Functional Resonance Analysis Method Research Articles

Extended FRAM model based on cellular automaton to clarify complexity of socio-technical systems and improve their safety

The safety of socio-technical systems is intractable by traditional approaches, such as a simple cause-effect analysis. It would be no longer effective only to eliminate potential hazards or to explain why things go wrong (i.e., the limitation of the approach called Safety-I). The safety instead could be improved by validating why everyday operations go right and by verifying their resilience, based on an alternative idea of Safety-II. The objective of this research is to develop a tool enabling us to validate and verifying safeties based on the functional resonance analysis method (FRAM). FRAM would be an effective way to analyze the safety of complex socio-technical systems. However, FRAM only provides a conceptual methodology, and further extensions and implementations are needed. This work first presents an extended FRAM model based on a classical idea of cellular automaton, and the result of applying our model to a steel production management problem is provided. Steel production line reveals a quite complicated process consisting of many linked workstations where a production flow might be varied frequently. Wherein flexible delivery decisions are required, including changing the supply chains themselves. There exists empirical know-how to tackle those, but these remain as tacit knowledge, and there has been no way to validate and verify their effectiveness under specific conditions. The results of applying our extended FRAM model to this example provide several insights concerning the characteristics of experienced workers’ operations to handle and manage the process’s complexities, such as harnessing, phase transformation, and identifying critical points attaining resilient operations in terms of the entropy of the process status. We also discuss how these findings contribute to the safety management of the other socio-technical systems based on the findings of the analysis.

Resilience development: learnings for organisations from technical diving

PurposeThe purpose of this paper is to follow the general question, how technical rebreather divers ensure their survival during performing of highly demanding dives – and what organisations could learn from these practices. As one form of complex adaptive system, technical divers perform different routines before and during the dive. These practices are formally trained and also informally mediated and developed. After investigating theoretical concepts like high reliability organising, Safety-I and -II as well as organisational resilience management, the authors scope on the existing risk and resilience practices in technical rebreather diving. Finally, the insights of the empirical research are used to make the transfer to the field of management studies – and ask relevant questions regarding their applied resilience intelligence.Design/methodology/approachThe empirical research is analysed by applying Hollnagel’s Functional Resonance Analysis Method (FRAM) which leads to the reconstruction of an extended resilience management model for technical rebreather diving. The model development bases on a field study which comprised 300 hours of observations.FindingsThe findings are depicted in an FRAM model that exactly shows how technical divers perform high reliability operations and thus manages and increase the resilience of their socio-technical system.Research limitations/implicationsResearch results show the depicted model and the potential learnings for organisations and organisational resilience. However, the research remains inductive and is qualitative. Deductive and quantitative research would enrich and complete the picture.Practical implicationsThe research is informative and offers an interdisciplinary but comprehensive bridge between the specific high reliability organisations/resilience practice of technical divers and the potential learnings for organisations. Companies can take the identified categories and mechanisms to match them to their own resilience activities.Social implicationsIncreasing organisational resilience means to increase societal resilience and thus sustainability. The research aims to support this interdisciplinary learning process.Originality/valueThe originality lies in the research object itself (technical diving practices), that never has been researched with an FRAM before. It is an interesting, comprehensive and interdisciplinary show case that is used to derive practical considerations for companies to strengthen their organisational resilience.

Unveil key functions in socio-technical systems: mapping FRAM into a multilayer network

Network theory has been widely used to describe many complex systems belonging to several fields from physics to sociology. Particularly interesting are multilayer networks which concurrently account for several types of relationships, without necessarily aggregating them. The functional resonance analysis method (FRAM) is an agnostic method (i.e., not making modeling assumptions) allowing semantically rich descriptions of the relationships among functions constituting a socio-technical system. This richness may soon become overwhelming in case of not trivial FRAM models. A multilayer network represents a promising choice for combining the long-proven experience in network theory with the FRAM’s agnosticism. On these observations, this article shows how a FRAM model can be reinterpreted as a five-layer multilayer-directed network without any loss of information, even reducing the cognitive workload required for the analysts. This paper defines a methodology able to prioritize potentially critical functions through dedicated network centrality descriptors, and to generate instantiations for comparison and benchmarking of scenario-based envisioned solutions. A walk-through application in industrial operations management confirms the feasibility and validity of the proposed methodology.

