Modeling operators' emergency response time for chemical processing operations

2014 ◽  
Vol 12 (6) ◽  
pp. 479
Author(s):  
Susan L. Murray, PhD ◽  
Emrah Harputlu, MS ◽  
Ray A. Mentzer, PhD ◽  
M. Sam Mannan, PhD
Keyword(s):  
Response Time ◽  
Emergency Response ◽  
Industrial Engineering ◽  
Time Range ◽  
Chemical Processing ◽  
Emergency Situations ◽  
Time Requirements ◽  
Corrective Actions ◽  
Time Required ◽  
Time Standard

Operators have a crucial role during emergencies at a variety of facilities such as chemical processing plants. When an abnormality occurs in the production process, the operator often has limited time to either take corrective actions or evacuate before the situation becomes deadly. It is crucial that system designers and safety professionals can estimate the time required for a response before procedures and facilities are designed and operations are initiated.There are existing industrial engineering techniques to establish time standards for tasks performed at a normal working pace. However, it is reasonable to expect the time required to take action in emergency situations will be different than working at a normal production pace. It is possible that in an emergency, operators will act faster compared to a normal pace. It would be useful for system designers to be able to establish a time range for operators' response times for emergency situations. This article develops a modeling approach to estimate the time standard range for operators taking corrective actions or following evacuation procedures in emergency situations. This will aid engineers and managers in establishing time requirements for operators in emergency situations.The methodology used for this study combines a well-established industrial engineering technique for determining time requirements (predetermined time standard system) and adjustment coefficients for emergency situations developed by the authors. Numerous videos of workers performing well-established tasks at a maximum pace were studied. As an example, one of the tasks analyzed was pit crew workers changing tires as quickly as they could during a race. The operations in these videos were decomposed into basic, fundamental motions (such as walking, reaching for a tool, and bending over) by studying the videos frame by frame. A comparison analysis was then performed between the emergency pace and the normal working pace operations to determine performance coefficients. These coefficients represent the decrease in time required for various basic motions in emergency situations and were used to model an emergency response. This approach will make hazardous operations requiring operator response, alarm management, and evacuation processes easier to design and predict. An application of this methodology is included in the article. The time required for an emergency response was roughly a one-third faster than for a normal response time.

Time required to notify 9-1-1 with automated collision notification systems

2007 ◽  
Vol 5 (5) ◽  
pp. 43
Author(s):  
Alan J. Blatt, BS, MEng ◽  
Dietrich Von Kuenssberg Jehle, MD, FACEP ◽  
Anthony J. Billittier IV, MD, FACEP ◽  
David G. Wagner, MD ◽  
Jill Schleifer-Schneggenburger, BS, MEng
Keyword(s):  
Confidence Interval ◽  
Response Time ◽  
Emergency Response ◽  
Field Test ◽  
Traditional Method ◽  
Motor Vehicle ◽  
Motor Vehicle Crash ◽  
Percent Confidence Interval ◽  
System A ◽  
Time Required

Background: Automated Collision Notification (ACN) systems reduce emergency response time to a vehicular crash by immediately alerting a Public Safety Answering Point (PSAP) of the collision and its details.Methods: An operational field test was performed to evaluate the effectiveness and reliability of the ACN system: a total of 874 vehicles were equipped with ACN systems and, for a period of 29 months, all collisions involving these vehicles were included in a study of the automatic notification time. Fifteen collisions of ACN-equipped vehicles registered with a PSAP. Both the time for the ACN notification to be received and the time for a traditional method of notification to be received were recorded for each crash.Results: The ACN notified a PSAP of a collision in an average time of 74.2 seconds and between 79.9 and 456.1 seconds sooner than a traditional notification method (paired mean difference 95 percent confidence interval).Conclusion: The ACN system significantly improves emergency notification time to a motor vehicle crash.

Time-to-scene for opioid overdoses: are unmanned aerial drones faster than traditional first responders in an urban environment?

