Development of risk assessment model for biomass plant boiler using bayesian network
Malaysia as the second-largest producer of crude palm oil has abundance of biomass residues from palm oil industries which can be converted to bio-chemicals to generate electricity. However, despite institutional arrangements of the biomass industry, there are several risks which may prone to reduce...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IOP Publishing
2020
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/30929/1/Development%20of%20risk%20assessment%20model%20for%20biomass%20plant.pdf |
| _version_ | 1796994525083729920 |
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| author | F. A., Alaw Nurul Sa'aadah, Sulaiman |
| author_facet | F. A., Alaw Nurul Sa'aadah, Sulaiman |
| author_sort | F. A., Alaw |
| collection | UMP |
| description | Malaysia as the second-largest producer of crude palm oil has abundance of biomass residues from palm oil industries which can be converted to bio-chemicals to generate electricity. However, despite institutional arrangements of the biomass industry, there are several risks which may prone to reduce efficiency of biopower boiler especially empty fruit bunch as the fuel. Boiler is one of the primary equipment of power generation plants, in a significant role in converting biofuel to electricity. The main risk areas in biopower boiler are dearator, economizer, fuel preparation, and water cooling system. Available risk methodologies are not able to provide accurate results for a combination of risks. In this work, Bayesian network approach is introduced to determine and predict risk associated with biopower boiler. The predictive and diagnosis analyses of the Bayesian Network were performed to find the casual links which cause the failure and make a prediction of the control measures to reduce the rate of mistakes. Results revealed that dearator showed a significant effect when the system operates beyond the limits of its design. In conclusion, Bayesian Networks appear to be an assist for decision makers to decide when and where to take preventive or mitigate measures. |
| first_indexed | 2024-03-06T12:48:59Z |
| format | Conference or Workshop Item |
| id | UMPir30929 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:48:59Z |
| publishDate | 2020 |
| publisher | IOP Publishing |
| record_format | dspace |
| spelling | UMPir309292021-07-26T13:55:20Z http://umpir.ump.edu.my/id/eprint/30929/ Development of risk assessment model for biomass plant boiler using bayesian network F. A., Alaw Nurul Sa'aadah, Sulaiman TP Chemical technology Malaysia as the second-largest producer of crude palm oil has abundance of biomass residues from palm oil industries which can be converted to bio-chemicals to generate electricity. However, despite institutional arrangements of the biomass industry, there are several risks which may prone to reduce efficiency of biopower boiler especially empty fruit bunch as the fuel. Boiler is one of the primary equipment of power generation plants, in a significant role in converting biofuel to electricity. The main risk areas in biopower boiler are dearator, economizer, fuel preparation, and water cooling system. Available risk methodologies are not able to provide accurate results for a combination of risks. In this work, Bayesian network approach is introduced to determine and predict risk associated with biopower boiler. The predictive and diagnosis analyses of the Bayesian Network were performed to find the casual links which cause the failure and make a prediction of the control measures to reduce the rate of mistakes. Results revealed that dearator showed a significant effect when the system operates beyond the limits of its design. In conclusion, Bayesian Networks appear to be an assist for decision makers to decide when and where to take preventive or mitigate measures. IOP Publishing 2020-12-22 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/30929/1/Development%20of%20risk%20assessment%20model%20for%20biomass%20plant.pdf F. A., Alaw and Nurul Sa'aadah, Sulaiman (2020) Development of risk assessment model for biomass plant boiler using bayesian network. In: IOP Conference Series: Materials Science and Engineering; 5th International Conference of Chemical Engineering and Industrial Biotechnology, ICCEIB 2020 , 9 - 11 August 2020 , Kuala Lumpur, Malaysia. pp. 1-9., 991 (1). ISSN 1757-8981 (Print), 1757-899X (Online) https://doi.org/10.1088/1757-899X/991/1/012136 |
| spellingShingle | TP Chemical technology F. A., Alaw Nurul Sa'aadah, Sulaiman Development of risk assessment model for biomass plant boiler using bayesian network |
| title | Development of risk assessment model for biomass plant boiler using bayesian network |
| title_full | Development of risk assessment model for biomass plant boiler using bayesian network |
| title_fullStr | Development of risk assessment model for biomass plant boiler using bayesian network |
| title_full_unstemmed | Development of risk assessment model for biomass plant boiler using bayesian network |
| title_short | Development of risk assessment model for biomass plant boiler using bayesian network |
| title_sort | development of risk assessment model for biomass plant boiler using bayesian network |
| topic | TP Chemical technology |
| url | http://umpir.ump.edu.my/id/eprint/30929/1/Development%20of%20risk%20assessment%20model%20for%20biomass%20plant.pdf |
| work_keys_str_mv | AT faalaw developmentofriskassessmentmodelforbiomassplantboilerusingbayesiannetwork AT nurulsaaadahsulaiman developmentofriskassessmentmodelforbiomassplantboilerusingbayesiannetwork |