating and embedding such meetings, their transformative potential could be further unleashed and reinforce the development of an integrated and sustainable maternity care system.

An integrated approach to quantitative resilience assessment in process systems

Chemical process systems are becoming more automated and complex, which leads to increased interaction and interdependence between the human and technical elements of process systems. This urges the need for updating the safety assessment method by treating “safety” as an emergent property of a system. Uncertainty comes together with complexity. To enhance system ability of dealing with uncertain disruptions, this paper proposes a quantitative resilience assessment method by modeling the failure propagation (initiated by a disruption) across the functional units of a system. The Functional Resonance Analysis Method (FRAM) is utilized to model the system operation to represent the relationship among its function units and to consider the interactions among human-technical factors. Then, a Cascading Failure Propagation Model (CFPM) is developed to quantify the fault propagation process and reflect the system functionality changes over time for resilience assessment. The proposed method is applied to a propane-feeding control system. The results show that it can help practitioners understand the process of fault propagation and risk increase, identify potential ways to design a more resilient system to respond to uncertain disruptions/attacks, and provide a real-time dynamic resilience profile to support decision-making.

System Safety Assessment of the Warehouse Operation Using Functional Resonance Analysis Method and Resilience Analysis Grid

This study applied the perspective of Safety-II using the Functional Resonance Analysis Method (FRAM) and the Resilience Analysis Grid (RAG) to analyze safety in warehouse operations from a system perspective. FRAM was used to emphasize what caused things to go right, with the findings highlighting higher performance and safety variability occurring in activities that require multiple individual or group efforts. RAG was used to assess the organization’s potential to handle unexpected occurrences, identify the potential resilience of the warehouse in its daily activities, and evaluate the ability to maintain flow and worker safety based on four pillars of resilience. The assessment resulted in a value of 3.50 in the ability to respond, 2.84 in the ability to monitor, 3.88 in the ability to learn, and 3.21 in the ability to anticipate. Combining FRAM and RAG enhances the depth of a new perspective of safety analysis and addresses resilience factors in daily operations.

A FRAM-based Case Study on Leakage Accidents in Cathode Material Manufacturing Process

In this study, the interrelationships among accident prevention functions targeting leakage accidents in cathode material manufacturing process were analyzed using the FRAM (Functional Resonance Analysis Method) method. 17 system functions of accident prevention were derived from the target accidents. Each function was connected and developed into six aspects such as input, output, prerequisites, resources, control, and time. And, the causes of leakage accidents in complex interactions were analyzed in detail. Results showed that the complex interaction and ripple effects of functional variability were analyzed as the cause of the accident unlike the existing root cause analysis (RCA) that deals with simple cause-effect relationships. Specific response plans were derived, including systematic management of operation plans, continuous monitoring of facilities, and strengthening of worker training and information sharing mechanisms. The FRAM method confirmed that it can serve as an effective tool for accident prevention in considered new chemical processes. It is expected to be used as an important tool that can significantly reduce human casualties, property damage, and environmental accidents in the cathode active material manufacturing process.

Analyzing organizational gaps in process accidents with FRAM: The case of the Imperial Sugar refinery explosion (2008)

AbstractThis study presents a reanalysis of the Imperial Sugar refinery accident that occurred in February 2008, in Georgia, USA, using functional resonance analysis method (FRAM) and based on technical‐scientific materials and the official reports. This explosion was fueled by sugar dust in the packaging building of the refinery, causing 14 fatalities and injuring 38 workers. The purpose of this reanalysis is to seek factors and interactions that could not be well analyzed or evidenced using traditional accident investigation techniques, which are primally designed to analyze linear systems. This reanalysis with FRAM allowed us to perceive the influence of organizational elements, such as culture, in the accidental chain of the event, highlighting the need of a broader approach for accidents involving high‐tech process industries. In this sense, FRAM enabled a more comprehensive analysis of the complex functioning of process plants, for both normal operation and in emergency. It was noticed that the greater the complexity of work systems, the greater the interaction and variability between personnel, equipment, and systems, requiring analysis techniques and methodologies capable of recognizing the real complexities that take place in these sociotechnical systems, especially in high‐tech process plants, such as the sugar refinery in this case.

