Abstract
The Sirikit Oil Field (S1 Asset), Thailand's largest onshore oil field, previously relied on paper-based job cards for maintenance tasks and record-keeping. Since Q1 2024, digital transformation has been implemented. This case study examines the challenges of paper records in management and analysis, showing how digital systems can improve record organization, establish a structured database, and enhance optimization and cost efficiency.
The data used in this project is sourced exclusively from S1 Asset, recorded in a digital maintenance platform which named D-MService, developed by a subsidiary of PTT Group, Thailand's national oil and gas corporation. The project, now approaching full implementation, aims to mitigate risks related to maintenance deficiencies and ensure all stakeholders have access to accurate, up-to-date information, aligning with a single source of truth. With implementation steps as:
System Assessment - Evaluating existing maintenance systems.
Data Transformation - Digitalizing the legacy SAP job card to create Digital Maintenance Job Card.
Agile Deployment - Utilizing pilot testing and deploying full phase.
Feedback Review - Collecting user feedback for continuous improvement.
At the end of Q4 2024, the implementation of Digital Maintenance Job Card has completed deployment for the S1 Asset. It covers both preventive (PM) and corrective maintenance (CM). Over 900 job card templates for more than 5,000 maintenance plans have been digitized into the system, accessible via web-based and mobile application (compatible with both iOS and Android). The preparation phase took three months. Following implementation, in the first six months, 4,339 work orders —or an 87% utilization rate—were processed using digital job cards. Initially, the system encountered challenges with urgent work (the request needs to be completed within that day) submitted without formal approval. This issue was successfully addressed by introducing an ad-hoc maintenance feature, allowing maintenance planners to issue urgent work orders, parallel approval workflow.
With the integration of in-house analytical tools, such as Power BI connected to the database on Google Cloud Platform (GCP), maintenance engineers now have direct access to data and can create their own analytical dashboards to identify equipment failures based on maintenance records. For example, Power BI enables detailed analysis of the closed drain and open drain pumps dashboard, and the instrument calibration result dashboard. Certified explosion-proof mobile devices also provide remote troubleshooting. Standardizing job cards across different locations should also be continuously refined to maximize scalability. A key challenge is the need for further integration between digital job cards and other data sources, i.e. PI OSIsoft. For future improvements, it should focus on enhancing data utilization by implementation of AI-driven analytics. It is essential to incorporate into corporate long-term maintenance strategy.
