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Showing 3 results for Human Factors
Psychological Effect of Safety Signs on Message Transmission given Signs Designing Features in Petrochemical Industry
M.saeed Moradi, Davood Afshari, Taher Hoseinzade, Kambiz Ahmadi,
Volume 2, Issue 2 (9-2014)
Abstract
Background: Safety signs are considered as visual intermediates for message transmission and play a crucial role in reducing accidents particularly in petrochemical industries. These signs are effective as long as they are designed in compliance with ergonomic principles, human factors, and cognitive features. Therefore, the present study aimed to investigate the psychological effects of safety signs in transmitting message given their designing features in the petrochemical industry. Materials and methods: This descriptive-cross-sectional study was carried out on 100 employees in Mahshahr Petrochemical Complex. A 2 partite questionnaire was used to collect data the first part for demographic information and the second part included designing features of signs (familiarity, objectivity, simplicity, meaningfulness, semantic proximity). The Pearson correlation test was used to identify the correlation coefficients between signs features and scores given by the participants. Findings: Mean and standard deviation of the scores of the signs’ message perception were 60.73 and 4.36, respectively. Cognitive features of the signs included familiarity and semantic proximity with a mean of 49.15 and 66.78, respectively. The factors of work experience, age, and academic level had no significant effect on guessing the meaning of signs (p>0.05). Conclusion: The results of this study showed that no significant relationship existed between cognitive features of the signs and transmission of the message and message transmission of safety signs is affected by other features than their design. Therefore, in order to improve individuals’ awareness about familiarity of employees with particular meaning of signs, ergonomic design of safety signs and proper training for perceiving their meaning are proposed.
Content and trend analysis of articles published in a key journal on human factors and ergonomics during 2005-2014
Narmin Hassanzadeh-Rangi, Yahya Khosravi,
Volume 3, Issue 2 (9-2015)
Abstract

Introduction: The introduction of a thematic framework is necessary for the field of ergonomics and human factors. Content analysis is a useful tool for the trend analysis and distribution of published articles however, reports on the content analysis of ergonomics journals are rare. The present study was conducted to identify research trends in the journal of Human Factors through a content analysis of its recent articles published over the past ten years (2005-2014).

Materials and Methods: The present study used the directed content analysis method. Two analysis experts classified 741 articles based on their thematic codes. A conceptual framework was used to perform the content analysis. EXCEL 2007 and SPSS-19 were used for the data preparation, theme distribution and trend analysis of the published themes.

Results: From the total of 21 themes extracted, six themes defined over 50% of the variance in the published articles, including “Biomechanics, Anthropometry and Work Physiology", "Display and Control Design", "Surface Transportation Systems", "Cognitive Processes", "Attentional Processes" and "Sensory, Perceptual and Psychomotor Processes". The journal had a special focus on "Biomechanics, Anthropometry and Work Physiology" (about 12%). 

Conclusion: The thematic framework and distribution pattern noticed in this study can be used for planning education and research on human factors and ergonomics in universities, research centers and related organizations.


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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