Room Operators Research Articles

An ergonomic focus evaluation of work-related musculoskeletal disorders amongst operators in the UAE network control centres

Work-related musculoskeletal disorders (WMSDs) have rapidly increased during the last decade, but only a few descriptive surveys have been conducted in the United Arab Emirates (UAE). This study investigated the prevalence of WMSDs and analysed their ergonomic risks amongst operators in the network control rooms across two government organisations, X and Y, in the UAE. Essential data were collected by the Nordic Musculoskeletal Questionnaire (NMQ) and the Maastricht Upper Extremity Questionnaire (MUEQ) from online surveys and direct observations based on the Rapid Office Strain Assessment (ROSA) and the Rapid Upper Limb Assessment (RULA) form and ergonomic measurements for the working environments, respectively. Fifty-three and eighteen operators participated from Organisations X and Y. This study found a high presence of WMSDs in both organisations over the past 12 months. In Organisation X, individual, work-related physical and psychosocial risk factors of high BMI, educational level, morning work shift, high job duration, lack of exercise habit, awkward body posture, high job demand, low job control, and low work social support were associated with WMSDs in different body areas (p < 0.05). In Organisation Y, older age, high BMI, high job duration, lack of exercise habits, unergonomic workstations, awkward body posture, low break time, high job demand, and stress level were associated with WMSDs in different body areas (p < 0.05). The control room operators' most affected body areas were the back, eyes, and neck. Several efficient ergonomic intervention ideas were explored to lessen the detrimental effects of WMSDs and preclude the development of WMSDs amongst the control centre operators.

A video processing and machine learning based method for evaluating safety-critical operator engagement in a motorway control room

In safety-critical automatic systems, safety can be compromised if operators lack engagement. Effective detection of undesirable engagement states can inform the design of interventions for enhancing engagement. However, the existing engagement measurement methods suffer from several limitations which damage their effectiveness in the work environment. A novel engagement evaluation methodology, which adopts Artificial Intelligence (AI) technologies, has been proposed. It was developed using motorway control room operators as subjects. Openpose and Open Source Computer Vision Library (OpenCV) were used to estimate the body postures of operators, then a Support Vector Machine (SVM) was utilised to build the engagement evaluation model based on discrete states of operator engagement. The average accuracy of the evaluation results reached 0.89 and the weighted average precision, recall, and F1-score were all above 0.84. This study emphasises the importance of specific data labelling when measuring typical engagement states, forming the basis for potential control room improvements. Practitioner summary: This study demonstrates an automatic, real-time, objective, and relatively unobtrusive method for measuring dynamic operator engagement states. Computer vision technologies were used to estimate body posture, then machine learning (ML) was utilised to build the engagement evaluation model. The overall evaluation shows the effectiveness of this framework. Abbreviations: AI: Artificial Intelligence; OpenCV: Open Source Computer Vision Library; SVM: Support Vector Machine; UWES: Utrecht Work Engagement Scale; ISA Engagement Scale: Intellectual, Social, Affective Engagement Scale; DSSQ: Dundee Stress State Questionnaire; SSSQ: Short Stress State Questionnaire; EEG: electroencephalography; ECG: Electrocardiography; VMOE: Video-based Measurement for Operator Engagement; CMU: Carnegie Mellon University; CNN: Convolutional Neural Network; 2D: two dimensional; ML: Machine learning.

Human-machine interface (HMI) assessment in the nuclear control room operations using the modified machine learning (ML) algorithm

Human-machine interface (HMI) assessment in the nuclear control room operations using the modified machine learning (ML) algorithm

Prediction and Assessment of Human Errors in Control Room of a Steam Power Plant by SHERPA Method in 2021

Background: Human errors are considered as important factor in occurrence of accidents that can leading to death, injuries and damages. The power plant industry as the most important infrastructure industry plays a significant role in industrial infrastructure. Objectives: The present study was carried out with the aim of prediction and assessment of human errors in a control room of a steam power plant by systematic approach to error prediction and reduction (SHERPA) method. Methods: This descriptive – cross sectional study was conducted in a control room of steam power plant. In this research human errors were identified and analyzed by hierarchical task analysis (HTA) and SHERPA methods. Results: In total 85 errors were identificated that 56 (65.1%) action errors, 24 (27.9%) checking errors, 1 (1.2%) retrieval errors, 2 (2.32%) communication errors and 3 (3.48%) were related to selection errors. Results also indicated that already 51% of risk level due to identification errors in unacceptable and undesirable level. Conclusions: The most important identificated errors in this research were related to action errors. In order to minimize of these errors and limitation of their consequence, we can use checklist and proper instructions according to work and educate control room operators.

