Prof. Dr. Khairur Rijal Jamaludin

Over the past 15 years, Professor Khairur Rijal Jamaludin’s scholarly publications have consistently focused on advancing Quality Engineering, Robust Design, and data-driven manufacturing systems, with a strong emphasis on real-world industrial applicability. His papers span key themes including Mahalanobis–Taguchi System (MTS) enhancement, feature selection and optimization using swarm intelligence and metaheuristics, robust predictive analytics, and AI-enabled decision-making for manufacturing, healthcare, and energy systems. He has also published extensively on lean operations, Industry 4.0 readiness, sustainable energy and quality integration, and advanced materials processing such as metal injection molding, powder metallurgy, and composite materials. His work appears in reputable Web of Science–indexed journals across Q1–Q4 quartiles, reflecting both methodological depth and interdisciplinary reach, and has contributed to practical frameworks, validated models, and hybrid algorithms that strengthen explainability, robustness, and reliability in complex engineering systems