2020 ◽  
Vol 6 (4) ◽  
pp. 204-208
Author(s):  
Connor Andrew Tukel ◽  
Matthew Ryan Tukel ◽  
Robert Jacob Weinbaum ◽  
Valerie H Mika ◽  
Phillip D Levy
Keyword(s):  
Response Time ◽  
Emergency Response ◽  
Opioid Overdose ◽  
Time Data ◽  
Arrival Times ◽  
Straight Line ◽  
Life Saving ◽  
Rural Settings ◽  
Prospective Trials ◽  
Time Required

IntroductionOpioid overdoses claim tens of thousands of lives every year. Many of these deaths might be prevented if overdose-reversal medications such as naloxone are administered in a timely manner. Drones may help overcome barriers to timely arrival on scene for opioid overdoses. This study analyses the time required for a drone carrying naloxone to traverse various distances, simulating the response time for a drone to the scene of an opioid overdose. For comparison, we used the time required for ambulances to traverse similar distances while responding to the scene of actual or suspected opioid overdoses.MethodsFifty flight trials, using a modified Dà-Jiāng Innovations (DJI) ‘Inspire 2’ drone, were conducted across seven distances, and the travel time for the drone was then compared with historical response time data from 200 actual or suspected opioid overdose cases that occurred within Detroit, Michigan.ResultsWe determined with 95% certainty that drone arrival times were discernibly quicker than ambulance arrival times at all distances where sufficient data were available to perform statistical comparisons including 0.5 km, 1.0 km, 1.5 km, 2.0 km and 3.0 km.ConclusionWe have shown that a drone is capable of travelling several ranges of straight-line (ie, ‘as the crow flies’) distance faster than an ambulance. Further exploration into the use of drones to deliver life-saving therapies in urban and rural settings is warranted. Head-to-head prospective trials that consider the practical challenges of medical drone delivery are needed to better understand the viability of incorporating this technology into existing emergency response infrastructure.

IMPLEMENTATIONS EMERGENCY RESPONSE SYSTEM IN CASE OF ACCIDENTS AND EMERGENCY SITUATIONS (ERA-GLONASS) FOR CARS AND TRUCKS IN UZBEKISTAN

2020 ◽  
Author(s):  
Akmal Rustamov
Keyword(s):  
Emergency Response ◽  
Call Center ◽  
Emergency Services ◽  
Main Idea ◽  
Emergency Situation ◽  
High Mountain ◽  
Additional Information ◽  
Emergency Situations ◽  
Emergency Response System ◽  
Response System

The paper addresses the problem of increasing transportation safety due to usage of new possibilities provided by modern technologies. The proposed approach extends such systems as ERA-GLONASS and eCall via service network composition enabling not only transmitting additional information but also information fusion for defining required emergency means as well as planning for a whole emergency response operation. The main idea of the approach is to model the cyber physical human system components by sets of services representing them. The services are provided with the capability of self- contextualization to autonomously adapt their behaviors to the context of the car-driver system. The approach is illustrated via an accident emergency situation response scenario. “ERA-GLONASS” is the Russian state emergency response system for accidents, aimed at improving road safety and reducing the death rate from accidents by reducing the time for warning emergency services. In fact, this is a partially copied European e Call system with some differences in the data being transmitted and partly backward compatible with the European parent. The principle of the system is quite simple and logical: in the event of an accident, the module built into the car in fully automatic mode and without human intervention determines the severity of the accident, determines the vehicle’s location via GLONASS or GPS, establishes connection with the system infrastructure and in accordance with the protocol, transfers the necessary data on the accident (a certain distress signal). Having received the distress signal, the employee of the call center of the system operator should call the on-board device and find out what happened. If no one answers, send the received data to Sistema-112 and send it to the exact coordinates of the team of rescuers and doctors, and the last one to arrive at the place is given 20 minutes. And all this, I repeat, without the participation of a person: even if people caught in an accident will not be able to independently call emergency services, the data on the accident will still be transferred. In this work intended to add some information about applying system project in Uzbek Roads especially mountain regions like “Kamchik” pass. The Kamchik Pass is a high mountain pass at an elevation of 2.306 m above the sea level, located in the Qurama Mountains in eastern Uzbekistan and its length is about 88km.The road to reach the pass is asphalted, but there are rough sections where the asphalt has disappeared. It’s called A373. The old road over the pass was by passed by a tunnel built in 1999. On the horizon, the snow-capped peaks of the Fan Mountains come into view. The pass is located in the Fergana Valley between the Tashkent and Namangan Regions.

