جستجوی مقالات مرتبط با کلیدواژه « control room » در نشریات گروه « پزشکی »

Human errors cause major accidents in many industries, including railway industries. Several factors also play a role in the occurrence of such errors. The quality of people's sleep may affect their probability of human error. This study was conducted to investigate the effect of sleep quality on the probability of human error in employees of railway traffic control rooms.

Methods and Materials:

 This cross-sectional descriptive-analytical study was conducted in 2021 with 115 male employees working in railway traffic controls. In this survey, each participant completed the General Health Questionnaire (GHQ), the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), and the Self-report of Human Error Probability Questionnaire (SHEPQ). Data were analyzed using Spearman and Independent T-Test.

According to the results of the study, the mean age ± (Standard Deviation (SD)) and work experience ± (SD) of the participants were 36.57 ± (5.22) and 10.09 ± (5.66), respectively. 36.5%, 49.6%, 18% and, 21.7% of participants had 23 ≤GHQ≤ 40, PSQI> 5, ESS≥13 and SHEPQ> 50, respectively. Also, there is a significant relationship between PSQIScore and ESSScore, with the probability of human error (P<0.001, Correlation Coefficient (CC) = 0.399, P<0.001, CC = 0.412, respectively). In addition, there was a significant relationship between the mean error scores in the sleep quality subgroups (P<0.001).

According to the findings of this study, poor sleep quality is an important factor in the incidence of human error.

Despite the advancement of control mechanisms and automation in industrial processes, there is still the chance of human error and accidents. As a result, this study was conducted in the control room of a cement company to identify human errors and propose control methods to reduce them using the Systematic Human Error Reduction and Prediction Approach (SHERPA).

The data for this cross-sectional descriptive study were gathered through task observation, reviewing technical documentation, and interviews. For the selected tasks, a hierarchical task analysis (HTA) was done, and the human errors of each critical task were assessed using SHERPA. Finally, control methods for reducing the risk of identified errors were proposed.

In this study, 9 main tasks and 103 sub-tasks were assigned for the control room operators. The results of the SHERPA showed that out of 204 identified human errors, 45.1% were functional, 35.3% retrieval, 11.3% communication, 44% checking, and 9.3% were selection errors. C2 (55 cases), C3 (32 cases), and 2D (30 cases) had the highest risk levels, whereas 1E (1 case), 1B (2 cases), and 4C (3 cases) had the lowest.

The most common errors were those relating to performance and retrieval. Operator training, monitoring systems, smart control system utilization, effective instructions, and suitable control measures can help to significantly reduce the number of human errors that result in accidents.

 In many workplaces today, the incidence of human error can lead to catastrophic accidents in which human error is the main cause of accidents. Due to the vital role of the control room in guiding and controlling various sites of the pipe industry, especially the outer coating sector, the incidence of any error can lead to human accidents, damage to machinery, and interruption in production. This study aimed to identify and evaluate human error by Human Error Calculator (HEC) method in the epoxy control room of a pipe mill company. 

 In the present descriptive cross-sectional study, the HEC method was used to identify and evaluate human errors. The HEC technique is provided by Risk Map Company, in which the probability of human error is based on five factors affecting the occurrence of human error, including a degree of urgency, complexity, importance, degree of individual skill, and task repetition, using a disk-shaped tool called Risk Disk is determined through direct observation, available instructions and interview with the head of the mentioned unit.

 According to the results of this study, out of 11 identified tasks, five job tasks with a risk number of 70% have a high probability of human error, four job tasks with a risk number of 50%, and one job task with a number There is a 40% risk of moderate human error, And a job task with a 20% risk number has an increased chance of human error.

 The results of the present study showed that the HEC method is easy to use and is a simple and useful tool for professionals to calculate the probability of human error. In addition, HEC is a practical, effective and beneficial method for managers to reduce human error.

 This paper aims to explore the main effect of night shift rotation speed on the pattern of melatonin secretion and the sleepiness, among control room operators (CORs) in a petrochemical industry

 In this study, 60 CORs operators within two different patterns, including 7 nights and 3 nights shift works were selected from a petrochemical industry to investigate the influence of rotation speed on their melatonin secretion and the sleepiness pattern. Thus, melatonin was sampled from saliva, and the sleepiness and sleep quality were assessed using Karolinska Sleepiness Scale (KSS) index. Data analysis was carried out using spss18, Chi square, t-test, and GLM model.

 Melatonin values and their general changes during shift were noticeably different in two proposed patterns (P <0.05). The sleepiness index was significantly different only at 3:00 in both patterns, whereas the interaction of light and caffeine on both melatonin changes and sleepiness was not significant (P <0.05). Moreover, a significant difference was observed between the process of melatonin changes and sleepiness in the two studied patterns (P <0.05).

 Adopting slower shift schedules rotations would be more appropriate, from the viewpoints of the importance of alertness and performance for human error prevention, among people working in serious worksites such as control rooms.

