Radical systems thinking and the future role of computational modelling in ergonomics: an exploration of agent-based modelling

The role of smart technology, managerial initiatives and human factors on sustainable manufacturing: a case study of Indonesian oil and gas workers

This study aims to analyse and determine the effect of Big Data, the Internet of Things (IoT), and physical-cyber system variables on human factors in refinery industry operators and the influence of human factors and managerial initiatives on sustainable manufacturing. The method used in this study is a quantitative method using partial least square-structural equation modelling (PLS-SEM). The respondents in this study were workers of Indonesia's upstream oil and gas sector. The results of this study indicate that Big Data, IoT, and Physical Cyber Systems (PCS) have a positive and significant effect on the human factor. In addition, there is a significant relationship between human factors and sustainable manufacturing. Furthermore, it is also found that there is a relationship between managerial initiatives and sustainable manufacturing. However, the managerial initiative cannot moderate the human factor and sustainable manufacturing.

Interactions in Sociotechnical Systems: Achieving Balance in the Use of an Augmented Reality Mobile Application

OBJECTIVE

We explore relationships between barriers and facilitators experienced by users to understand dynamic interactions in sociotechnical systems and improve a mobile phone-based augmented reality application that teaches users about the contents of a standardized pediatric code cart.

BACKGROUND

Understanding interactions between performance obstacles and facilitators can provide guidance to (re)designing sociotechnical systems to improve system outcomes. Clinicians should know about contents and organization of code carts, and an augmented reality mobile application may improve that knowledge but changes the sociotechnical system in which they learn. Prior work identified barriers and facilitators impacting the use of this application-participants described dimensions together, indicating interactions that are explored in the current study.

METHOD

We conducted four focus groups (number of clinicians = 18) and two interviews with clinicians who used the application. We performed a secondary analysis of focus group data exploring interactions between previously identified barriers and facilitators to application use. We used epistemic network analysis to visualize these interactions.

RESULTS

Work system barriers interacted with barriers and facilitators interacted with facilitators to amplify cumulative negative or positive impact, respectively. Facilitators balanced barriers, mitigating negative impact. Facilitators also exacerbated barriers, worsening negative impact.

CONCLUSION

Barriers and facilitators interact and can amplify, balance, and exacerbate each other-notably, positives are not always positive. To obtain desired outcomes, interactions must be further considered in sociotechnical system design, for example, the potential improvements to the application we identified.

Analysing dynamic work systems using DynEAST: a demonstration of concept

The capability of current Ergonomics methods to capture dynamism is limited, stifling our understanding of work-as-done, distributed situational awareness and organisational drift. This paper provides a demonstration of concept of DynEAST; an extension of the EAST framework underpinned by principles from Dynamic Network Analysis, to capture elements of dynamism within work systems. The DynEAST concept is applied to a railway maintenance case study. Case study findings demonstrate how DynEAST outputs can be used to advance our understanding of the aforementioned phenomena and better equip practitioners for current and future Ergonomics challenges.Practitioner summary: This paper introduces the DynEAST method. DynEAST enables HF/E practitioners to model and analyse dynamic features of complex work systems. The development of DynEAST is timely due to the concurrent proliferation of increasingly complex sociotechnical systems and stagnation of HF/E methods development; particularly those able to model systemic dynamism. Abbreviations: DynEAST: dynamic event analysis of systemic teamwork; EAST: dynamic event analysis of systemic teamwork; HF/E: human factors and ergonomics; HF: human factors; DNA: dynamic network analysis; HTA: hierarchal task analysis; CWA: cognitive work analysis; CAST: causal analysis based on system theory; STAMP: system theoretic accident model and processes; FRAM: functional resonance analysis method; SNA: social network analysis; DSA: distributed situational awareness; PPO: possession protection officer; PO: protection officer; RTS: railway track signals; LPA: local possession authority; SMEs: subject matter experts.