Information Technology Systems at the sharp end of medication therapy management

This study explored how to inform the design of information systems for medication therapy management, in the context of the southwestern Ontario health system. The data collection comprised document analysis, interviews, and process mapping, and the analysis of previous interview records. The Functional Resonance Analysis Method (FRAM) was used for data analysis to identify the effects of functional variability in system outcomes, and to propose ways to redesign future systems. The results from the FRAM showed that shortcomings in the information systems require users to adapt in many ways. While these adjustments are essential to delivering care in everyday practice, they may lose their effectiveness in the face of specific situations, creating brittleness and risk of adverse outcomes as users are led to make challenging decisions.

A taxonomy of interactions in socio-technical systems: A functional perspective

Although the modelling of interactions has long been at the core of socio-technical systems theory, and is a key for understanding resilience, there is a lack of a holistic taxonomy of interactions. This study introduces a taxonomy of interactions to be used in association with the Functional Resonance Analysis Method (FRAM). The taxonomy has nine criteria: nature of agents, output nature, levelling, waiting time, distance, degree of coupling, visibility, safety and/or security hazards, and parallel replications. For each criterion, two descriptors are proposed: what the interaction looks like; and - when applicable - the variability level of the interaction. The use of the taxonomy is presented for three systems with clearly distinct complexity characteristics: cash withdrawal from an ATM, teaching a university course, and manufacturing operations. These case studies indicate the usefulness of the taxonomy for the identification of leverage points in work system design. They also show the value of modelling the variability of the interactions in FRAM models, in addition to the traditional modelling of the variability of the outputs of functions. Implications of the taxonomy for resilience engineering are discussed.

Understanding and improving safety in artisanal fishing: A safety-II approach in raft fishing

Artisanal fishing with rafts is responsible for most of the Brazilian Northeastern region fishing production. Fishing is done in open sea, with very small boats in the unpredictable and often hostile maritime environment. Safety is achieved through the fishermen’s expertise to adjust their performance to cope with the demands and disturbances. Under this environment, safety should be improved by constraining the way people do things, based on traditional safety management principles or Safety I. This research describes a Safety II approach to improve raft fishing safety in a typical Brazilian beach community. Safety II main focus is on fishermen activities and strategies to construct safety during their fishing expeditions. The methods, following the action research iterative procedure, are workplace empirical studies to uncover knowledge, expertise, and artifacts that inform fishermen sensemaking and the Functional Resonance Analysis Method FRAM to model the fishing capture expeditions. Results indicated that the fishermen’s safety related trade-offs during fishing expeditions depends on their sensemaking, and to improve safety there is a need of a broader, systemic and continuous approach, involving not only objective measures and devices to inform and to support sensemaking for safer decisions, but also ways improve survival conditions of fishermen.

Formal or informal human collaboration approach to maritime safety using FRAM

It has been argued that human and organizational factors are critical for accident analysis and safety management. The maritime domain represents a safety-critical system that has complex and temporary human collaborations. The level of collaboration includes not only human collaboration within a single ship, but also between ship-to-ship or ship-to-shore. From the safety-II perspective, these collaborations play a significant role in managing safety. Thus, this study suggests a framework to consider informal and temporary human collaborations using a functional resonance analysis method (FRAM) under the safety-II perspective. The framework is based on FRAM analysis and contributes by analyzing the level of human collaboration through establishing classifications of human collaborative relationships including the specified or unspecified relationships. Further, it supports organizing findings from the analysis and the derivation of strategy using templates and rules. The analyzed findings and derived strategy ultimately aim to help human’s decision-making to adjust variable and uncertain situations by enhancing human collaboration. In particular, this framework is applied to maritime accidents analysis and safety strategy derivation. The authors believe that FRAM has the potential to be employed to other safety-critical systems and to be combined with safety analysis and management methodologies related to human collaboration.