Risk Approach Based on the FRAM Model for Vessel Traffic Management

Abstract This study analyzes the risks in ship traffic services management using the functional resonance analysis method (FRAM), a novel approach that focuses on identifying interactions leading to performance variability rather than errors. The research area is the Turkish Straits vessel traffic service management (VTSM) region, known for frequent risky ship passages. The goal is to ensure safe VTSM, minimize the negative impacts on people, goods, and the environment. The daily routine functions of the VTSM, determined through consultations with vessel traffic operators (VTOs), are explained by following FRAM analysis principles. Qualitative methods, aligned with expert opinions, are used to examine potential performance variabilities and hazard factors. The resulting risk situation for each function is categorized by criticality on a color-coded scale. Solution proposals are provided to manage critical function variability, enhancing the VTSM system's responsiveness and adaptability.

A Resilience Engineering Approach for the Risk Assessment of IT Services

Nowadays, services related to IT technologies have assumed paramount importance in most sectors, creating complex systems involving different stakeholders. Such systems are subject to unpredictable risks that differ from what is usually expected and cannot be properly managed using traditional risk assessment approaches. Consequently, ensuring their reliability represents a critical task for companies, which need to adopt resilience engineering tools to reduce the occurrence of failures and malfunctions. With this goal in mind, the current study proposes a risk assessment procedure for cloud migration processes that integrates the application of the Functional Resonance Analysis Method (FRAM) with tools aimed at defining specific performance requirements for the suppliers of this service. In particular, the Critical-To-Quality (CTQ) method was used to define the quality drivers of the IT platform customers, while technical standards were applied to define requirements for a security management system, including aspects relevant to the supply chain. Such an approach was verified by means of its application to a real-life case study, which concerns the analysis of the risks inherent to the supply chain related to cloud migration. The results achieved can contribute to augmenting knowledge in the field of IT systems’ risk assessment, providing a base for further research.

An integrated discrete-event simulation with functional resonance analysis and work domain analysis methods for industry 4.0 implementation

In the Industry 4.0 era, advanced analytical tools are essential for progressing with digital transformation, especially within complex socio-technical systems. However, the growing complexity of these systems in manufacturing impedes system improvement, and traditional analytical methods focusing solely on the technological aspect often fall short. To overcome this problem, this paper introduces an integrated methodology combining Discrete-Event Simulation, Functional Resonance Analysis Method, and Work Domain Analysis for analysing and enhancing manufacturing systems by considering factors like operator skill levels, demand changes, and production constraints. Implemented in two industrial case studies, this methodology effectively identifies system limitations and aids in structured data analysis, positioning it as a vital decision support system in the digital transformation of Industry 4.0.

Systems-theoretic interdependence analysis in robot-assisted warehouse management

The safe and efficient application of collaborative robots requires an understanding of actual work practices transformation, emerging from the adoption of new technological instruments. Functional systems-thinking is largely absent in literature about collaborative robot applications. In this context, this study proposes a framework that combines two safety analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. Both safety and efficiency are examined by selected case study highlights to gain an in-depth understanding of human operators’ role as the central driver of human–machine (eco)systems in a warehouse distribution system, in which warehouse robot assistance is provided. Whereas the Functional Resonance Analysis Method first maps the work system interactions as a whole, Interdependence Analysis is subsequently applied to investigate individual inter-agent exchanges by the principles of Observability, Predictability, and Directability as a core principle for goal coordination between multiple agents, including warehouse robot agents. The case study examples reveal the combined effects of the working system environment and the robot application but also demonstrate possible operational solutions to deal with socio-technical complexity.