Proactive monitoring and operator discretion: A systematic social observation of CCTV control room operations

Proactive monitoring and operator discretion: A systematic social observation of CCTV control room operations

Proactive monitoring and operator discretion: A systematic social observation of CCTV control room operations

BackgroundResearch on police discretion indicates a host of legal and extra-legal factors can impact officer decision making. The emergence of video surveillance technologies has made certain police interactions with the public more remote in nature. Decisions to enforce the law, consequently, now commonly begin outside of the context of face-to-face police/citizen interactions. This study explores police decision-making in the context of proactive video surveillance operations. MethodsData were generated from a systematic social observation of CCTV operator activity during the Newark CCTV Directed Patrol Experiment. Regression models tested how covariates affect the duration of CCTV operator targeted surveillances and CCTV operator decisions to report incidents providing reasonable suspicion and/or probable cause for a police response. ResultsA range of model covariates significantly influenced CCTV operator decision making, inclusive of surveillance targets identified as prior suspects, the CCTV site being within a commercial area, visible obstructions impeding camera view, CCTV operator rank, and CCTV operator gender. ConclusionsFindings suggest that organizational culture, CCTV operator characteristics, and land usage of target areas may foster differential surveillance behavior across CCTV operators. As remote strategies for policing continue to expand internationally, the identification of factors that impact discretionary practices is critical.

Whereables? Examining Personal Technology Adoption in Contemporary Control Rooms

Early work in wearables research has often proposed visions in which wearable computers are introduced to support human operators in critical environments such as control rooms, ship bridges, cockpits, or operating rooms. Wearable assistants could for instance present critical task-relevant information to users regardless of their location, help in avoiding procedural errors, or enhance collaborations between multiple operators. In reality, however, such visions have not galvanized: What happened? And could operators’ attitudes and misgivings toward wearables be responsible? The rise of personal wearables in the past years has led to fitness trackers, smartwatches, and other consumer devices being worn by a larger audience, likely also among control room operators. We report in this article on findings from a series of onsite interviews and workshops with professional control room operators to get an insight in their attitude toward wearables, and opinions and current views on the use and adoption of wearable and pervasive technologies in their work environment.

Emotionally Loaded Visual Stimuli to Alter Brain Arousal: A Flicker Fusion Study

Background: Human brain performance and arousal are still challenging and critical, especially in environments such as power plants. Since different emotions are common in daily work life and have inevitable effects on cognitive performance, it is important to evaluate whether emotional interventions can alter brain arousal. Poor cognitive performance in control room operators (CROs) can lead to mental fatigue and affect their cognitive emotion regulation. To address this issue, flicker fusion frequency (FFF) was employed as a simple and reproducible surrogate index for mental fatigue. Objectives: This study aimed to investigate whether emotionally loaded visual stimuli can alter brain arousal (brain fatigue) or is associated with cognitive emotion regulation (CER) ability. Methods: Flicker fusion frequency was assessed by RT-961, and the International Affective Picture System (IAPS) was adopted as the picture database of stimuli. Additionally, the Cognitive Emotion Regulation Questionnaire (CERQ) was used to determine the participants’ cognitive emotion CER ability. Twenty volunteer CROs from Fars Combined Cycle Power Plant participated in this study. After completing the CERQ, they were assessed at 2 different time points (ie, before and after presenting emotional stimuli). Flicker fusion frequency was assessed 20 times at each round, and the average frequency was recorded. Emotionally loaded images were considered as stimuli. The stimuli sets were classified based on their arousal levels and valences, yet they were presented in random order. Subjects were exposed to each image for 5 seconds (30 minutes in total). Results: The participants’ mean age was 39.55 ± 7.02 years. The first and second FFFs were 42.15 ± 3.90 and 41.96 ± 3.98 in the appropriate group and 42.82 ± 3.59 and 42.26 ± 4.07 in the inappropriate group. Based on the statistical tests, there were no significant relationships between the measurements (P &gt; 0.05). Conclusions: Control room operators may positively maintain their brain arousal during specific emotional stimuli when the intervention lasts less than 30 minutes. Considering the prolonged working hours in such industries (roughly over 8 hours a day) and the importance of cognitive aptitude in preventing work-related errors, we propose this line of research to gain momentum.

