Publication: Fouling predictive model for maintenance scheduling strategy of crude preheat train in heat exchanger
| dc.contributor.author | Mohammad Fariz Farhan Mohd Jaafar | |
| dc.date.accessioned | 2023-11-17T07:44:16Z | |
| dc.date.available | 2023-11-17T07:44:16Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | The target of this research is to explore the fouling conduct in the heat exchanger by utilizing the chronicled plant information. The plant information is created by utilizing Aspen Hysys for 2 days before the fouling happened with the goal that the information examined is precise and solid. Next, the other target is to show a prescient fouling technique that can earlier foresee the rate of the fouling in warm exchanger for the arranging of maintenance scheduling strategy. The ability of the fouling predictive model and maintenance scheduling results with advisory aide been broke down likewise be one of the goals. The information gathered is isolated into two sections which are fouled condition and clean condition. Fouled condition implies the information gathered from heat exchanger encounters fouling conduct while the cleaned condition implies the information gathered from the heat exchanger in ordinary condition. At that point, every datum of the conditions is separated into training, validation and testing subsets as the contribution for neural network. | |
| dc.identifier.uri | https://irepository.uniten.edu.my/handle/123456789/28661 | |
| dc.language.iso | en_US | |
| dc.subject | Petroleum | |
| dc.title | Fouling predictive model for maintenance scheduling strategy of crude preheat train in heat exchanger | |
| dc.type | Resource Types::text::Final Year Project | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 83 | |
| oaire.citation.startPage | 1 | |
| oairecerif.author.affiliation | #PLACEHOLDER_PARENT_METADATA_VALUE# |