Human errors and consequently the occurrence of adverse accidents in industries is a possible mishap. The control room is the main center of an industrial system, and any errors during the tasks of the operators can have adverse consequences with irreparable damage. Therefore, this study was conducted to identify and evaluate the human error in the control room of one of a cement manufacturing companies using a cognitive reliability error analysis method to improve the safety status as a necessity.

This is a qualitative and cross-sectional study that was conducted using the cognitive reliability error analysis method in a control room of a cement manufacturing industry. After analyzing the tasks using hierarchical task analysis, the method worksheets were completed through observation; interviews with the
operators, the production manager and shift engineer, and analyzing the related documents of the company. Then, user probabilistic controls and cognitive probability errors were determined using the basic and extended cognitive reliability error analysis method for various tasks.

In this study, 7 tasks of control room operators were analyzed using hierarchical task analysis. The findings of the basic method indicated that the type of control style for tasks of action, control room operator, and shift engineer was opportunistic control and the task of the production manager was tactical control. Based on the results of the extended method, execution error (42.74%), interpretation error (23%), planning error (20.61%), and observation error (13.74%) were obtained from the total number of detected errors.

The positive features of the studied method for maximizing the likelihood of human performance along with the likelihood of recovery of human errors along with minimizing the risk of human error were quite evident in this study. Hence this method is recommended for the determination of the probability of cognitive errors in the control room of other industries

Nowadays, human error is one of the main causes of incidents in the industry. One of the vital characteristics of modern industries is that the precise control of key parts of the process is performed by operators from central control rooms, so an error by the control room staff can be disastrous. The present study is aimed at identifying and evaluating human errors in the control room of the petrochemical industry.   This is a descriptive-analytic case study that was conducted in a control room of the petrochemical industry. In this research, firstly by using hierarchical task analysis (HTA), the tasks in the control room were identified and analyzed. Then, using the extended CREAM method, possible human errors were identified, their cognitive category was determined, and their probabilities were calculated using a new approach based on BN. The results of the study showed that the most prevalent control modes for the Boardman and the senior board man were strategic and scrambled modes with error probabilities of 0.136 and 0.171, respectively. According to the results obtained in the modeling section, BN can be proposed as an approach with high processing accuracy and also high accuracy in modeling human errors and problems with high input parameters affecting the output parameter.

Control room is one of the most important working environments that require optimal performance of individuals to minimize errors. Lighting is one of the environmental factors affecting the operation of the control room operators. Providing optimal lighting in the control room is very important. The purpose of this study was to determine the effect of light on workload, sleepiness, eye fatigue, and satisfaction of individuals from light conditions. Material and Method: This was an interventional study conducted in a control room of a power plant. Intervention in the control room lighting was performed with two lighting systems including fluorescent lamps (4000 Kelvin, 200 lux) and LED lamps (4,000 Kelvin, 400 lux). Sixteen operators were evaluated under the two lighting systems in terms of workload, sleepiness, eye fatigue and satisfaction of individuals from light conditions. According to the results, eye fatigue significantly decreased after intervention (p (0.004>. Also, the higher light intensity, significantly decreased the level of sleepiness (p <0.001). In the study of workload, the amount of mental workload (p <0.001) and effort (p <0.03) decreased significantly, after intervention and the increase in the intensity of light; but physical demand, temporal demand, performance and frustration had no significant difference with the results before intervention. In general, a combination of fluorescent and LED lighting systems, with 400 lux intensity, can provide optimal functional and mental conditions for control room operators. The illumination intensity of 400 lux in terms of workload, sleepiness, eye fatigue and the degree of satisfaction of individuals from light conditions provides a much better environmental condition than 200 lux.

One of the important characteristic features of modern industries is the precise control of key components of the industry through central control rooms. Thus, committing an error by the control room staff can be catastrophic. The present study was conducted with the aim of identifying and evaluating human errors in the control room of one of the petrochemical industries.
The present descriptive-analytic study was conducted in a control room of one of the petrochemical industries. In this research, the job tasks in the main control room were first analyzed using hierarchical analysis. Then, using the extensive CREAM method, in addition to identifying human errors, probabilistic user controls and cognitive probability errors for job tasks were determined and evaluated. All stages of this research were conducted ethically.
The results of the study showed that the type of control style for the Board man tasks was strategic in 88% of the cases and the remaining 12% was of the instant type. Based on the results of the CREAM method, execution errors (55%), interpretation errors (20%), planning errors (14.9%) and observational errors (10.1%) were respectively the most determined errors.
Regarding the determination of the role of the most important factors in the implementation of tasks, the review and redevelopment of the program of shift work and optimization of the communication system were among the most important suggestions of the present study.