Information assistance systems as preventive mediators between increasing customization and mental workload

BACKGROUND: The future of work in Germany is shaped by megatrends like globalization, automatization, digitization, and the demographic change. Furthermore, mass customization and the increasing usage of AI even in manual assembly offers new opportunities as well as it creates new challenges. OBJECTIVE: The trend towards mass customization in turn leads to increased complexity in production, which results in additional mental workload. This effect will continue in the foreseeable future. METHOD: Especially for small and medium sized companies, the backbone of Germany’s economy, automatization and Human-Robot-Collaboration will take time to develop. Information assistance systems are and will be a bridging technology to help organizations to manage increasing complexity and the mental workload of their employees to not only boost productivity but also keep their workforce healthy. The ongoing demographic change further underlines the need to use information assistance systems to compensate possible age-associated deficits, but also keep older employees committed to their work and avoid effects of disengagement or disenfranchisement through participatory ergonomics. RESULTS: Information assistance systems can only develop their inherent potential if they are designed to support employees of varying age, competence levels, and affinity for technology. Participatory development and early engagement are key factors for an increased acceptance and usage of the systems as well as the individualization to make it suitable for each individual employee. CONCLUSION: Expanding the functionalities to an adaptive assistance system, using physiological correlates of mental workload as an input, is conceivable in the future.

The Binary-Based Model (BBM) for Improved Human Factors Method Selection

OBJECTIVE

This paper presents the Binary-Based Model (BBM), a new approach to Human Factors (HF) method selection. The BBM helps practitioners select the most appropriate HF methodology in relation to the complexity within the target system.

BACKGROUND

There are over 200 HF methods available to the practitioner and little guidance to help choose between them.

METHOD

The BBM defines a HF "problem space" comprising three complexity attributes. HF problems can be rated against these attributes and located in the "problem space." In addition, a similar HF "approach space" in which 66 predictive methods are rated according to their ability to confront those attributes is defined. These spaces are combined into a "utility space" in which problems and methods coexist. In the utility space, the match between HF problems and methods can be formally assessed.

RESULTS

The method space is split into octants to establish broad groupings of methods distributed throughout the space. About 77% of the methods reside in Octant 1 which corresponds to problems with low levels of complexity. This demonstrates that most HF methods are suited to problems in low-complexity systems.

CONCLUSION

The location of 77% of the rated methods in Octant 1 indicates that HF practitioners are underserved with methods for analysis of HF problems exhibiting high complexity.

APPLICATION

The BBM can be used by multidisciplinary teams to select the most appropriate HF methodology for the problem under analysis. All the materials and analysis are placed in the public domain for modification and consensus building by the wider HF community.

Research Outputs in Ergonomics and Human Factors Engineering: A bibliometric and co-word analysis of content and contributions

This paper analyzes research outputs in Ergonomics and Human Factors Engineering (EHFE), revealing its intellectual structure via bibliometric techniques, co-word, network analysis, and science visualization tools. Population comprises of 23,472 records published during 2000-2018, in 19 core journals of Human Factors and Ergonomics subject category in Scopus. The findings showed that in EHFE fields "the United States", "University of Central Florida" and "Stanton NA" were the most productive country, university and author, respectively. It was also found that "Ergonomics" was the most frequent keyword and "Ergonomics and Human Factor" were the most frequent co-occurred keywords in EHFE documents. Hierarchical cluster analysis led to the creation of eight topical clusters, including among others "Biomechanics ergonomics", "Work-related MSDs & work system design", and "Performance". The results indicated that "Biomechanics ergonomics" was a well-matured cluster while "Human machine interaction", "Ergonomics design", "Macro-ergonomics", and "Cognitive ergonomics" were found to be emerging or declining clusters.

