Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance
Abstract
:1. Introduction
- (1)
- What are the user-centred design and acceptance issues that face the introduction of autonomous rail maintenance systems, in terms of individual, organisational and societal concerns?
- (2)
- How can our understanding of these issues be used to identify effective means for working with users (i.e., rail staff) and the public to get the maximum benefit for them and for the railways as a whole? The following paper addresses these questions through use of a scenario as the basis for 25 semi-structured interviews with experts both from rail and from other domains with experience in robotics and UAVs. The analysis of these interviews identifies a structured set of factors that need to be anticipated for successful adoption. Additionally, the interviews highlight frameworks from existing human factors work—both from rail and from other domains—that can be applied, with adaptation, to support user-centred autonomous maintenance. These contributions point towards future design, deployment and engagement strategies for human-centred adoption of autonomous rail maintenance.
2. Background
- There is suspicion or outright rejection of the technology [25].
- The technology requires significant training and/or users do not have a good understanding of how it works, leading to a negative impact on performance [26].
- The technology changes work in unanticipated ways, which may have unanticipated reverberations across working practice [27].
- The technology provides an initial advantage in reducing workload, but, over time, mechanisms (particularly automated mechanisms that were intended to assist work) drive new expectations of performance and capacity or new levels of reliance on technology that was only originally intended to assist [28,29].
2.1. Users
2.2. Teamworking
- Human–robot,
- Human–human,
- Robot–human,
- Robot–robot,
- The human’s overall mission awareness.
- Communication: Poor communication between the team members through using inconsistent automated systems (e.g., utilising different legacy systems or different mixes of legacy and new technology at different locations).
- Rule dissemination: Lack of clear instructions and poor implementation of autonomy will potentially lead to misunderstanding rules.
- Competence capability and certification: Automation may lead to reduced competence which will also have an impact on the quality of human intervention in the case of system failures. Appropriate checks and balances should be in place to facilitate successful supervisory control.
- Working hours—different behaviour out of normal hours: Shift work, fatigue and level of vigilance can be modified when automation is more centrally introduced within the workplace.
2.3. Organisational Factors
- Enablers:
- ○
- Operator participation in the implementation;
- ○
- Communication of the change to the workforce;
- ○
- Visible senior management commitment and support to the project;
- ○
- Provision of training to the workforce;
- ○
- Empowerment of the workforce;
- ○
- Use of a process champion during the implementation.
- Barriers:
- ○
- Lack of union involvement;
- ○
- Lack of awareness of the complexity of the manual process by the system integrator;
- ○
- Capturing the variability of the manual process prior to introducing the automated system;
- ○
- Allocation of resources for the development of the automated system.
2.4. Societal
3. Method
3.1. Material
- A consent and information sheet, sent to all participants. This allowed all participants to have a clear understanding of the study aims, expectations around their involvement and information about their rights to anonymity and data protection;
- A visual scenario describing how automation could be used (presented in Figure 1)—this study covered both short-term and long-term applications of automation to the railways. This scenario served to give everyone a common understanding of the automation relevant to the study, to give people from outside of rail engineering an idea of how automation could be used in the future and to ensure that the interviews could focus more on the human and organisational aspects, rather than being misdirected into a discussion of technology implementation;
- A question guide was also prepared to shape the interview and to provide a degree of consistency between the three interviewers involved in the project.
3.2. Participants
3.3. Procedure
3.4. Analysis
- Short-term scenario:
- ○
- User factors;
- ○
- Team factors;
- ○
- Organisational factors;
- ○
- Societal factors.
- Long-term scenario:
- ○
- User factors;
- ○
- Team factors;
- ○
- Organisational factors;
- ○
- Societal factors.
- Any other comments of note.
4. Results
4.1. User Factors
4.1.1. Acceptance
4.1.2. Human–Machine Interface
4.1.3. Safety
- Safe operation of the automation
4.1.4. Robots as ‘Tools’
4.1.5. Cognitive Factors for Working with Automation
4.1.6. Context
- Location—understanding general geographic location; the specific location in terms of its proximity to other assets; access to the location; whether the location was isolated or near to urban environments; interfaces with the public (e.g., level crossings).
- Working arrangements—whether the work was being conducted without protection (highly unlikely in the short term but possible in a future scenario where robots had knowledge of the real-time timetable); as a single worksite within a possession or as one of a number of worksites within a possession.
- Physical environment—whether this took place in the day, at night, in rail, cold, sunshine, etc.
- Asset context—what kind of asset was being inspected, variability among assets of the same type; age of the asset, etc.
4.1.7. Individual Differences
- Operators’ different skill levels and their ability to understand and use equipment involving a high degree of technology.
- Operators’ experience, particularly in more ‘craft’ jobs (i.e., those jobs that might be performed by hand and/or involve a high degree of tacit, physical and sensory knowledge or skill).
- Decision-making ability—not all people had the same ability to engage and make critical decisions.
