MATEC Web Conf.
Volume 281, 2019International Conference of Engineering Risk (INCER 2019)
|Number of page(s)||6|
|Section||Fault Tolerant Systems, Diagnosis and Prognosis|
|Published online||21 May 2019|
A Systemic Risk Management Model to Manage the Equipment Maintenance System in Oil and Gas Companies
1 Researcher, Risk Engineering Master (REM), Faculty of Engineering, Cairo University (CUFE), Egypt
2 Professor of Petroleum Engineering, CUFE, Coordinator of REM, Egypt
The risk management is significant when managing the equipment maintenance system (EMS) which is very important to maintain equipment operations and is fundamental for achieving business objectives. With the advent of risk-based thinking in industry, there was a need for introducing the risk culture within the organization, including maintenance, in order to reduce business losses. Analysis of equipment failures data showed a relation between the failures types with their consequences, and all interaction with system maintenance components. The ineffective maintenance system may cause multiple losses for the organization and therefore affects the whole business. This paper introduces a systemic risk management model to manage the maintenance system undesired events and control the impact on the organization and the consequences on business. Using systemic risk management model, the maintenance professional can manage the whole maintenance system through risk analysis, assessment, and management by creating the different risk scenarios to develop proper types of control.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.