Study on Human Integrity Management System Maturity Level for Supporting Asset Integrity and Process Safety Implementation - Sihotang, Anggiat M; Priadi, Dedi; Asral, D. Rizal (Journal of Materials Exploration and Findings, 2024)
The human factors (HF) are recognized as one of critical process safety barriers involved in normal and abnormal conditions in the oil and gas industry. In order to strengthen the HF roles as barriers we need to ensure that the actions generated are based on a valid risk assessment of the operation to be addressed by a relevant human factor analysis. Organizations within the oil and gas process have made much progress in understanding and implementing HF improvement programs. However, organizations are not always clear about what are their current situations in managing HF, their priorities for HF to be improved or where they should focus in their future plans. The objectives of this paper are to develop and propose a model called the human integrity management system (HIMS) model and the way its maturity level (HIMS-ML) is measured in managing HF related to asset integrity (AI) and process safety (PS) implementation. It nowadays becomes something urgent to be implemented but also, importantly, to identify where future efforts and strategy need to be set-up used as basis for improving HF. The proposed HIMS model introduces 5-level scale to determine the level of maturity and includes 20 key elements mainly generated from Bow-Ties model and mapping alignment with the CCPS-risk based inspection process safety (CCPS-RBPS) where 46 expectations are developed to reflect key HF issues within the process safety management system to prevent and mitigate the major accident hazard (MAH) event. This paper describes the model and the method of assessment, illustrating its use with a case study in the 3 big oil and gas operators in Indonesia. Spider chart is used to reflect the results of the maturity assessment obtained based on the response given by the relevant key persons in the organization. It can be concluded that the proposed model appears to be an effective and useful tool to measure the maturity of HF management implementation in AI and PS operation, identify the gaps and propose improvement plans.