- Motivations to work—at the very frontline, some of the people attracted to the job were attracted because of the autonomy, working outdoors, physical work, not being compelled to use IT, etc. Therefore, the introduction of robotics could run contrary to what they wanted from the job.
4.2. Team Factors
4.2.1. Authority
4.2.2. Identifying Affected Roles
- Immediate team and trackwork roles—not only those who would be working with or around automation but those who might come into indirect contact with robotics, particularly in larger worksites. It was noted that many of these people may be from the maintenance supply chain.
- Wider asset management roles who would be required to plan or interpret asset maintenance and renewal and therefore use the information that autonomous maintenance systems might capture.
- Wider planning roles who would need to factor in the delivery and management of robots and other forms of automation within their maintenance planning.
- Signalling and controllers of the electrical supply who could be required to provide protection and would potentially play a role in managing the situation should a fault develop (e.g., a robot fails leading to the work overrunning into the expected handback of the network).
- Drivers that need to know what to expect and potential risks if work involving robots is taking place on and around the railway.
4.2.3. Working in Possessions
4.2.4. Working with Teams
4.2.5. Repeatability/Reliability
4.3. Organisational Factors
4.3.1. Within
Leadership
Engagement
- Decision makers and managers, e.g., track maintenance engineers—need to be convinced of the benefits of the project and technology. How can it improve their work processes, and how can they assess where it is going to have a genuine positive impact? Will it impact on the staff and resources they have available?
- Unions—should be involved to understand the safety and performance benefits, while discussing the potential changes in resourcing that may result.
- Frontline staff—to understand the benefits and to understand their perceptions and gather their expertise on how best to introduce the technology into the working environment and what procedural and training changes will be required.
Phased Introduction
Realistic Scope
Resourcing
- Financial resourcing—the kind of projects being described are likely to take time and run over more than the control period. Therefore, as well as there being sufficient financial resources in the short term, there has to be a long-term commitment to fund the project over extended periods.
- People—when projects of this type are initially launched, they tend to take more of people’s time, not less, as they learn to use the new process. Often (e.g., for the use of new forms of inspection), they need to run in parallel with the existing processes until they are tested against existing processes and become established. In addition, resourcing should not be reduced because the technology has made efficiency gains but should be redeployed into other high-priority tasks.
- Appetite for project risk—projects of this type take time and are unlikely to work first time. There will be changes to plans and to scope as the capabilities and limitations of autonomous technology become clear. Projects must be planned and delivered with an understanding that, for the short term at least, there will be risks and problems to solve. This also relates to the culture of the project where people are allowed to fail and to learn without fear of reprimand.
Procedures and Processes
Competence, Training and Selection
Infrastructure to Reflect Automation
4.3.2. Inter-Organisational—Upstream
Liability
Integration
Issues of Technology Transfer
Service Not Product
4.3.3. Downstream
4.4. Societal Factors
4.4.1. Expectation
4.4.2. Crime
4.4.3. Social Responsibility
4.4.4. Structured Communication
5. Discussion
5.1. Observations
- User issues relating to trust, workload and robotic HMI;
- Team issues relating to awareness of the robot around multiple actors and changes to roles;
- Organisational issues relating to competence and having planned engagement and deployment strategies;
- Societal issues related to the wider acceptance of robotics.
5.2. Recommendations
5.2.1. Ontology
- The stages of work (planning, access, performing the work, egress).
- Dimensions of safety (safety of the robot, safe work quality, safety of workers, safe action in unexpected events). The important point to note here is that safety arrangements are likely to be more complex than those previously encountered in many, more ‘closed’, automation working environments (e.g., manufacturing, warehousing) and therefore needs both careful planning and appropriate reflection in standards, training, working practices and the design of the behaviours of the automation.
- Types of factors—user, team, organisational and societal.
- Maturity levels of the technology.
- Relevant rail standards.
5.2.2. Structured Engagement
5.2.3. Procedural Design
5.3. Limitations
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
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Golightly, D.; Chan-Pensley, J.; Dadashi, N.; Jundi, S.; Ryan, B.; Hall, A. Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance. Sustainability 2022, 14, 2123. https://doi.org/10.3390/su14042123
Golightly D, Chan-Pensley J, Dadashi N, Jundi S, Ryan B, Hall A. Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance. Sustainability. 2022; 14(4):2123. https://doi.org/10.3390/su14042123
Chicago/Turabian StyleGolightly, David, Jamie Chan-Pensley, Nastaran Dadashi, Shyma Jundi, Brendan Ryan, and Amanda Hall. 2022. "Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance" Sustainability 14, no. 4: 2123. https://doi.org/10.3390/su14042123
APA StyleGolightly, D., Chan-Pensley, J., Dadashi, N., Jundi, S., Ryan, B., & Hall, A. (2022). Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance. Sustainability, 14(4), 2123. https://doi.org/10.3390/su14042123