Gatekeeper family doctors operating a decentralized referral prioritization system: Uncovering improvements in system resilience through a grounded-based approach

The referral prioritization system from primary care to specialized ambulatory care in Rio de Janeiro, Brazil, was centralized until 2012. From 2012 onwards major reforms in course in the city’s public health care sector restructured referral prioritization to operate from primary care, elevating primary care coverage from 7% to 70% of the population. This paper aims at describing how this organizational change reshaped the system in a large city, and how strategies used by gatekeeper physicians contribute to system resilience. The criteria used to assess resilience improvements are the Hollnagel’s resilience cornerstones – Responding, Monitoring, Anticipation and Learning. The method used to disclose and describe the impacts of this organizational change to everyday work practices was semi-structured interviews with gatekeeper family physicians and the mapping of these interviews according to concept mapping guidelines. Thus the work-as-done was captured in concepts and its aspects were classified in mutually-exclusive categories. For data analysis we used the Functional Resonance Analysis Method – FRAM to depict the relations among the resilience cornerstones. The findings reveal that system decentralization paved the way for the emergence of situated strategies to cope with shortcomings at the sharp end of referral prioritization, allowing gatekeepers and primary care teams to employ and couple various adjustment maneuvers, improving overall resilience. The qualitative approach has led us to see gaps and identify support processes that are still peripheral to the formal planned assignments, pointing out innovation paths and potential future adjustments to public healthcare policies.

Understanding variability in discharge planning processes for the older person

Discharge planning for the older person is complex and complicated with multiple task interactions, and multiple opportunities for the process to go right and to go wrong. The purpose of the research was to understand the variability in everyday performance during discharge processes for the older person, to identify the parts of the process that may be susceptible to resonance and other potential problems areas. The study employed mixed method data collection comprising document review, focus groups and semi-structured interviews. This research was set in a Sub-Acute Geriatric Evaluation and Management inpatient ward in a 531-bed public hospital in regional Australia. Fourteen ward staff participated in 13 semi-structured interviews. Two focus groups were held, of which the first included five business and senior clinicians who had knowledge of the business practices related to the discharge planning processes. The second focus group included five interview participants. The discharge planning processes was analysed using Functional Resonance Analysis Method (FRAM). The resultant FRAM model provided a graphical description of functional variability in the discharge planning processes. A total of 61 instances of variability were identified through the interviews and focus groups. Recommendations were developed and prioritised on each of these instances and presented to staff for implementation. It is concluded that the health care system is complex and modelling performance adjustments in everyday work provides staff at the coalface with an opportunity to highlight and resolve issues that they are continuing to face on a day-to-day basis in the workplace.

A socio-technical analysis of functional properties in a joint cognitive system: a case study in an aircraft cockpit

In a socio-technical work domain, humans, device interfaces and artefacts all affect transformations of information flow. Such transformations, which may involve a change of auditory to visual information & vice versa or alter semantic approximations into spatial proximities from instruments readings, are generally not restricted to solely human cognition. This paper applies a joint cognitive system approach to explore a socio-technical system. A systems ergonomics perspective is achieved by applying a multi-layered division to transformations of information between, and within, human and technical agents. The approach uses the Functional Resonance Analysis Method (FRAM), but abandons the traditional boundary between medium and agent in favour of accepting aircraft systems and artefacts as agents, with their own functional properties and relationships. The joint cognitive system perspective in developing the FRAM model allows an understanding of the effects of task and information propagation, and eventual distributed criticalities, taking advantage of the functional properties of the system, as described in a case study related to the cockpit environment of a DC-9 aircraft. Practitioner Summary: This research presents the application of one systemic method to understand work systems and performance variability in relation to the transformation of information within a flight deck for a specific phase of flight. By using a joint cognitive systems approach both retrospective and prospective investigation of cockpit challenges will be better understood. Abbreviations: ATC: air traffic control; ATCO: air traffic controller; ATM: air traffic management; CSE: cognitive systems engineering; DSA: distributed situation awareness; FMS: flight management system; FMV: FRAM model visualize; FRAM: functional resonance analysis method; GF: generalised function; GW: gross weight; HFACS: human factors analysis and classification system; JCS: joint cognitive systems; PF: pilot flying; PNF: pilot not flying; SA: situation awareness; SME: subject matter expert; STAMP: systems theoretic accident model and processes; VBA: visual basic for applications; WAD: work-as-done; WAI: work-as-imagined; ZFW: zero fuel weight

