Identification and evaluation of human errors of Epoxy control room operators of a pipe Mill company using HEC technique

Introduction: 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, 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. Materials and Methods: 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. Results: 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. Conclusion: 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.

Health Monitoring and Tracking System for Soldiers Using Internet of Things (IoT)

The paper reports an Internet of Thing (IoT) based health monitoring and tracking system for soldiers. The proposed system can be mounted on the soldier’s body to track their health status and current location using GPS. These information will be transmitted to the control room through IoT. The proposed system comprise of tiny wearable physiological equipment’s, sensors, transmission modules. Hence, with the use of the proposed equipment, it is possible to implement a low cost mechanism to protect the valuable human life on the battlefield

Formal Modeling of IoT and Drone-Based Forest Fire Detection and Counteraction System

Forests are an enduring component of the natural world and perform a vital role in protecting the environment. Forests are valuable resources to control global warming and provide oxygen for the survival of human life, including wood for households. Forest fires have recently emerged as a major threat to biological processes and the ecosystem. Unfortunately, almost every year, fire damages millions of hectares of forest land due to late and inefficient detection of fire. However, it is important to identify the forest fire at the initial level before it spreads to vast areas and destroys natural resources. In this paper, a formal model of the Internet of Things (IoT) and drone-based forest fire detection and counteraction system is presented. The proposed system comprises network maintenance. Sensor deployment is on trees, the ground, and animals in the form of subnets to transmit sensed data to the control room. All subnets are connected to the control room through gateway nodes. Alarms are being used to alert human beings and animals to save their lives, which will help to initially protect them from fire. The embedded sensors collect the information and transfer it to the gateways. Drones are being used for real-time visualization of fire-affected areas and to perform actions to control fires because they play a vital role in disasters. Graph theory is used to construct an efficient model and to show the connectivity of the network. To identify failures and develop recovery procedures, the algorithm is designed through the graph-based model. The model is developed by the Vienna Development Method-Specification Language (VDM-SL), and the correctness of the model is ensured using various VDM-SL toolbox facilities.

Risk Assessment through Fire and Evacuation Simulation in the Main Control Room of a Domestic Thermal Power Plant

A fire in the main control room of a thermal power plant is a significant threat to the entire power plant by incapacitating the concept of performance design to secure the safety of the power plant. In this study, using the PyroSim and Pathfinder programs to evaluate fire and evacuation risk of the main control room, the appropriate time and fire shape for evacuating people calmly were confirmed when the available safe egress time and required safe egress time of the main control room were compared. In the case of a cable fire, the simulation results indicate the heat generation rate to be more serious than the actual experimental results showed. This is because heat generation was lower in the experiment as the polymer material constituting the cable fell to the floor during combustion and no loger burns. The fire dynamics simulator results indicate that the power plant facility is safe because even these points are not considered.

The modeling of a Tokamak plasma discharge, from first principles to a flight simulator

A newly developed tool to simulate a tokamak full--discharge is presented. The tokamak "flight--simulator" Fenix couples the tokamak control system with a fast and reduced plasma model, yet realistic enough to take into account several of the plasma non--linearities. Distinguishing feature of this modeling tool is that it only requires the Pulse Schedule (PS) as input to the simulator. The output is a virtual realization of the full discharge, which time traces can then be used to judge if the PS satisfies control/physics goals or needs to be revised. This tool is thought for routine use in the control--room before each pulse is performed, but can also be used off--line to correct PS in advance, or to develop and validate reduced models, control schemes, and in general the simulation framework.

Resilience Control Room Operator During Pandemic Covid-19

The control room acts as a central nervous system facility. This is where important decisions, using complex systems, are made every day. The actions of control room operators have a direct impact on uptime, production yields, quality, and industrial plant safety. In addition, long working hours per shift result in fatigue, irregularity of circadian rhythms and sleep cycles, and decreased cognitive performance at the end of day and night shifts. Fatigue causes decreased alertness, attention span, poor memory, and concentration and affect other mental factors. ADNOC Gas Processing established Fatigue Risk Management Taskforce (FRMT) to adapt practices to the specific conditions and create a safer working environment, leading to happier and healthier employees and an overall community. In industries that run continuous and heavy-duty plants such as Oil, gas, and petrochemical, shift work ensures production flow. After the outbreak of Covid-19, business needs to adapt quickly so that their activities can run. The finding suggests that the workers' cognitive performance is reduced, shown by the increase of triggered alarm by the average of 14.39% higher than before the outbreak of Covid-19. However, with the ability to adapt and implement control and monitoring measures, the number of alarm rate gradually decreased. The study framework was proven to be a valuable tool that decision-makers can use, especially to measure the performance of control room workers and their psychological fatigue affected by the Covid-19 pandemic.