Establishment of Control Room Habitability Analysis Methodology Postulating the Event of Pressurized Tank/System of Hazardous Gas Release

A new methodology using a free turbulent flow model to evaluate control room habitability is developed, and the theoretical model can be applied to the postulated event of rupture or line break of the on-site hazardous gas pressurized tank/system. Based on the conservation of mass law and momentum equations, correlations of the control room ventilation hazardous gas intake concentration and the control room buildup toxic concentration were established and can be used to evaluate control room habitability. Compared with current methodology widely used in the industry (introduced by NUREG-0570), the developed theoretical analysis methodology is applicable to events occurring without any constraint on the distance between the site of toxic gas release and the inlet of the control room fresh air intake or the control room. With a given amount of hazardous gas release source, the analysis results indicate that maximum control room toxic gas concentration will depend on the mass release rate or its break size, the density of the hazardous gas, and the distance between the site of the toxic release and the control room fresh air intake. The limiting case of the control room habitability analysis will occur at the break size resulting in the highest control room toxic gas concentration. The control room toxic gas transient concentration at the limiting break size can be predicted by the model and compared with its acceptance criteria of short-term exposure limit and time-weighted average to evaluate the control room habitability whether protection actions of the control room operators are required to prevent incapacitation or death due to the postulated events of toxic gas release.

Development and validation of a task load index for process control room operators (PCRO-TLX)

Process control room operators (PCRO) perform a range of complex cognitive safety-critical tasks. The aim of this exploratory sequential mixed methods study was to develop an occupation specific tool to measure the task load of PCRO using NASA Task Load Index (TLX) methodology. Participants were 30 human factors experts and 146 PCRO at two refinery complexes in Iran. Dimensions were developed via a cognitive task analysis, a research review, and three expert panels. Six dimensions were identified: perceptual demand, performance, mental demand, time pressure, effort, and stress. Data from 120 PCRO confirmed that the developed PCRO-TLX has acceptable psychometric properties, and a comparison with the NASA-TLX confirmed that perceptual, not physical, demand was relevant for measuring workload in PCRO. There was a positive convergence of scores of the Subjective Workload Assessment Technique and the PCRO-TLX. This reliable tool (α = 0.83) is recommended for risk assessing the task load of PCRO. Practitioner summary: There are benefits of having a specific tool to measure task load in safety critical roles. Thus, we developed and validated an easy-to-use targeted tool, the PCRO-TLX, for process control room operatives. Timely use and response will assure optimal production alongside health and safety in an organisation. Abbreviations: PCRO: process control room operator; TLX: task load index; PCRO-TLX: process control room operator task load index; NASA-TLX: National Aeronautics and Space Administration task load index; SWAT: subjective workload assessment technique; DALI: driving activity load index; SURG-TLX: surgery task load index; SIM-TLX: virtual reality simulation task load index; VACP: visual, auditory, cognitive and psychomotor; CVI: content validity index; CVR: content validity ratio; RMSEA: root mean square of error approximation; GFI: goodness of fit index; AGFI: adjusted goodness of fit index; CFI: comparative fit index; ANOVA: analysis of variance; CI: confidence interval

ACT-R based human digital twin to enhance operators' performance in process industries.

To ensure safe and efficient operation, operators in process industries have to make timely decisions based on time-varying information. A holistic assessment of operators' performance is, therefore, challenging. Current approaches to operator performance assessment are subjective and ignore operators' cognitive behavior. In addition, these cannot be used to predict operators' expected responses during novel situations that may arise during plant operations. The present study seeks to develop a human digital twin (HDT) that can simulate a control room operator's behavior, even during various abnormal situations. The HDT has been developed using the ACT-R (Adaptive Control of Thought-Rational) cognitive architecture. It mimics a human operator as they monitor the process and intervene during abnormal situations. We conducted 426 trials to test the HDT's ability to handle disturbance rejection tasks. In these simulations, we varied the reward and penalty parameters to provide feedback to the HDT. We validated the HDT using the eye gaze behavior of 10 human subjects who completed 110 similar disturbance rejection tasks as that of the HDT. The results indicate that the HDT exhibits similar gaze behaviors as the human subjects, even when dealing with abnormal situations. These indicate that the HDT's cognitive capabilities are comparable to those of human operators. As possible applications, the proposed HDT can be used to generate a large database of human behavior during abnormalities which can then be used to spot and rectify flaws in novice operator's mental models. Additionally, the HDT can also enhance operators' decision-making during real-time operation.

