Cognitive Manufacturing: A Hybrid AI - Kepner Tregoe Framework for Predictive Root Cause Analysis in Saudi Arabia's Industry 4.0

Saudi Arabia isn't just upgrading its industrial sector; it is completely rewriting theoperational blueprint. Driven by the National Industrial Development and Logistics Program (NIDLP),the push toward Industry 4.0 has placed advanced smart factories at the heart of Vision 2030. Thesefacilities rely entirely on the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) forpredictive maintenance. The problem? AI is largely a "black box." It flags anomalies but rarelyexplains the logic behind them. This forces engineers into a dangerous cycle: executing costly,unjustified production halts or ignoring critical warnings. Furthermore, merging operationaltechnology (OT) with IT networks exposes sensitive industrial databases to unprecedented cyber risks.Objective: Relying solely on automated AI predictions in high-stakes manufacturing is a criticalvulnerability. This paper introduces a customized operational model: the "Hybrid AI-Kepner TregoeFramework for Predictive Root Cause Analysis (AI-KT PRCA)." The goal is to build a bridge betweenalgorithmic anomaly detection and human rational logic. This ensures that industrial anomalies areverified, resolved, and secured against global IT standards before a multi-million riyal assembly line isshut down.