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Journal article(2023)
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Arie Adriaensen, Liliane Pintelon, Francesco Costantino, Giulio Di Gravio, Riccardo Patriarca
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.
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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.
Journal article(2023)
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Arie Adriaensen, Margherita Bernabei, Francesco Costantino, Andrea Falegnami, Sara Stabile, Riccardo Patriarca
The increasing usage of cobot applications reshapes work environments and working conditions, requiring specific advancements in organizational practices for health and safety. Enterprises should shift from a technocentric risk management approach to considering cobot application as socio-technical systems, for which a resilience engineering approach is beneficial. This study presents an instantiation of the resilience analysis grid in cobot applications with the aim of measuring resilience potentials in terms of the four cornerstones of resilience engineering (respond, learn, monitor, and anticipate). The assessment has been provided via a questionnaire to 15 companies making use of cobot applications. Results revealed that companies mainly focus on the risk assessment of cobot applications with a traditional view of machine-centric safety, paying less attention to assessing contexts and process variables. This observation seems to arise mainly due to the lack of formally available safety methods or limited guidance from technical standards. Additionally, traditional industrial approaches to risk management lack monitoring of several risks that are essential for managing resilience, defined as the adaptive capacity of people, organizations, and human-machine systems. In addition, companies strongly rely on data from the cobot manufacturer for their safety assessment. The resilience analysis grid was confirmed as a valuable assessment tool for the participating companies to identify improvement areas and assess health and safety from a resilience engineering perspective.
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The increasing usage of cobot applications reshapes work environments and working conditions, requiring specific advancements in organizational practices for health and safety. Enterprises should shift from a technocentric risk management approach to considering cobot application as socio-technical systems, for which a resilience engineering approach is beneficial. This study presents an instantiation of the resilience analysis grid in cobot applications with the aim of measuring resilience potentials in terms of the four cornerstones of resilience engineering (respond, learn, monitor, and anticipate). The assessment has been provided via a questionnaire to 15 companies making use of cobot applications. Results revealed that companies mainly focus on the risk assessment of cobot applications with a traditional view of machine-centric safety, paying less attention to assessing contexts and process variables. This observation seems to arise mainly due to the lack of formally available safety methods or limited guidance from technical standards. Additionally, traditional industrial approaches to risk management lack monitoring of several risks that are essential for managing resilience, defined as the adaptive capacity of people, organizations, and human-machine systems. In addition, companies strongly rely on data from the cobot manufacturer for their safety assessment. The resilience analysis grid was confirmed as a valuable assessment tool for the participating companies to identify improvement areas and assess health and safety from a resilience engineering perspective.
Review(2022)
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A. Adriaensen, F. Costantino, G. Di Gravio, R. Patriarca
Collaborative human–machine interaction will be progressively intensified in industrial applications. The aim of this article is to examine current approaches to cobot safety by showing that these approaches can additionally benefit from systems thinking methods. The first part of this article covers a narrative literature review on predominantly techno-centric robot safety approaches, with a strong focus on containing kinetic energy and ensuring separation with humans. The second part introduces systems thinking methods to analyze a socio-technical perspective on cobot safety, including joint cognitive systems and distributed cognition perspectives. This explorative research dimension is expected to overcome an overly narrow interpretation of safety issues, anticipating the challenges ahead in ever more complex cobot applications. This article embraces a socio-technical perspective to explore the potential of Joint Cognitive Systems to manage risk and safety in cobot applications. Three systemic safety analysis approaches are presented and tested with a demonstrator case study concerning their feasibility for cobot applications: System-Theoretic Accident Model and Processes (STAMP); Functional Resonance Analysis Method (FRAM); and Event Analysis of Systemic Teamwork (EAST). These methods each provide interesting extensions to complement the traditional understanding of risk as required by current and future industrial cobot implementations. The power of systemic methods for safer and more efficient cobot operations lies in revealing the distributed and emergent result from joint actions and overcoming the reductionist view from individual failures or single agent responsibilities. The safe operation of cobot applications can only be achieved through alignment of design, training, and operation of such applications.
