Accident contributor interconnection study as a basis for accident mechanism prediction
The accident rate in the chemical process industry (CPI) is not decreasing although the large majority of accident causes are known, foreseeable and could be prevented by existing knowledge. Continuous learning and improvement on experience feedback system is essential for process safety. In this pa...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Italian Association of Chemical Engineering - AIDIC
2014
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/51704/ http://dx.doi.org/10.3303/CET1436005 |
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| Summary: | The accident rate in the chemical process industry (CPI) is not decreasing although the large majority of accident causes are known, foreseeable and could be prevented by existing knowledge. Continuous learning and improvement on experience feedback system is essential for process safety. In this paper, the experience feedback system is used to generate accident knowledge and understanding on accident mechanism. Accident data such as accident contributors are analysed and their interconnection matrix is develop. The matrix reveals three main functional groups of contributor to accident. Therefore, the likelihood of chronological event of accident could be predicted |
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