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Showing 2 results for Human Reliability
Investigating the Effects of Human Personality on Human Reliability and Accident Frequency Using DISC and HEART Technique in Automotive Industries
Elham Pakdel, Manochehr Omidvari,
Volume 5, Issue 1 (6-2017)
Abstract

Introduction: One of the most important issues in industries is accident. Various factors affect these events, one of which is individual features. This study aimed at investigating the role of human resource personality on human reliability in accident outbreaks using DISC behavioral approach modal in automotive industry.

Methods: This was a descriptive-analytical research. The relationship of person vulnerability with human personality with fallibility was investigated. In order to determine human personality disk standard model was used and to estimate the degree of human fallibility heart techniques were used. Then, the relationships of natural personality, human reconcilable dimensions, human reliability and fallibility were found. Also, the relationship of accident repetition with personality and human fallibility was determined. This research was conducted among 98 personnel of one of the biggest production units during 2013 to 2015.

Results: The results indicated that there was a high correlation in human personality and fallibility dimension with accidents outbreak. There was a significant relationship between persons with influential personality, inherent stability, adapted stability, adapted dutiful, and accident outbreak repetition.

Conclusions:  According to the results, the personality of individuals with high sensitivity in their job and less adaptation to changes made in work environment, has a higher possibility of accidents outbreaks. Perhaps, this issue is created because of the inconsistency between the management system that is ruling the industry of developing countries and personality features of those people.


Identification and Evaluation of Fault in Human-Machine Interactive System using CREAM Technique and Fault Tree Analysis
Nooshin Atashfeshan, Prof Mohammad Saidi-Mehrabad, Hamideh Razavi,
Volume 9, Issue 3 (12-2021)
Abstract
Background and Objectives: Despite contribution to catastrophic accidents, human errors have been generally ignored in the design of human-machine (HM) systems and the determination of the level of automation (LOA). This paper aims to develop a method to estimate the level of automation in the early stage of the design phase considering both human and machine performance.
Methods: A quantitative method is used to evaluate the performance of the whole human-machine system by the human-in-the-loop fault tree analysis while a qualitative and cross-sectional method is used to estimate human errors using the CREAM technique. The data are collected from real cases that happened in the control room of the Ferdowsi power plant.
Results: Full automatic option with an average error of 0.013 had the lowest error rate, i.e. 1/8 of the error rate of the manual design. In addition, the CREAM analysis showed that the control room operators were not satisfied with the availability of procedures and Man-Machine Interface and operational support in general. Thus, on average, the reliability of the manual design is less than the reliability of the automatic setting.
Conclusion: High machine reliability has led to the fact that the fully automatic design would be one of the best design choices for human-machine systems. However, based on the previous studies, high automation may have some human-out-of-the-loop shortcomings. Thus, this study proposed solutions to overcome these disadvantages based on the importance of the control parameters or the essence of human involvement in some decision-making and execution tasks.

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