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A risk-based shutdown inspection and maintenance interval estimation considering human error

journal contribution
posted on 2023-05-19, 10:16 authored by Hameed, A, Faisal KhanFaisal Khan, Ahmed, S
This paper presents a risk-based methodology to estimate shutdown inspection and maintenance interval by integrating human errors with degradation modeling of a processing unit. The methodology presented in this paper addresses to identify the number of shutdown intervals required to achieve a target reliability over a goal period. The proposed methodology is the extension of the previously published work by the authors to determine the shutdown interval considering the system's desired availability. The proposed work is novel in the sense that a concept of human error during shutdown inspection and maintenance is introduced while modeling the system failure. Selection of critical equipment is the most important aspect in obtaining the shutdown interval to minimize overall operational risk. In order to achieve this, a risk criticality matrix is proposed to select the critical equipment for shutdown inspection and maintenance. Probability of human error induced during shutdown inspection and maintenance is estimated using Success Likelihood methodology (SLIM). The proposed methodology is composed of three steps namely, equipment selection considering criticality of operation, system failure modeling considering human error and finally a risk-based shutdown inspection and maintenance interval estimation. The proposed methodology is applied to a gas chilling and liquefaction unit of a hydrocarbon processing facility. The methodology is used to ensure the practicality of the proposed formulation to the real industry. The proposed methodology can be applied to any plant (process or non-process) such as those for LNG processing, petrochemicals, refineries or manufacturing plants. The key elements for the success of the proposed methodology are the identification and selection of critical equipment, breakdown of activities to estimate human error probability and plant-specific data for modeling system failures.

History

Publication title

Process Safety and Environmental Protection

Volume

100

Pagination

9-21

ISSN

0957-5820

Department/School

Australian Maritime College

Publisher

Elsevier Ltd

Place of publication

United Kingdom

Rights statement

© 2015 The Institution of Chemical Engineers

Repository Status

  • Restricted

Socio-economic Objectives

Oil and gas processing