Systemic approaches to incident analysis in coal mines: Comparison of the STAMP, FRAM and “2–4” models

Coal mine accidents are often caused by the coupling of multiple factors rather than by a single factor. Therefore, explaining the nonlinear and coupling characteristics in accidents by using traditional accident theory is hard. To cope with the safety challenges caused by the extensive use of digital components and the construction of complex systems, incorporating the idea of system engineering into accident analysis is deemed effective. First, this paper introduces the basic principles and analysis steps of the Systems-Theoretic Accident Model and Processes (STAMP), Functional Resonance Analysis Method (FRAM) and “2–4” models and then applies the three models to the eight coal mine accidents. Finally, the three models are compared based on their characteristics, analysis processes and analysis results. The results show that the accident causes identified by the three methods cover the main causes in the accident investigation report, and new causes were identified. However, the results of the STAMP and FRAM models are more comprehensive and systematic, but the model characteristics and analysis processes are more complex, whereas the results of the “2–4” model analysis are relatively broad, but the analysis process is simple and easy to understand. Therefore, the study suggests that although the choice of accident causing model depends on the user's knowledge level or accident type, the STAMP and FRAM models are more suitable for analyzing a small number of complex coal mine accidents, while the “2–4” model is more advantageous in the analysis of large number of accidents.

Evaluation of governmental safety regulatory functions in preventing major accidents in China

Governmental safety regulatory functions play an important role in preventing major accidents by incorporating lessons from both the investigation of major accidents and the theory of system accident causation. However, to date, these functions have not been evaluated. In China, a unique aspect of accident prevention is that the government engages in macro-safety regulation. In this paper, the analysis process of the Functional Resonance Analysis Method (FRAM) is applied to the Chinese safety regulatory system to classify and evaluate governmental safety regulatory functions. The results show that there are nine main regulatory functions, and they are divided into four levels. The potential performance variability in the outputs of regulatory functions influences other functions through up-down coupling. The entire regulatory system could therefore undergo unexpected changes that could lead to major accidents. The two most important functions are F1, formulating a plan, and F2, enacting laws and regulations. This system reverses the past view of focusing only on the non-compliance behaviours of government regulators and companies. Some safety constraints are proposed in this paper, which mainly include monitoring and suppression, to reduce the unreasonable output of functions and unexpected changes. This paper provides a new perspective for other countries to further evaluate their governmental safety regulatory functions.

Evolution of the Functional Resonance Analysis Method (FRAM) through the combination with other methods

Traditionally, simple and complex linear models were used to analyze accidents and find their causes. The Resilience Engineering breaks with the traditional way of understanding safety focused on things that go wrong. In this way, the concept of safety is redefined to focus on things that go well. The new paradigm of Resilience Engineering emphasizes that when things go well in difficult circumstances, it is mainly due to the ability of workers to adapt, that is, their ability to recognize and absorb unexpected changes and events. In this new context, Functional Resonance Analysis Method enables to model how a system works and to understand the variability in daily performance. The objective of this research study is to present the main approaches that combine other methods with FRAM with the aim of improving it, as for example: Monte Carlo simulation, Fuzzy Logic theory, Model Checking, Analytical Hierarchical Process methodologies and Abstraction Hierarchy. Notice that the present study develops a non-exhaustive review of the methods that appears most frequently in the scientific Literature. The search process has been carried out in the main scientific databases such as Web of Knowledge, Science Direct or Google Scholar since they are identified as relevant to the research domain. In order to obtain adequate results concerning the objective of this work, we consider “Functional Resonance Analysis Method” as terms to perform the search in the title, abstract and keyword fields. After the data collection process, a total of 22 documents were obtained. Subsequently, all the retrieved documents were filtered by selecting those publications that had the purpose of combining the FRAM with another method to define the function variability in a semi-quantitative or quantitative manner. Then, after this filtering process, 18 studies were analysed and presented from diverse perspectives. Firstly, an analysis was conducted to explore the evolution of this research domain over time. As a result of this analysis, a growing trend in the publication of research is observed, both journal documents and conference documents. Secondly, an analysis concerning the sector where the study is focused is detailed since all the analyzed studies included an application example of their proposal. In this sense, the aviation sector was the one that appeared most frequently, followed by the maritime sector. Thirdly, the distribution of analysed studies on the basis of the country of authors has been presented, being Italy and China the reference countries in this research domain. Following, an analysis in relation to the journals where the documents are published is conducted. Finally, the proposals were grouped according to the different approaches that were combined with FRAM. As a general conclusion, the analysis of the new FRAM approaches shows that all the authors coincide in preserving the theoretical basis of FRAM for modeling complex systems. Despite this, there is still no approach that prevails over others and future research should continue to advance the evolution the Functional Resonance Analysis Method with the aim to facilitate the risk assessments in complex systems. Keywords : Functional Resonance Analysis Method; Resilience Engineering, Complex systems; Risk assessment; Safety.