NH4 automatic analysers for wastewater treatment plant: evaluation test at laboratory and field level

1996 ◽  
Vol 33 (1) ◽  
pp. 193-201
Author(s):  
H. Wacheux ◽  
J.-L. Million ◽  
C. Guillo ◽  
E. Alves
Keyword(s):  
Wastewater Treatment ◽  
Response Time ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Field Tests ◽  
Time Range ◽  
Data Link ◽  
Factors Of Influence ◽  
June July ◽  
Plant Evaluation

Nine NH4 automatic analysers or monitors were tested in June-July 1995 (among them 2 prototypes): - 5 based on ion electrode; ABB, Applikon, Contronic, Hydro-Environnement, STIP, - 4 based on colorimetry; Danfoss, Data Link (UV absorption), Meerestechnik, Skalar Laboratory tests are aimed to determine response time, repeatability, response linearity, short-term stability, influence of various factors on the measurement. The field test relates to real conditions: all the sensors were installed in parallel at the discharge point of a Wastewater treatment plant (WWTP). Recorded outputs were compared with conventional laboratory analysis of average hourly samples. Response time range from 2 to 21 minutes. Repeatability varies from 1 to 10%, stability from 1 to 17%. Linearity is always good and detection limits (about 0.2 mg/l) do not seem to be critical for use in a WWTP. Among factors of influence, power voltage has limited effect, sample temperature is affecting some monitors, chemical interferents have nearly no effect excepted for one monitor. Field tests have shown that NH4 monitors are still very sensitive and that installation is crucial. Each monitor suffered several failures, some of them required high maintenance and used costly reagents.

Clinic Time Required for Remote and In-person Management of Cardiac Device Patients: A Time and Motion Workflow Evaluation (Preprint)

2021 ◽  
Author(s):  
David Lanctin ◽  
Eliana Biundo ◽  
Marco Di Bacco ◽  
Sarah Rosemas ◽  
Emmanuelle Nicolle ◽  
...  
Keyword(s):  
Patient Management ◽  
Clinic Visit ◽  
Future Research ◽  
Staff Time ◽  
Cardiac Device ◽  
Cardiac Implantable Electronic Devices ◽  
Time And Motion ◽  
Number Of Patients ◽  
Time Requirements ◽  
Time Required

BACKGROUND The number of patients with cardiac implantable electronic devices (CIEDs) is growing, creating substantial workload for device clinics. OBJECTIVE This study aimed to characterize the workflow and quantify clinic staff time requirements to manage CIED patients. METHODS A time and motion workflow evaluation was performed in 11 US and European CIED clinics. Workflow tasks were repeatedly timed during one business week of observation at each clinic. Observations were inclusive of all device models/manufacturers present. Mean cumulative staff time required to review a Remote device transmission and for an In-person clinic visit were calculated, including all necessary clinical and administrative tasks. Annual staff time for follow-up of 1 CIED patient was modeled using CIED transmission volumes, clinical guidelines, and published literature. RESULTS A total of 276 in-person clinic visits and 2,173 remote monitoring activities were observed. Mean staff time required per remote transmission ranged from 9.4-13.5 minutes for therapeutic devices (pacemaker, ICD, CRT) and 11.3-12.9 mins for diagnostic devices (insertable cardiac monitors (ICMs)). Mean staff time per in-person visit ranged from 37.8-51.0 mins and 39.9-45.8 mins, for therapeutic devices and ICMs respectively. Including all remote and in-person follow-ups, the estimated annual time to manage one CIED patient ranged from 1.6-2.4 hours for therapeutic devices and 7.7-9.3 hours for ICMs. CONCLUSIONS CIED patient management workflow is complex and requires significant staff time. Understanding process steps and time requirements informs implementation of efficiency improvements, including remote solutions. Future research should examine the heterogeneity in patient management processes to identify the most efficient workflows.

