AI in Aircraft Airworthiness Management in Bhutan: Prediction of Aircraft Maintenance Cost

What is it about?

This paper explores how ARIMA models can aid in managing aircraft safety and maintenance in Bhutan. By analyzing historical records from 2016 to 2023—including regulations, audits, maintenance costs, and inspections—the model predicts future trends up to 2026. These predictions assist in planning maintenance, inspections, and audits in advance, making aircraft upkeep more efficient and proactive. Utilizing ARIMA models for time series analysis provides valuable insights that enhance decision-making in airworthiness management. While it is just one of many available tools, this method can contribute to ensuring that aircraft remain safe and well-maintained.

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Photo by vineet singh on Unsplash

Photo by vineet singh on Unsplash

Why is it important?

This paper is important as it explores how ARIMA models can predict maintenance costs, audit schedules, and inspections, enabling efficient and data-driven decision-making in Bhutan’s aviation sector. By identifying the most suitable ARIMA model for analyzing and forecasting aviation data, it ensures accurate predictions that help optimize airworthiness management. Additionally, the study aims to inspire further research and encourage continuous improvement and innovation in Bhutan’s aviation industry. By leveraging data analytics, this approach supports proactive maintenance planning, enhances safety, and contributes to the long-term sustainability of aviation operations in the country.