Evaluating Technicians' Workload and Performance in Diagnosis for Corrective Maintenance.

The advancement in digital technology is transforming the world. It enables smart product-service systems that improve productivity by changing tasks, processes, and the ways we work. There are great opportunities in maintenance because many tasks require physical and cognitive work, but are still carried out manually. However, the interaction between a human and a smart system is inevitable, since not all tasks in maintenance can be fully automated. Therefore, we conducted a controlled laboratory experiment to investigate the impact on technicians' workload and performance due to the introduction of smart technology. Especially, we focused on the effects of different diagnosis support systems on technicians during maintenance activity. We experimented with a model that replicates the key components of a computer numerical control (CNC) machine with a proximity sensor, a component that requires frequent maintenance. Forty-five participants were evenly assigned to three groups: a group that used a Fault-Tree diagnosis support system (FTd-system), a group that used an artificial intelligence diagnosis support system (AId-system), and a group that used neither of the diagnosis support systems. The results show that the group that used the FTd-system completed the task 15% faster than the group that used the AId-system. There was no significant difference in the workload between groups. Further analysis using the NGOMSL model implied that the difference in time to complete was probably due to the difference in system interfaces. In summary, the experimental results and further analysis imply that adopting the new diagnosis support system may improve maintenance productivity by reducing the number of diagnosis attempts without burdening technicians with new workloads. Estimates indicate that the maintenance time and the cognitive load can be reduced by 8.4 s and 15% if only two options are shown in the user interface.

Investigating effect of standardized total body skin examination using sequence-networks.

This study employs sequence-network analysis to investigate the influence of instructing a standardized procedure on total-body skin examination (TBSE) performance. A between-subjects study was conducted with thirty-one participants comprising medical students and attending physicians. Among these participants, fifteen were randomly assigned to the uninstructed group and sixteen to the instructed group. The participants' gaze and field of view were recorded using eye tracking glasses while performing TBSE on a male and a female standardized patient. The recordings were then transcribed to depict the examination process. The instructed group missed significantly fewer body parts (p = 0.045) and had higher time efficiency (p = 0.007) while examining the female patient, but no significant difference was observed for the male patient examination. Furthermore, the examination sequences of the instructed group contained lesser variability than the uninstructed group. Hence, implementing a standard optimal procedure to perform TBSE could minimize the likelihood of missing body parts, increase examination efficiency, and improve performance consistency. This study demonstrated the potential of sequence-network analysis to study human performance in sequential tasks.

Investigating the effects of age, task load, task complexity, and input device on monitoring performance for smart manufacturing in the oil refining industry.

Human beings play an important role in a smart manufacturing economy. In this study, we explored the effects of age, task load, task complexity, and input device on abnormal event detection performance in an oil refinery control room task. Thirty participants were recruited to complete a process plant monitoring task in which they were asked to continuously monitor the gauge states, and immediately detect and solve the abnormal events. Participants' accuracy in detecting abnormal states was recorded and analysed during the task. We found that the complexity factor affected accuracy significantly, and younger adults had significantly higher accuracy than older adults in high task load trials. No significant effect was found for the input device factor. These findings suggest that age, task load, and task complexity should be taken into consideration when designing tools to improve older operators' performance.Practitioner summary: The smart manufacturing economy elicits higher requirements for older operators in oil refinery monitoring tasks. Under high task load, older adults had lower accuracy in detecting abnormal conditions than younger adults. The task complexity affected participants' accuracy in detecting abnormal states.

Effects of Desk Pedaling Work Rate on Concurrent Work Performance among Physically Inactive Adults: A Randomized Experiment.