scholarly journals Dynamic Computation Offloading Scheme for Drone-Based Surveillance Systems

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2982 ◽  
Author(s):  
Bongjae Kim ◽  
Hong Min ◽  
Junyoung Heo ◽  
Jinman Jung
Keyword(s):  
Response Time ◽  
Target Object ◽  
Computation Offloading ◽  
Moving Target ◽  
Surveillance Systems ◽  
Network Failure ◽  
Dynamic Computation ◽  
Tracking Time ◽  
Time Required ◽  
Time Critical

Recently, various technologies for utilizing unmanned aerial vehicles have been studied. Drones are a kind of unmanned aerial vehicle. Drone-based mobile surveillance systems can be applied for various purposes such as object recognition or object tracking. In this paper, we propose a mobility-aware dynamic computation offloading scheme, which can be used for tracking and recognizing a moving object on the drone. The purpose of the proposed scheme is to reduce the time required for recognizing and tracking a moving target object. Reducing recognition and tracking time is a very important issue because it is a very time critical job. Our dynamic computation offloading scheme considers both the dwell time of the moving target object and the network failure rate to estimate the response time accurately. Based on the simulation results, our dynamic computation offloading scheme can reduce the response time required for tracking the moving target object efficiently.

scholarly journals An Extended Rule of the SysML Requirement Diagram Transformation into OWL Ontologies

2021 ◽  
Vol 14 (1) ◽  
pp. 506-515
Author(s):  
Ahmad Ashari ◽  
◽  
Anny Sari ◽  
Helna Wardhana ◽  
◽  
...  
Keyword(s):  
Response Time ◽  
System Modeling ◽  
Unified Modeling Language ◽  
Modeling Language ◽  
Functional Requirements ◽  
Unified Modeling ◽  
Object Property ◽  
Transformation Rules ◽  
Owl Ontology ◽  
Time Required

The System Modeling Language (SysML) used the Requirement Diagram to model non-functional requirements, such as response time, size, or system functionality, which cannot be accommodated in the Unified Modeling Language (UML). SysML Requirement Diagram, in its implementation, integrates with several diagrams describing the requirements, which are referred to as additional elements. The absence of transformation rules for these additional elements to become OWL ontology causes difficulties in reading, understanding, and tracking the requirements. In this research, an extended rule of the Requirement Diagram transformation is proposed to solve the problems. First, some transformation rules are defined to make requirements easier to trace and realize the ontology generation's automatic transformation. Second, the time required during transformation processing to prepare and generate the OWL file shows the proposed model's performance. The ontology components produced from this research, such as class, subclass, object property, and data property, can be viewed in Protégé.

scholarly journals TWO-GRAPH BUILDING INTERIOR REPRESENTATION FOR EMERGENCY RESPONSE APPLICATIONS

2016 ◽  
Vol III-2 ◽  
pp. 9-14
Author(s):  
P. Boguslawski ◽  
L. Mahdjoubi ◽  
V. Zverovich ◽  
F. Fadli
Keyword(s):  
Decision Making ◽  
Emergency Response ◽  
Indoor Environment ◽  
Fire Spread ◽  
Variable Density ◽  
Quick Response ◽  
Automated Generation ◽  
Emergency Situations ◽  
Available Information ◽  
Automated Methods

Nowadays, in a rapidly developing urban environment with bigger and higher public buildings, disasters causing emergency situations and casualties are unavoidable. Preparedness and quick response are crucial issues saving human lives. Available information about an emergency scene, such as a building structure, helps for decision making and organizing rescue operations. Models supporting decision-making should be available in real, or near-real, time. Thus, good quality models that allow implementation of automated methods are highly desirable. This paper presents details of the recently developed method for automated generation of variable density navigable networks in a 3D indoor environment, including a full 3D topological model, which may be used not only for standard navigation but also for finding safe routes and simulating hazard and phenomena associated with disasters such as fire spread and heat transfer.

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