Neural network based human reliability analysis method in production systems
Nowadays, many accidents, malfunctions, and quality defects are happening in production systems due to Human Errors Probability (HEP). Human Reliability Analysis (HRA) methods have been proposed to measure the HEP based on Performance Shaping Factors (PSFs), but these methods do not have a procedure...
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| Format: | Article |
| Language: | English |
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Ayandegan Institute of Higher Education, Iran
2021-09-01
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| Series: | Journal of Applied Research on Industrial Engineering |
| Subjects: | |
| Online Access: | http://www.journal-aprie.com/article_133616_0da9f69b353714322085ac9ea4ac39e9.pdf |
| _version_ | 1811339443760529408 |
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| author | Rasoul Jamshidi Mohammad Ebrahim Sadeghi |
| author_facet | Rasoul Jamshidi Mohammad Ebrahim Sadeghi |
| author_sort | Rasoul Jamshidi |
| collection | DOAJ |
| description | Nowadays, many accidents, malfunctions, and quality defects are happening in production systems due to Human Errors Probability (HEP). Human Reliability Analysis (HRA) methods have been proposed to measure the HEP based on Performance Shaping Factors (PSFs), but these methods do not have a procedure to select the effective PSFs and consider the PSFs dependency. In this paper, we propose an Artificial Neural Network based Human Reliability Analysis (ANNHRA) in cooperation with Response Surface Method (RSM). This framework uses the advantage Systematic Human Error Reduction and Prediction Approach (SHERPA) method to quantify the PSFs and the ANN and RSM to consider the PSFs dependency and select the most effective PSFs. This framework decreases the time and cost and increases the accuracy of HRA. The proposed framework has been applied to a real case and the provided results show that human reliability can be calculated more effectively using ANNHRA framework. |
| first_indexed | 2024-04-13T18:26:42Z |
| format | Article |
| id | doaj.art-81e2a626c0cd4fe69be3642dc63e0f24 |
| institution | Directory Open Access Journal |
| issn | 2538-5100 2676-6167 |
| language | English |
| last_indexed | 2024-04-13T18:26:42Z |
| publishDate | 2021-09-01 |
| publisher | Ayandegan Institute of Higher Education, Iran |
| record_format | Article |
| series | Journal of Applied Research on Industrial Engineering |
| spelling | doaj.art-81e2a626c0cd4fe69be3642dc63e0f242022-12-22T02:35:14ZengAyandegan Institute of Higher Education, IranJournal of Applied Research on Industrial Engineering2538-51002676-61672021-09-018323625010.22105/jarie.2021.277071.1274133616Neural network based human reliability analysis method in production systemsRasoul Jamshidi0Mohammad Ebrahim Sadeghi1Department Industrial of Engineering, School of Engineering, Damghan University, Damghan, Iran.Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.Nowadays, many accidents, malfunctions, and quality defects are happening in production systems due to Human Errors Probability (HEP). Human Reliability Analysis (HRA) methods have been proposed to measure the HEP based on Performance Shaping Factors (PSFs), but these methods do not have a procedure to select the effective PSFs and consider the PSFs dependency. In this paper, we propose an Artificial Neural Network based Human Reliability Analysis (ANNHRA) in cooperation with Response Surface Method (RSM). This framework uses the advantage Systematic Human Error Reduction and Prediction Approach (SHERPA) method to quantify the PSFs and the ANN and RSM to consider the PSFs dependency and select the most effective PSFs. This framework decreases the time and cost and increases the accuracy of HRA. The proposed framework has been applied to a real case and the provided results show that human reliability can be calculated more effectively using ANNHRA framework.http://www.journal-aprie.com/article_133616_0da9f69b353714322085ac9ea4ac39e9.pdfhuman reliability analysiserror predictionperformance shaping factorscognitive factors |
| spellingShingle | Rasoul Jamshidi Mohammad Ebrahim Sadeghi Neural network based human reliability analysis method in production systems Journal of Applied Research on Industrial Engineering human reliability analysis error prediction performance shaping factors cognitive factors |
| title | Neural network based human reliability analysis method in production systems |
| title_full | Neural network based human reliability analysis method in production systems |
| title_fullStr | Neural network based human reliability analysis method in production systems |
| title_full_unstemmed | Neural network based human reliability analysis method in production systems |
| title_short | Neural network based human reliability analysis method in production systems |
| title_sort | neural network based human reliability analysis method in production systems |
| topic | human reliability analysis error prediction performance shaping factors cognitive factors |
| url | http://www.journal-aprie.com/article_133616_0da9f69b353714322085ac9ea4ac39e9.pdf |
| work_keys_str_mv | AT rasouljamshidi neuralnetworkbasedhumanreliabilityanalysismethodinproductionsystems AT mohammadebrahimsadeghi neuralnetworkbasedhumanreliabilityanalysismethodinproductionsystems |