The competition's theme was “Advanced Asset Integrity Management System (AIMS) for a Resilient Industrial Future”. It was organized through a collaboration between PT Pertamina Maintenance and Construction (PertaMC) and Pertamina University.

With their paper titled “Optimization of Asset Integrity Management System (AIMS) Based on Bayesian Network with the Integration of Artificial Intelligence, Machine Learning, and Keyword Analysis”, the SDG ITB Team proposed an innovative solution to enhance the resilience and sustainability of the oil and gas industry.

One of the team members, Ghifari, explained that their insights into these three technologies were derived from extensive literature research, validated through cross-referencing international journals and scientific papers.

“We gathered our findings from literature studies based on previous research. To ensure accuracy, we cross-checked them against papers and international journals related to these three technologies,” he said.

In their paper, the SDG ITB team explained several major challenges faced by Indonesia's oil and gas sector, which supplies 45.32% of the nation's energy needs. According to data, this industry recorded more than 2 million casualties from 982 workplace incidents between 2016 and 2022, along with 63,445 barrels of oil spills. One of the most devastating fire incidents occurred at the Balongan Refinery, resulting in losses of up to Rp1.25 trillion. These alarming statistics underscore the urgent need for technology-driven solutions to reduce operational failures and improve asset management efficiency.

^{SDG ITB Team’s Poster in PERFORMANCE 2024 Scientific Writing Competition}

To address this, the SDG ITB team proposed to optimize the Asset Integrity Management System (AIMS) in the oil and gas industry through an integrated technological approach. Their model combines Machine Learning, Keyword Analysis, and Bayesian Networks to enable predictive data analysis and operational risk mapping. By incorporating Risk-Based Inspection (RBI) and predictive maintenance, the system has the potential to reduce equipment failure by 54.78% and minimize human error by 24.23%, enhancing efficiency and fostering a sustainable safety culture.

The diverse academic background of the SDG ITB Team, with members from three distinct academic backgrounds, played a crucial role in shaping their innovative approach and delivering high-quality collaborative research.

“Ghifar (Petroleum Engineering) focused on ensuring that our solution can be implemented with industry standards and practices in oil and gas. Dzaky (Bioengineering) focused on integrating the solution into Health, Safety, and Environment (HSE) strategies and ensuring its long-term sustainability. Meanwhile, I (Information Systems and Technology) focused on the algorithm’s functionality and its integration into existing systems,” explained Syakira.

With the adoption of advanced technologies, the SDG ITB team hopes to foster a stronger safety culture in the oil and gas industry. “It is hoped that the number of incidents in the oil and gas sector can be minimized, to reduce both material and non-material losses,” concluded Dzaky.

Translator: Nabila Puspita (Bioengineering, 2022)