Using the functional resonance analysis method on the drug administration process to assess performance variability

The complex and dynamic features of neonatal intensive care units (NICUs) have made it necessary to think beyond traditional safety management approaches. The Functional Resonance Analysis Method (FRAM) was thus developed to explore how functional variability affects the overall system. This study performs the FRAM on the drug administration process in a NICU to understand performance variability as conditions change, as well as to understand how variability in functions influences the system in terms of both success and failure. A mixed methods approach was used, including observations, interviews and workshops. From the data obtained, we identified 21 foreground and 16 background functions and developed 58 scenarios in relation to the effects of potential variability on the system. This study shows that the FRAM can be used to determine how to respond to changing conditions, to anticipate how variability might lead to system success or failure, to understand how to monitor it and to learn from all these.

A Functional Resonance Analysis Method Driven Resilience Quantification for Socio-Technical Systems

Due to the continuous increment in complexity of the socio-technical systems, decision makers call for new methods which are able to support timely as well as accurate decision-making related to resilience management. The current methods tend to be polarized on: efficiency-thoroughness forcing decision makers in making decisions on the base of resource availability instead of the problem to be solved. This paper presents a new fast-forward, cost-effective, and thorough enough framework to quantify resilience of a complex socio-technical system. The approach extends the functional resonance analysis method (FRAM) with a numerical method for the quantification of the analysis (Q-FRAM). In particular, it has been extended and operationalized the qualitative concepts of functional variability and dumping capacities into a method in which key performance indicators are derived from the model and aggregated into four indicators representing the FRAM resilience cornerstones (anticipate, respond, monitor, learn) through a bottom-up hierarchical approach. Finally, the four indicators are composed in a unique system resilience index that expresses the total variability present in the system at instant t . A numerical example of the use of the framework is provided together with a validation based on a comparison of the proposed approach with the current landscape.

Aplicação do fram para solução de problemas em sistemas sócio-técnicos complexos: estudo de caso em uma unidade hospitalar

Caracterizado pelo ambiente em constante mudança, o setor hospitalar possui problemas complexos, cuja solução necessita de uma abordagem adequada e robusta. O Functional Resonance Analysis Method (FRAM), método desenvolvido para modelagem de sistemas complexos, demonstra potencial como alternativa para solução de problemas no ambiente hospitalar. Por tratar-se de um método relativamente novo, a proposta desse estudo é analisar o desempenho do FRAM quando utilizado para a solução de problemas em uma unidade de internação de um hospital universitário. Para esse fim, as ações de melhoria propostas como resultado da aplicação do FRAM foram avaliadas de acordo com os critérios de dificuldade de implantação, a possibilidade de replicação, o tempo necessário para aplicação do método, o número de envolvidos, a necessidade de capacitação e o número total de oportunidade de melhoria identificadas. No contexto avaliado, FRAM resultou em ações de melhoria consideradas satisfatórias pelos envolvidos na aplicação, destacando-se pela visão realista que proporcionou aos participantes quanto à forma que o trabalho é rotineiramente executado.

