Monitor, anticipate, respond, and learn: developing and interpreting a multilayer social network of resilience abilities

Resilient performance is influenced by social interactions of several types, which may be analysed as layers of interwoven networks. The combination of these layers gives rise to a “network of networks”, also known as a multilayer network. This study presents an approach to develop and interpret multilayer networks in light of resilience engineering. Layers correspond to the four abilities of resilient systems: monitor, anticipate, respond, and learn. The proposal is applied in a 34-bed intensive care unit. To map relationships between actors in each layer, a questionnaire was devised and answered by 133 staff members, including doctors, nurses, nurse technicians, and allied health professionals. Two multilayer networks were developed: one considering that actors are 100% available and reliable (work-as-imagined) and another considering suboptimal availability and reliability (work-as-done). The multilayer networks were analysed through actor-centred (Katz centrality, degree deviation, and neighbourhood centrality) and layer-centred metrics (inter-layer correlation, and assortativity correlation). Strengths and weaknesses of social interactions at the ICU are discussed based on the adopted metrics

WAx: an integrated conceptual framework for the analysis of cyber-socio-technical systems

Modern work domains are constituted by an intertwined set of social and technical actors with different, often conflicting, functional purposes. These agents act jointly to ensure system's functioning under both expected and unexpected working conditions. Considering the increasing digitalization and automation of work processes, socio-technical systems are progressively including interconnected cyber technical artefacts, thus becoming cyber-socio-technical systems (CSTSs). Adopting a natural science perspective, this paper aims to explore knowledge creation and knowledge conversion within CSTSs, as rooted in an in-depth analysis of work practices and work contexts. The paper proposes a conceptual framework which unveils the relationships between different work representations, i.e. relying on Work-As-Imagined, Work-As-Done, Work-As-Disclosed, Work-As-Observed, intended as knowledge entities generated by different agents, i.e. sharp-end operators, blunt-end operators, and analysts. The recursive and fractal nature of the proposed WAx (Work-As-x) framework ensures its adaptability for different granularity levels of analysis, fostering the understanding, modeling, and analysis of work practices, while abandoning reductionist and over-simplistic approaches

The occupational health and safety risks of ongoing digital transformation. A knowledge management software powered literature review

The fast technical-organizational transformation undergoing, promoted by Industry 4.0 as well as other similar initiatives, partly sped up due to the Covid-19 pandemic, is radically changing actors, modes, and environments of human work. Although part of these innovations is directed at occupational health and safety (OHS), some scholars raise reasonable doubts, arguing that the same innovations even if they solve some problems, could create new ones. The 4th industrial revolution is likely introducing entirely new categories of worker risks. This review explores the evidence base that supports the latter hypothesis. Besides, it proposes an innovative and potentially useful combination of methods and computer applications. By applying the Prisma methodology, tagging one-by-one activity, and hyperlinks, the paper proposes a knowledge graph explorable in terms of semantic, logical and chronological links as well as argumentative. In the final phase, the paper synthesizes in a meta-annotation ten recurring themes and clusters that emerged in this bottom-up process of knowledge elicitation

Lean ICU layout re-design: a simulation-based approach

Healthcare facilities require flexible layouts that can adapt quickly in the face of various disruptions. COVID-19 confirmed this need for both healthcare and manufacturing systems. Starting with the transfer of decision support systems from manufacturing, this paper generalizes layout re-design activities for complex systems by presenting a simulation framework. Through a real case study concerning the proliferation of nosocomial cross-infection in an intensive care unit (ICU), the model developed in systems dynamics, based on a zero order immediate logic, allows reproducing the evolution of the different agencies (e.g., physicians, nurses, ancillary workers, patients), as well as of the cyber-technical side of the ICU, in its general but also local aspects. The entire global workflow is theoretically founded on lean principles, with the goal of balancing the need for minimal patient throughput time and maximum efficiency by optimizing the resources used during the process. The proposed framework might be transferred to other wards with minimal adjustments; hence, it has the potential to represent the initial step for a modular depiction of an entire healthcare facility

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

Serious games for industrial safety: An approach for developing resilience early warning indicators