PURPOSE: Under-desk pedaling devices could help reduce health risks associated with the global decline in work-related energy expenditure. However, the optimal pedaling work rate to facilitate concurrent work performance among physically inactive adults is unclear. We examined the effects of two light-intensity pedaling work rates on physically inactive adults' work performance. METHODS: We recruited equal numbers of older (45-65 yr) versus younger (20-44 yr), male versus female, and overweight/obese (body mass index [BMI], 25-35 kg·m -2 ) versus normal weight (BMI, 18.5-24.9 kg·m -2 ) participants. Using a Graeco-Latin square design, participants ( n = 96) completed a laboratory experiment to evaluate the effects of using an under-desk pedaling device at two seated light-intensity work rates (17 and 25 W), relative to a seated nonpedaling condition on objectively measured typing, reading, logical reasoning, and phone task performance. Ergonomic comfort under each pedaling work rate was also assessed. Equivalence tests were used to compare work performance under the pedaling versus nonpedaling conditions. RESULTS: Treatment fidelity to the 17- and 25-W pedaling work rates exceeded 95%. Mean work performance scores for each pedaling and nonpedaling condition were equivalent under alpha = 0.025. Age, sex, and BMI did not significantly moderate the effect of pedaling on work performance. Participants reported greater ergonomic comfort while completing work tasks at the 17-W relative to the 25-W work rate. CONCLUSIONS: Physically inactive adults obtained similar work performance scores under the 17- and 25-W pedaling and the nonpedaling conditions, suggesting that either pedaling work rate could help reduce health risks of sedentary work time. The 17-W work rate yielded greater ergonomic comfort and may be an appropriate starting point for introducing diverse inactive workers to under-desk pedaling.

Using eye movements to evaluate the effectiveness of the situation awareness rating technique scale in measuring situation awareness for smart manufacturing.

Physiological indicators, including eye-tracking measures, may provide insight into human internal states in many domains, such as smart manufacturing. The Situation Awareness Rating Technique (SART) scale has been criticised for not assessing situation awareness (SA) accurately. In this study, we investigated the precision of the SART scale for assessing SA by comparing the scores to eye movement data. Thirty participants were recruited to complete a process plant monitoring task. Participants' eye movements and SART scores were recorded and analysed. Our results moderately supported the idea that the SART scale did not accurately measure SA. We found that four dimensions in the SART scale need to be revised to reflect real SA, which may partially solve the divergence between objective and subjective SA measurements. Moreover, these findings provided solutions for designing a revised SART scale to measure the internal states of operators for smart manufacturing. Practitioner summary: Situation awareness (SA) is a critical component of decision-making and performance for smart manufacturing. The present study examines the relationships among eye movement, the SART scale, and SA for smart manufacturing in a refinery control room.

Validating an abnormal situation prediction model for smart manufacturing in the oil refining industry.

Human beings play an important role in a smart manufacturing economy. The repetitive and cognitive demanding task operations of smart manufacturing require the development of system models for measuring and predicting human performance, including oil refinery monitoring tasks. The main objective of this research was to validate the generalizability of a mathematical model for the prediction of refinery operators' detection of abnormal events. Moreover, we examined operators' visual behaviors in response to abnormal situations at different ages and with different task loads, task complexities, and input devices. We found that participants had lower mean fixation durations, total fixation numbers, and fixation/saccade ratios when they were in the condition of a touchscreen device. Moreover, we found that older adults had higher mean saccade durations and saccade amplitudes when they were in the condition of a touchscreen device. Finally, the statistical model borrowed from our prior paper was found to be generalizable to different task loads and age groups for the prediction of operators' detection of abnormal events. Our results showed that visual behaviors can indicate specific internal states of participants, including their cognitive workload, attention, and situation awareness in a real-time manner. The findings provide additional support for the value of using visual behavior to predict responsiveness of oil refinery operators and for future applications of smart manufacturing monitoring systems.

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.

An evaluation of touchscreen versus keyboard/mouse interaction for large screen process control displays.