A proactive operational risk identification and analysis framework based on the integration of ACAT and FRAM

Risks in the industrial operation processes involve complex system elements such as human, machine, organization, information, as well as nonlinear coupling relationships among them. Traditional risk analysis methods focus on the cause-effect relationships between the system elements and accidents, while ignoring what the correct and proper relationships should be. For a proactive risk identification and analysis, learning from success is suggested instead of learning from post hoc accidents, which requires that risk analysis identifies the normal functions and their couplings. Therefore, system functioning has been a subject of interest in the field of risk analysis. The Functional Resonance Analysis Method (FRAM) has been an effective tool to reveal the couplings and dependent relationships among different functions. However, the functions identification and interaction analysis in the FRAM is limited because there is no consistent or explicit stop rule. For a detailed and rigorous description of functions, the Accident Causation Analysis and Taxonomy (ACAT) model is used to enrich the FRAM by generating functions based on a closed-loop control system. Two operation processes in the hazardous industries are used as illustrations. The results show that more functional constraints and deep contributing factors to accidents can be identified with the hybrid approach.

Assessing operational impacts of automation using functional resonance analysis method

Interaction with automated systems and other types of technologies seems inevitable and almost a requirement of human work. The aviation sector, and in particular air traffic control, is devoting considerable efforts towards automation, to respond to the increased demand for capacity. Project AUTOPACE investigated the impacts of foreseeable automation over human performance and behaviour. The purpose was to identify new training requirements for air traffic controllers under foreseeable automation scenarios. In addition to the research carried out under the remit of AUTOPACE, the functional resonance analysis method was used to explore how the interactions between human operators and technology may change, as new automation features would be introduced into ATC operations. The FRAM model was developed based on AUTOPACE concept of operations, two levels of automation (E2 and E1) and was then used to instantiate three different non-nominal situations that were also investigated by the project. This paper presents the FRAM-based analysis carried out and discusses the potential impacts of automation, considering uncertainty and variability as two critical aspects that emerge from complex operation scenarios. The relation with AUTOPACE work is continuously established and the added value of FRAM for the pursuit of further AUTOPACE work is argued.

Functional modeling in safety by means of foundational ontologies

Modern theory of safety deals with systemic approach to safety, formalized in form of several systemic prediction models or methods such as FRAM (Functional Resonance Analysis Method) or STAMP (System-Theoretic Accident Model and Processes). The theory of each approach emphasizes different viewpoints to be considered in approaching various industrial safety issues. This paper focuses on FRAM and its functional viewpoint for modern complex sociotechnical systems. The methodology in this paper is based on the utilization of foundational ontologies to conceptualize the core ideas of FRAM, with the focus on the concept of functions as used in theory. The outcomes of the case study in the aviation domain provide for what needs to be determined to properly model functions in FRAM and they allow for better utilization of the method in real-case applications. The results also confirm some previous research, suggesting that modern systemic approach to safety is theoretically grounded on common - or at least complementary - tenets, to be prospectively integrated by means of ontology engineering.

A Proposal for a Predictive Performance Assessment Model in Complex Sociotechnical Systems Combining Fuzzy Logic and the Functional Resonance Analysis Method (FRAM)

Modern sociotechnical systems exhibit dynamic and complex behavior, which can be difficult to anticipate, model and evaluate. The perpetually evolving nature and the emergent properties of such systems require a continuous re-evaluation of adopted safety and risk analysis methods to comply with arising challenges and ensure successful performance. One of the interesting methods proposed in recent years is the Functional Resonance Analysis Method (FRAM). FRAM adopts a systemic perspective to model sociotechnical systems characterizing non-linear relationships and quality of outcome arising from performance variability and functional resonance. This paper aims to further improve the framework and expand the spectrum of features provided by FRAM through the integration of fuzzy logic. Fuzzy logic offers adequate mathematical tools capable of quantifying qualitative concepts and uncertain information applying comprehensible inference systems based on human judgement. An example of a possible application scenario is included through a simulation of aircraft on-ground deicing operations. The preliminary results of this project present an approach to generate numerical indicators for the quality of outputs, which can allow for a more comprehensible representation of potential performance variability. The presented model, however, requires further validation and optimization work to provide more representative and reliable results.