The development of safety indicators represents an integral part of any safety management process. Safety indicators are generally classified as leading or lagging, respectively whether they are active (providing feedback on performance before an accident or incident), or reactive measurements (identifying and reporting on incidents to identify weaknesses and failures). Leading indicators have been largely addressed as early warning instruments crucial to assess the potential for either safety events (accidents, incidents), or system's resilience. The Resilience-based Early Warning Indicator (REWI) method is a representative approach to develop such indicators. However, its main challenges are related to the data gathering process, which is traditionally managed by open-ended interviews or surveys, and the fact that the developed indicators may not necessarily represent proxy measures of system performance. This paper presents an alternative methodological framework for the development of leading indicators. We will explore the use of GREWI (Games for Resilience-based Early Warning Indicator method), a new method based on gamified data gathering, more specifically related to serious games. Abandoning traditional tick-box surveys, the proposed approach is intended to favour workers' engagement in workplace safety and, more in general, to overcome psychological barriers to their participation. The approach has been explored in a case study within chemical industry. In particular, the safety-critical sector of ammonia production has been addressed, with the purpose to promote and improve its resilience towards unwanted events

Actionable safety analyses in socio-technical systems with myFRAM

Complex systems require dedicated models, methods and techniques since safety management in socio-technical systems no longer should rely just on causality principles and structural decomposition. The overall behavior of the system should be considered as emerging from the non-linear interaction of the underlying subsystems. The Functional Resonance Analysis Method (FRAM) is one systemic approach allowing for the construction of deeply informative models. Such semantic richness entails a complexity of the resulting models significantly reflecting a useful portion of systems' reality. Unfortunately, as soon as the analyzed systems are little more than mundane, this richness of information becomes unmanageable whenever it is relying only upon qualitative methods. This paper presents myFRAM version 1.0.3, a free Excel add-on that paves the way for a multitude of systematic analysis types ranging from statistics to complex network analysis and simulation. The trust put in myFRAM by many safety experts who have already adopted it, confirms that it is a valuable tool to sustain the FRAM method. This application builds bridges to several different software and techniques currently available, expanding the potential of the method itself

Knowledge fusion for distributed situational awareness driven by the wax conceptual framework

Large crisis scenarios involve several actors, acting at the blunt-end of the process, such as rescue team directors, and at the sharp-end, such as firefighters. All of them have different perspectives on the crisis situation, which could be either coherent, alternative or complementary. This heterogeneity of perceptions hinders situational awareness, which is defined as the achievement of an overall picture on the above-mentioned crisis situation. We define knowledge fusion as the process of integrating multiple knowledge entities to produce actionable knowledge, which is consistent, accurate, and useful for the purpose of the analysis. Hence, we present a conceptual modelling approach to gather and integrate knowledge related to large crisis scenarios from locally-distributed sources that can make it actionable. The approach builds on the WAx framework for cyber-socio-technical systems and aims at classifying and coping with the different knowledge entities generated by the involved operators. The conceptual outcomes of the approach are then discussed in terms of open research challenges for knowledge fusion in crisis scenarios

New and emerging hazards for health and safety within digitalized manufacturing systems

The Fourth Industrial Revolution is radically reshaping the procedures and the manufacturing environments through the digitalization process. The digitalization process can change ac-cording to the context and to specific solutions, and it is able to modify manufacturing systems and production areas. All the employees are directly affected by the transformation of the working en-vironment, manufacturing tools, and working conditions and by the increasing need for new com-petencies. In this context, it is crucial to identify new and emerging hazards concerning the health and safety of the employees to ensure a conscious and safe digital transformation for everyone in-volved. In this regard, the paper presents the state of the research and defines seven areas of interest for a safe and harmless digital transformation for the employees, drawing attention to the hazards in the different technological areas. The state of the research unveils the absence of detailed analysis to identify specific hazards of 4.0 technologies. Therefore, every specific 4.0 technologies is analyzed by an extensive review to provide a comprehensive matrix of new and emerging hazards for health and safety within digitalized manufacturing systems. The results can help manufacturing organizations to perform robust risk assessments for worker when introducing specific 4.0 technologies