Capital projects in the energy sector continue to experience systemic cost overruns and schedule delays. While AI-driven predictive analytics promise improved foresight, their effectiveness is often limited by fragmented data landscapes, inconsistent reporting practices, and weak governance. This paper introduces a d...
Fuad Shalan, Sarafudheen M. Tharayil, Rawabi Aldossary et al.· GOTECH· 0 citations
Results demonstrate that the agent successfully identifies multiple concurrent root causes, produces actionable maintenance steps, and generalizes to synthetic failures, establishing a scalable, explainable framework for intelligent industrial maintenance.
Sarafudheen M. Tharayil, Dalia A. Albuqytah, Fuad Shalaan et al.· GOTECH· 0 citations
A metadata-driven automation framework that leverages AI-assisted refactoring and Python-based pipelines to accelerate migration while maintaining functional correctness is presented, providing a scalable blueprint for enterprise-wide BI modernization.
Sarafudheen M. Tharayil, Nouf F. Alzahrani, Bala Koppuravuri et al.· GOTECH· 0 citations
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