Designing the Layout of Fibreglass Production Facilities Using the ARC (Activity Relationship Chart) and ARD (Activity Relationship Diagram) Methods at PT. XYZ

PT. XYZ is a plastic material and product manufacturing company founded in Riau in 1997. This company produces fibreglass (FRP) goods and accepts design requests according to consumer demand. In addition, PT. XYZ also has water tanks made of Polyethylene (HDPE) and stainless steel. In practice, some inefficiencies and inefficiencies make it difficult for operators to find tools such as grinders. This study uses the ARC (Activity Relationship Chart) and ARD (Activity Relationship Diagram) and redesigns the layout of the fibreglass production facility. The results of the study show changes and rotations in the 90º room operator, the transfer of measurements and cuts close to the base material mixture workstation located in the fibreglass production division room, and the addition of 4 workstations because it utilizes an empty floor. Keywords: ARC, ARD, Fiberglass, Layout

‘Sadly, my group was “hanged” at the end of the evening’: the politics of deservingness and representation at carceral-themed escape rooms

ABSTRACT Escape rooms are a popular new form of leisure and amusement globally, including in North American cities. Based on a thematic and discourse analysis of online content, we examine ten carceral-themed escape room operations in the United States and Canada. Drawing on theories of cultural power and neoliberalism, we analyze the messages conveyed by site operators about the deservingness of life, freedom and justice for imprisoned people. Contributing to literature on dark tourism and dark leisure, we also explore how the ideas of a ‘crime complex’ and ‘safe contact’ are reflected in representations of penality attached to escape room games. We argue that such depictions misrepresent the realities of carceral experience, producing understandings of carcerality and deservingness that foster punitive views among participants.

Estimating the Duration of Motorway Incidents using Machine Learning Approaches

Motorway incidents are frequent & varied in nature. The causes & severity of incidents might vary, ranging from road debris to severe traffic collisions. Incident management on motorways is critical for both driver safety & road network operation. The expected duration of an incident is a key parameter in the decision-making process for control room operators. This paper presents a study which compares the ability of different machine learning algorithms to estimate the duration of motorway incidents on Ireland's M50 motorway, using an extensive historical incident database. Results show that the support vector machine has the best performance in most cases, but a different method may need to be used to improve accuracy in some situations. Results highlight difficulties in accurately forecasting incident durations in real time & recommendations are made for improving prediction accuracy.

Ensuring Utility Workers’ Health and Safety: Keeping the Lights On and Protecting the Workforce

The sudden emergence and spread of COVID-19 brought many challenges affecting everyday life. Many companies promptly shifted to remote work to reduce the potential for transmission and maintain an effective workforce. However, essential workers—those in industries that are essential to ensure the continuity of critical functions—were not able to switch to working remotely. Energy sector workers who are unable to work remotely are considered essential workers along with workers in health care, transportation and logistics, and government operations. Some essential utility functions, such as control room operations and in-home visits, need to continue to be conducted in person. The pandemic underscored the importance of a reliable utility workforce and thus the importance of adequate pandemic preparedness.

Ergonomics Evaluation of Control Room Operators in Selected Oil and Gas Installations in Delta and Rivers States

Ergonomics Evaluation of Control Room Operators in Selected Oil and Gas Installations in Delta and Rivers States

APPLICATION SOFTWARE DEVELOPMENT FOR THE GEOTECHNICAL MONITORING SYSTEM OF GAS PIPELINES

The article considers a scientifically based approach that ensures trouble-free operation of large-scale distributed production facilities using a set of measures, one of the components of which is an automated monitoring system. A procedure for automated collection of a large array of data from the entire object in a relatively short period of time with automatic interpretation and visualization of information in forms convenient for decision-making is proposed. It is shown that one of the most important indicators of the functioning of pipeline transport is the level of the stress-strain state of the metal, which depends on internal and external factors – the parameters of the transportation process, the state of the pipeline metal, ground movement and other meteorological and technological factors. At the same time, the integration of the monitoring system with automated systems for planning and carrying out routine maintenance and repair work, as well as closer integration with automated process control systems and dispatch control systems, is very significant. As a result of the creation of such a system of integrated monitoring of the gas pipeline, data exchange speeds are increased, their analytical processing is provided, as well as rapid visualization on the control room operator's workstation. The implementation of these procedures for automatic interpretation and visual representation of large volumes of incoming information contributes to the support of operational decision-making during the operation of oil and gas pipelines in adverse environmental conditions.

