Risk Assessments of Columns Using RBI Program in Petrochemical Plant
| Periodical | Solid State Phenomena (Volume 110) |
|---|---|
| Main Theme | Advances in Safety and Structural Integrity 2005 |
| Edited by | Young-Jin Kim |
| Pages | 231-238 |
| DOI | 10.4028/www.scientific.net/SSP.110.231 |
| Citation | Sang Min Lee et al., 2006, Solid State Phenomena, 110, 231 |
| Online since | March, 2006 |
| Authors | Sang Min Lee, Yoon Suk Chang, Jae Boong Choi, Young Jin Kim, Sang In Han, Song Chun Choi, Ji Yoon Kim |
| Keywords | Artificial Neural Network (ANN), Petrochemical Plant, Qualitative Approach, Quantitative Approach, Risk-Based Inspection (RBI) |
| Price | US$ 28,- |
Risk-based inspection (RBI) guideline based on API 581 provides a methodology for calculating the risks of equipment in refinery or petrochemical plant. However, there is a major limitation of its application to the petrochemical plant directly since only a representative material is considered in calculating the risk, especially in part of the consequence of failure, even though the equipment is composed of numerous materials. The objectives of this paper are to develop an enhanced RBI program to resolve shortcoming inclusive of the above issue and to evaluate the risks of equipment in petrochemical plant using the program. In this respect, the mole fractions of materials were used to fully incorporate the characteristics of different materials. The proposed RBI program consists of qualitative, semi-quantitative and quantitative risk evaluation modules in which toxic materials as well as representative materials were selected automatically for comparison with those in the current guideline. The RBI program has been applied to evaluate the risks of equipment in Naphtha Cracking Center (NCC) which is a typical facility of petrochemical plant. Thereby, promising evaluation results were obtained and applicability of the proposed RBI program was proven.
