Human reliability assessment for complex physical operations in harsh operating conditions

2020 ◽  
Vol 140 ◽  
pp. 1-13
Author(s):  
Nima Golestani ◽  
Rouzbeh Abbassi ◽  
Vikram Garaniya ◽  
Mohsen Asadnia ◽  
Faisal Khan
Procedia CIRP ◽  
2016 ◽  
Vol 50 ◽  
pp. 796-801
Author(s):  
Julia Lindén ◽  
Anders Söderberg ◽  
Ulf Sellgren

2018 ◽  
pp. 135-135
Author(s):  
K. Rea ◽  
B. Kirwan ◽  
M. Lihou

2016 ◽  
Vol 06 (01) ◽  
pp. 25-34 ◽  
Author(s):  
Ahmad BahooToroody ◽  
Mohammad Mahdi Abaiee ◽  
Reza Gholamnia ◽  
Mohammad Bahoo Torody ◽  
Nastaran Hekmat Nejad

Author(s):  
Марина Николаевна Ильина ◽  
Дмитрий Васильевич Ларюшкин

Источником информации о техническом состоянии трубопроводов тепловых сетей объектов магистральных нефтепроводов ПАО «Транснефть» являются результаты их обслуживания и ремонта, технического освидетельствования, гидравлических испытаний и т. д. На основании этих данных проводятся расчеты показателей надежности, по итогам анализа которых осуществляется планирование дальнейшего технического обслуживания и ремонта. Однако при оценке надежности систем теплоснабжения необходимо учитывать не только срок эксплуатации и величину амортизационного износа, но и реальное состояние в конкретных условиях функционирования. Учесть многообразие факторов, которые влияют на работоспособность трубопроводов системы теплоснабжения, и тем самым повысить точность расчетов при оценке их остаточного ресурса позволяет применение кластерного анализа в дополнение к используемой методике оценки надежности тепловых сетей. В рамках настоящей работы оценка надежности объектов АО «Связьтранснефть» с применением кластерного анализа проведена на примере равнозначных участков тепловых сетей двух узлов связи, расположенных в Краснодарском крае и Республике Саха (Якутия). Currently, information about technical condition of pipelines of heat supply systems at the facilities of the main oil pipelines of PJSC Transneft is formed based on the results of maintenance and repair, technical inspection, hydraulic tests, etc. Upon these data, calculations of reliability indicators of heat networks are carried out, based on the analysis of calculations further maintenance and repairs are planned. However, when assessing the reliability of heat supply systems, it is necessary to take into account not only the service life and the amount of depreciation wear of heat network elements, but also their real state in specific operating conditions. The use of cluster analysis in addition to the currently used method of heat network reliability assessment allows us to take into account the variety of factors that affect the operability of pipelines of the heat supply system, and thereby increase the accuracy of calculations when assessing their residual resource. Within the framework of this work, the reliability assessment of Svyaztransneft JSC facilities using cluster analysis was carried out on the example of equivalent sections of heat networks of two communication nodes located in the Krasnodar Territory and the Republic of Sakha (Yakutia).


2019 ◽  
pp. 528-543
Author(s):  
Khashayar Hojjati-Emami ◽  
Balbir S. Dhillon ◽  
Kouroush Jenab

Human error has played a critical role in the events precipitating the road accidents. Such accidents can be predicted and prevented by risk assessment, in particular assessing the human contribution to risk. As part of the Human Reliability Assessment (HRA) process, it is usually necessary not only to define what human errors can occur, but how often they will occur. Lack of understanding of the failure distribution characteristics of drivers on roads at any given time is a factor impeding the development of human reliability assessment and prediction of road accidents in order to take best proactive measures. The authors developed the complete investigation methodology for crash data collection. Furthermore, they have experimentally tested the proposed predictive behavioral characteristics of drivers in light of their instantaneous error rate over the course of driving period to assist processing and analysis of data collection as part of risk assessment. The findings of this research can assist road safety authorities to collect the necessary data, to better understand the behavioral characteristics of drivers on roads, to make more accurate risk assessments and finally to come up with right preventive measures.


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