Doing the Right Things Through Operator Proactive Monitoring

Operator Proactive Monitoring is one of the critical paths to Ensure Safe Production. The objective is to ensure that facilities are proactively monitored to retain the best possible level of situational awareness. It is achieved by monitoring and control the unit and equipment to avoid exceeding a safe limit while meeting all operational and business targets. It promotes early detection & appropriate intervention to an arising abnormal situation. Operator Proactive Monitoring covers a wide range of activities from a control room and field operation. ADNOC Gas Processing, in line with the digital transformation program, has enterprise assets/equipment through implementing Operator Proactive Monitoring for control room and field operator. Operator rounds play an essential role in improving plant reliability and safety. This research aims to measure the effectiveness of the Operator Proactive Monitoring by the Ruwais NGL Operation division at ADNOC Gas Processing. By "doing the right thing," Operator Proactive Monitoring effectively supports and improves process safety culture in the operation business of Ruwais Plant division of ADNOC Gas Processing.

Telerobotic interventions from a distance: an initial experience in 3D phantom mapping

Introduction The current COVID-19 pandemic has fostered several accelerations in “remote” patient care such as video and telephone clinics, as well as multidisciplinary collaborations using online platforms with experts consulting the local teams from a distance. The next logical step would be to also offer remote-controlled interventions which the expert operator not on site, but in support of the local team. This is especially valuable for complex interventions when either patient or expert operator can not be present at the same place. Purpose We aimed to demonstrate that an expert operator located at far distance (Austria) could directly interact with the remote magnetic navigation system in London (UK) whilst mapping a 3D phantom using an electroanatomical mapping system. Method Two experienced operators of the magnetic navigation system were tasked with creating fast anatomic maps (FAM) of the atrial and ventricular chambers of a 3D phantom using remote magnetic navigation in combination with 3D electroanatomical mapping. One was located in the control room of the magnetic catheter lab (UK) and the second one was in Tirol, Austria and connected through a secure remote desktop connection (via high speed fibre optic cable). Using a solid tip magnetic catheter connected to a mechanical drive, all interactions with the system were carried out via the Odyssey platform. Acquisitions for right and left atrium, as well as right and left ventricles plus aorta was compared with regards to mapping duration, map completeness (as judged by the average distance of surface points from 3D CT scan reconstruction), total 3D map volume and need for additional radiation exposure during the mapping process. Results Mapping time and map completeness when performed by the distant operator was not inferior to the local operator and both did not require any additional radiation exposure during the mapping process. Table 1 demonstrates the mean parameters for each chamber, respectively. Figure 1 depicts the matched data for chamber completeness as compared for the LA (green= local operator, pink= distant operator) using a contrast CT scan as the gold standard. Conclusion Telerobotic 3D mapping of a 3D phantom from a distance was equally fast delivered from the control room as compared to an operator located 1200 km away without compromising on map completeness. This demonstrates the feasibility of telerobotic interventions and stress the need for remote collaboration which is especially valuable when travel of patients and/or physician experts is restricted. Funding Acknowledgement Type of funding sources: None. Matched data for aorta

Real Drive Truth Test of the Toyota Yaris Hybrid 2020 and Energy Analysis Comparison with the 2017 Model

This paper presents the performance analysis of a latest-generation hybrid vehicle (Toyota Yaris 2020) with a testing campaign in real road conditions and a comparison with the previous model (Toyota Yaris 2017). The study was conducted by applying the Real Drive Truth Test protocol, developed by the research group, validated and spread to other full hybrid vehicles: Toyota Prius IV (2016) and Toyota Yaris 2017 (2017). In the case of the 2020 tests, the co-presence on board—deemed unsafe in the usual ways given the ongoing pandemic—was achieved through precise and sophisticated remote control. An on-board diagnostic computer, video transmission and recording equipment guarantee the virtual co-presence of a technical control room and a driver. Thus, several engineers can follow and monitor each vehicle via a 4G modem (installed in each vehicle), analysing data, route and driver behaviour in real-time, and therefore even in the presence of a single occupant in the car under test. The utmost attention has also been paid to adopting anti-COVID behaviours and safety standards: limited personal interactions, reduced co-presence in shared rooms (especially in the control room), vehicle sanitising between different drivers, computers and technicians and video technicians working once at a time. The comparison between the two subsequent vehicle models shows a significant improvement in the performance of the new generation Yaris, both in terms of operation in ZEV (zero-emission vehicle) mode (+15.3%) and in terms of consumption (−35.1%) and overall efficiency of the hybrid powertrain (+8.2%).