Today, due to the development of technology and automation of industries, the presence of humans in working environments has decreased. Despite this dramatic decline, the cause of more than 80 percent of the incidents in the oil and gas industry is related to human errors. The purpose of this research was to identify and evaluate the human errors of operators in control rooms working in the Parsian Gas Refinery company.
This cross-sectional study was performed in the control rooms of Parsian Gas Refinery company. A hierarchical task analysis (HTA) was used in the first phase, and then, in the next step in order to the identification and assessment of the human errors, SHERPA method was performed.
Among the total of 218 errors related to the analysis of the SHERPA worksheets, 145 errors (66.5 %) were related to action ones, 61 to (28%) checking errors, 4 (1.8%) to retrieval errors, 6 (2.8%) to communication errors and 2 (0.9%) to selection errors. Also, 41.9% of the errors caused severe consequences.
It can be concluded that the most prevalent errors are checking and action errors. Appropriate control measures, such as work instructions, staff training as well as employing inspection operators to monitor the performance should be considered as a priority to reduce the occurrence of any identified error or limit their consequences.

Studies in the field of industrial accidents have shown that Human errors have the most important and significant role in accidents. According to studies conducted, 60 to 90 percent of accidents occur as a direct result of human errors. The main objective of this study is to identify and assess human errors in Control Rooms of Arya Sasol Polymer Company by CREAM method.
This Descriptive, Cross_Sectional study was conducted in 2016, using the Hierarchical task analysis (HTA). 14 job tasks was analyzed in four control rooms of the Arya Sasol Polymer Company. Then, by using the basic and extended version of CREAM, common performance conditions and cognitive failure probability were determined and the results were analyzed.
The results of this study show that 45% of identified errors related to execution errors, 22% observation errors, 22% interpretation errors and 11% planning errors.
The results of this study show that it is required to Opportunistic Control Mode for initiating off-site section But for other tasks need to Tactical control mode. Using this technique is appropriate to determine the type of errors and methods of control.

From the 70s onwards, safety engineering made significant progress in developing techniques and regulations relating to the fire. The first, this methods was considered after happening accidents to prevent similar accidents. But with the advancement of technology, the prediction and prevention of fire in complex industries such as power plant finds Important. This study is done to determine the risk of fire in the control room of a power plant and proposed effective strategies to fire prevention. In this study, based on fire risk assessment methods for engineers, computational package was prepared by EXCEL software. Next to the building and contents, residents and activities in the plant control room, risk assessment calculations were carried out separately. At the end based of FRAME pattern, proposed appropriate control measures. The results showed that the risk of fire for building and contents is 1.02, residents 20.6 and activity is 0.5. According to the acceptable level of risk in the method, only the risk of fire in activities within the acceptable range. The results showed that in case of fire, the expected damage to buildings is 10-20 percent. The fire risk for residents is required to take preventive measures to reduce the level of risk. The results showed that the FRAME method, in addition to risk assessment can determine the strengths and weaknesses of existing systems and will provide appropriate control measures to prevent fires in buildings built.

Nature of the work in control rooms is such that it can be classified as sophisticated with high-cognitive load jobs and, therefore, the prevention of human error seems to be necessary. A nalysis of cognitive tasks is the first and important step for designing preventive programs. This study was conducted to identify, quantify and compare the cognitive requirements of different occupations in the control rooms of a petrochemical industry. In this cross-sectional and descriptive-analytical study, Cognitive Task Analysis (CTA) and Fleishman Job Analysis Survey (FJAS) methods were used. The samples were 20 expert control room operators from leaders, board operators and site operators with 40.9 ± 6.98 years of old and 17.05 ± 6.25 years of work experience, which voluntary participated in this study. The One-Way ANOVA and Tukey HSD tests were used for Statistical data analysis via SPSS version 17. Based on the results of HTA –as the first CTA phase- 8 subtasks in leadership, board operator and site operator tasks were recognized. In addition, 12 cognitive requirements were defined for studied tasks via CTA. The FJAS scores indicated that 70% of recognized requirements in CTA are in moderate to high levels (the FJAS mean score higher than 4) which obligates a relatively high cognitive ability to operators. The Tukey HSD test results revealed no significant difference in cognitive requirements level of leadership and board operator tasks, as well as board operators and site operators. However, it was significantly different between leadership and site operator tasks (P value <0.05). This study indicated numerous and relatively, high level cognitive requirements of tasks in petrochemical control rooms, especially, among board operators. Moreover, due to the ability of scaling and analyzing various parameters, FJAS can be considered not only as a complementary but also as an alternative for CTA.

Considering the role of human errors in the incidence of catastrophic events in control rooms and also Lack of effectiveness of classical techniques to identify the human errors، special techniques are required for identification of human errors. Therefore، this study aimed to identify human errors in the control room in an oil company Using HEIST Technique. The present study is a case study of qualitative research that was conducted with using HEIST Technique. Collection of the required information has been done with Walking-Talking Trough and «Rose & Roses» model that is used for classification the decision-making process. «Kirwan» model is used for classification of factors that are involved in human errors and Types of errors have been detected with the SRK Model. Overall، 300 human errors has been detected. Of which،» interactions with controllers and indicators «،» instructions «and» training and experience «alone causes 71 percent of human errors in control room operators. In addition، 90% of human errors were related to the «stages of implementation of the solution»، «observing system» and «selection hypothesis». The results of this study showed a variety of possible scenarios resulting from human errors and their unintended consequences. These results emphasize that there are several weaknesses suggesting the implementation of both engineering and administrative controls simultaneously to reduce human errors