Complexity theory in accident causation: using AcciMap to identify the systems thinking tenets in 11 catastrophes

The quest to explain and understand the cause of accidents is both ever-present and ongoing amongst the safety science community. In an attempt to advance the theory and science of accident causation, researchers have recently formalised a set of '15 systems thinking tenets' that cover the conditions and characteristics of work systems that are believed to contribute to the cause of accidents. The purpose of this study was to attempt to identify the systems thinking tenets across a range of different systems and accidents using the Accident Mapping (AcciMap) method. The findings suggest that the tenets can be attributed to play a role in accident causation, however as a result of this process, the capability of AcciMap has been brought into question. Implications and directions for future research are described. Practitioner Summary: This study is an extension of previous work that suggested there was a need to test for the 'systems thinking tenets of accident causation' in a multi-incident dataset. We used AcciMap to evaluate whether it has the capability to support ongoing accident analysis activities in ergonomics research.

Resolving the differences between system development and system operation using STAMP: a road safety case study in a low-income setting

Road safety strategies adopted worldwide have made significant progress in reducing road trauma, but have stagnated more recently. The situation in low- and middle-income countries is even worse with no significant decrease in fatality rates. Safety researchers have argued that adopting sociotechnical systems approach is necessary to make significant advancements and improvements. The aim of this study was to develop a control structure model of the Bangladesh road safety system by identifying the actors and organisations involved across the system. Expert stakeholders were identified and interviewed, and relevant information was gathered in order to generate the Systems Theoretic Accident Model and Process control structure model. Throughout the analysis of this model, differences in the control and feedback mechanisms of the system were identified, and road safety intervention recommendations were made. Future research should also predict potential risks within the system and propose proactive and preventative countermeasures. Practitioner summary: In this article, a Systems Theoretic Accident Model and Process control structure model of the Bangladesh road safety system is developed, and the involved actors are identified. Based on interviews and workshops with expert stakeholders, differences in the controls and feedback mechanisms in the system were identified, and road safety intervention recommendations were made. Abbreviations: BUET: Bangladesh University of Engineering and Technology.

Aiding decision makers to reopening of places of worship

OBJECTIVE

Our research objective is to work with leaders of houses of worship in the local community to assess options for the physically reopening of places of worship.

METHOD

This study consists of two parts. The first part consists of working with a leader of a house of worship to formulate a decision process based on the priorities of the organization and its physical size and population. The second part involves the modeling of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus spread within a physical space to provide the leadership of the house of worship an estimate of the outcomes of deciding on various courses of action. The model is a modification of a standard virus model developed for the NetLogo programming environment.

RESULTS

The team worked with a large local church in Pennsylvania to physically reopen a worship service. Based on the questionnaire data, the congregation did not prefer the strongest form of the SARS-CoV-2 virus mitigation (mask wearing and social distancing) but favored either mask required and no social distancing or masks optional and social distancing. The team simulated conditions representative of the church and found that social distancing is the key factor to mitigate spread.

CONCLUSION

Given the preferences of the congregation, our simulation results suggested that one of the favored options would likely yield a large number of infections (>10% in a scenario with an asymptomatic carrier). This information was provided to the leadership to guide their decision-making for the coming months as poor weather will rule out outdoor worship as a viable option.

Cognitive Manufacturing in Industry 4.0 toward Cognitive Load Reduction: A Conceptual Framework

Cognitive manufacturing utilizes cognitive computing, the industrial Internet of things (IoT), and advanced analytics to upgrade manufacturing processes in manners that were not previously conceivable. It enables associations to improve major business measurements, for example, productivity, product reliability, quality, and safety, while decreasing downtime and lowering costs. Considering all the facts that can prejudice the manufacturing performance in Industry 4.0, the cognitive load has received more attention, since it was previously neglected with respect to manufacturing industries. This paper aims to investigate what causes cognitive load reduction in manufacturing environments, i.e., human–computer interaction technologies that reduce the identified causes and the applications of cognitive manufacturing that use the referred technologies. Thus, a conceptual framework that links cognitive manufacturing to a reduction of the cognitive load was developed.