“Context-Dependent Cognitive Workload Monitoring using Pupillometry for Control Room Operators to Prevent Overload”

Occupational Application Modernization of process plants has replaced traditional machine control with sophisticated computerized control, with the work required of control room operators changing from predominantly physical to cognitive. As a result, excessive cognitive workload during an abnormal condition is not an uncommon situation. Almost 70% of accidents in process industries are the result of human error, which is largely modulated by high cognitive workload. A context-dependent methodology using pupillometry was adopted in this study for workload assessment. We found that workload has a significant effect on task performance and subsequent success in handling an abnormal condition. Incorporating contextual information along with pupillometry-based measures was useful to explore the dynamics of variations in workload in depth. In addition, the proposed methodology is a more reliable method for a dynamic environment in which the situation evolves with operator interactions with the process. Technical : Background: Operator workload monitoring has become an important aspect of system engineering due to ever increasing cognitive demands in the control room. Higher cognitive workload, beyond capability, is directly associated with human error in plant operations. Even a small increase in workload during peak demand may result in human error, which can endanger the safety of a process plant. Purpose: Subjective methods are of limited use due to the requirement for near real-time evaluation of cognitive workload. Applications such as process plant control room require the operator to reiterate and re-represent the situation based on the contextual cues from environment. Hence, our objective was to develop and test a methodology that incorporates contextual information in workload measurement using pupillometry. Method: Participants (n = 44) performed simulated process control tasks. Pupil size was recorded using an eye-tracking device. Recorded pupil size was analyzed based on a methodology that incorporates contextual information from the human-machine interface. Events that present new information about the current state of the process were categorized as critical events. Pupil size variation was adopted to provide an estimate of cognitive workload between consecutive critical events. Results: Cognitive workload was associated with process behavior and operator actions. An increase in cognitive workload for specific events was observed when participant actions deteriorated process conditions. We also observed that overall task performance was associated with the frequency of certain events and corresponding variations in pupillary behavior. Conclusion: Incorporating contextual information provides more detailed insights into the dynamics of variations in cognitive workload. The mental representation of a current situation may vary depending on expertise level. The proposed methodology assesses such dynamic mental representations in the form of frequency of critical events and corresponding changes in the cognitive workload that ultimately determines the likelihood of an operator successfully completing a task.

Chase for lucky numbers and take positive actions

Number 8 is regarded as a lucky number in Chinese culture and is preferred over other numbers, especially in financial and retail market. To explore the impact of lucky numbers in room prices, we collect data from a room-sharing platform (Mayi) in China. The results indicate that a room with the lucky number in its price receives more bookings and higher customer ratings than other rooms without that price feature. Moreover, a host setting price with the lucky number 8 will receive more positive ratings. This study contributes to the existing literature and provides practical insights for room hosts and operators in room-sharing platforms.

Investigating Cognitive Load in Energy Network Control Rooms: Recommendations for Future Designs.

This study analyzed and explored the cognitive load of Australian energy market operators managing one of the longest inter-connected electrical networks in the world. Each operator uses a workstation with seven screens in an active control room environment, with a large coordination screen to show information and enable collaboration between different control centers. Cognitive load was assessed during both training scenarios and regular control room operations via the integration of subjective and physiological measures. Eye-tracking glasses were also used to analyze the operators gaze behavior. Our results indicate that different events (normal or unexpected), different participants for the same session, and different periods of one session all have varying degrees of cognitive load. The system design was observed to be inefficient in some situations and to have an adverse affect on cognitive load. In critical situations for instance, operator collaboration was high and the coordination screen was used heavily when collaborating between two control centers, yet integration with the system could be improved. Eye tracking data analysis showed that the layout of applications across the seven screens was not optimal for many tasks. Improved layout strategies, potential combination of applications, redesigning of certain applications, and linked views are all recommended for further exploration in addition to improved integration of procedures and linking alarms to visual cues.