The objectives of this study were to test the effect of interaction device on performance in a process control task (managing a tank farm). The study compared the following two conditions: a) 4K-resolution 55" screen with a 21" touchscreen versus b) 4K-resolution 55″ screen with keyboard/mouse. The touchscreen acted both as an interaction device for data entry and navigation and as an additional source of information. A within-subject experiment was conducted among 20 college engineering students. A primary task of preventing tanks from overfilling as well as a secondary task of manual logging with situation awareness questions were designed for the study. Primary Task performance (including tank level at discharge, number of tank discharged and performance score), Secondary Task Performance (including Tank log count, performance score), system interaction times, subjective workload, situation awareness questionnaire, user experience survey regarding usability and condition comparison were used as the measures. Parametric data resulted in two metrics statistically different means between the two conditions: The 4K-keyboard condition resulted in faster Detection + Navigation time compared to the 4K-touchscreen condition, by about 2 s, while participants within the 4K-touchscreen condition were about 2 s faster in data entry than in the 4K-keyboard condition. No significant results were found for: performance on the secondary task, situation awareness, and workload. Additionally, no clear significant differences were found in the non-parametric data analysis. However, participants showed a slight preference for the 4K-touchscreen condition compared to the 4K-keyboard condition in subjective responses in comparing the conditions. Introducing the touchscreen as an additional/alternative input device showed to have an effect in interaction times, which suggests that proper design considerations need to be made. While having values shown on the interaction device provides value, a potential issue of visual distraction exists when having an additional visual display. The allocation of visual attention between primary displays and the touchscreen should be further investigated.

Investigating information-processing performance of different command team structures in the NATO Problem Space.

The structure of command teams is a significant factor on their communications and ability to process, and act upon, information. The NATO Problem Space was used in this study to represent three of the main dimensions in the battle-space environment: familiarity, rate of change, and strength of information position. Results show that the five common team structures (chain, Y, circle, wheel and all-connected) did not generally perform as predicted in team literature. Findings suggest that under dynamic and highly variable conditions, high levels of synchronisation and trust should be present. On the other hand, synchronisation and trust are less important in hierarchical, highly centralised structures, because team members are more willing to accept the authority of a single leader and this tight control ensures that these teams can perform well as long as the Problem Space is familiar, information is explicit and the environment does not change. Practitioner Summary: Some types of team structures are better suited to particular constraints of the battle-space than others. This research has shown that the much touted all-connected structure is often the worst performing structure and that the traditional hierarchy of command and control has much merit in the digital information age.

Using Signal Detection Theory and Time Window-based Human-In-The-Loop simulation as a tool for assessing the effectiveness of different qualitative shapes in continuous monitoring tasks.

This paper provides a case study of Signal Detection Theory (SDT) as applied to a continuous monitoring dual-task environment. Specifically, SDT was used to evaluate the independent contributions of sensitivity and bias to different qualitative gauges used in process control. To assess detection performance in monitoring the gauges, we developed a Time Window-based Human-In-The-Loop (TWHITL) simulation bed. Through this test bed, we were able to generate a display similar to those monitored by console operators in oil and gas refinery plants. By using SDT and TWHITL, we evaluated the sensitivity, operator bias, and response time of flow, level, pressure, and temperature gauge shapes developed by Abnormal Situation Management(®) (ASM(®)) Consortium (www.asmconsortium.org). Our findings suggest that display density influences the effectiveness of participants in detecting abnormal shapes. Furthermore, results suggest that some shapes elicit better detection performance than others.

Analyses of team performance in a dynamic task environment.

Teamwork, a central component of team research, is not readily observable and must be inferred from the manner in which teams operate. Of particular interest is the measurement and evaluation of teamwork. The goal of this paper is to explore the assessment of team data using a temporal accuracy measure called the Relative Accuracy Index (RAI). For the statistical analysis, the generalized mixed model was applied. This model is applicable for binomial data and takes into account the correlation structure within team members. We describe the statistical procedure in detail, aiming to guide researchers who encounter similar problems. Using our statistical analysis, we found that participants whose training focused on coordination activities outperformed those whose training did not. Moreover, we found that workload stress accentuates the difference.