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Collaborative human–machine interaction will be progressively intensified in industrial applications. The aim of this article is to examine current approaches to cobot safety by showing that these approaches can additionally benefit from systems thinking methods. The first part of this article covers a narrative literature review on predominantly techno-centric robot safety approaches, with a strong focus on containing kinetic energy and ensuring separation with humans. The second part introduces systems thinking methods to analyze a socio-technical perspective on cobot safety, including joint cognitive systems and distributed cognition perspectives. This explorative research dimension is expected to overcome an overly narrow interpretation of safety issues, anticipating the challenges ahead in ever more complex cobot applications. This article embraces a socio-technical perspective to explore the potential of Joint Cognitive Systems to manage risk and safety in cobot applications. Three systemic safety analysis approaches are presented and tested with a demonstrator case study concerning their feasibility for cobot applications: System-Theoretic Accident Model and Processes (STAMP); Functional Resonance Analysis Method (FRAM); and Event Analysis of Systemic Teamwork (EAST). These methods each provide interesting extensions to complement the traditional understanding of risk as required by current and future industrial cobot implementations. The power of systemic methods for safer and more efficient cobot operations lies in revealing the distributed and emergent result from joint actions and overcoming the reductionist view from individual failures or single agent responsibilities. The safe operation of cobot applications can only be achieved through alignment of design, training, and operation of such applications.
Journal article(2022)
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Arie Adriaensen, Nicole Berx, Liliane Pintelon, Francesco Costantino, Giulio Di Gravio, Riccardo Patriarca
This paper sets up a framework to assess co-agency in human-robot interactions, and applies it specifically to the socio-technical safety analysis of collaborative robots. We also examine to what extent the concept of Situation Awareness can be applied to assess collaborative robots as efficient team members in socio-technical systems. We explain some theoretical concerns with traditional concepts of Situation Awareness and defend why the concept of Joint Cognitive Systems, which maps the conceptualization of the cognitive system onto the work system as a whole, is best suited for issues of distributed cognition and controllability in human-robot interaction. Thereafter we present a five-step methodology specifically conceived for cobot applications serving the aim of goal coordination between multiple agents by functional interactions. The proposed framework merges two existing safety and resilience analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. These methods are used in combination to assess shared control in safe and efficient human-robot interaction from a systems-thinking perspective. This allows to describe the systemic conditions for Distributed Situation Awareness in terms of observable system interactions and as an emergent object of distributed cognition. Instead of looking at undesirable safety outcomes, we have imposed the focus of co-agency as the unit of analysis in line with the Joint Cognitive Systems perspective. The theoretical insights from this paper are additionally applied to a hypothetical but credible demonstration case study with collaborative warehouse robots.
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This paper sets up a framework to assess co-agency in human-robot interactions, and applies it specifically to the socio-technical safety analysis of collaborative robots. We also examine to what extent the concept of Situation Awareness can be applied to assess collaborative robots as efficient team members in socio-technical systems. We explain some theoretical concerns with traditional concepts of Situation Awareness and defend why the concept of Joint Cognitive Systems, which maps the conceptualization of the cognitive system onto the work system as a whole, is best suited for issues of distributed cognition and controllability in human-robot interaction. Thereafter we present a five-step methodology specifically conceived for cobot applications serving the aim of goal coordination between multiple agents by functional interactions. The proposed framework merges two existing safety and resilience analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. These methods are used in combination to assess shared control in safe and efficient human-robot interaction from a systems-thinking perspective. This allows to describe the systemic conditions for Distributed Situation Awareness in terms of observable system interactions and as an emergent object of distributed cognition. Instead of looking at undesirable safety outcomes, we have imposed the focus of co-agency as the unit of analysis in line with the Joint Cognitive Systems perspective. The theoretical insights from this paper are additionally applied to a hypothetical but credible demonstration case study with collaborative warehouse robots.
Journal article(2021)
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A. Adriaensen, L. Pintelon, F. Costantino, G. Di Gravio, R. Patriarca
The technology for collaborative robots and the way these technologies are used in current socio-technical work systems are rapidly evolving in industrial applications. In the absence of prescribed safety assessment methods from normative standards, this paper explores the capabilities of an STPA analysis for the socio-technical behaviour of collaborative robot applications. We applied the STPA to a collaborative robot with a heavy-load manipulating arm and gripper, mounted on an AGV-type mobile base. The scope of the analysis is limited to a single AGV mode controller. It explores the systems thinking capabilities of STPA for the safety analysis, from which the principles can be applied to several types of collaborative robot applications.
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The technology for collaborative robots and the way these technologies are used in current socio-technical work systems are rapidly evolving in industrial applications. In the absence of prescribed safety assessment methods from normative standards, this paper explores the capabilities of an STPA analysis for the socio-technical behaviour of collaborative robot applications. We applied the STPA to a collaborative robot with a heavy-load manipulating arm and gripper, mounted on an AGV-type mobile base. The scope of the analysis is limited to a single AGV mode controller. It explores the systems thinking capabilities of STPA for the safety analysis, from which the principles can be applied to several types of collaborative robot applications.
Journal article(2019)
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Arie Adriaensen, Riccardo Patriarca, Anthony Smoker, Johan Bergström
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.
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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.