Assoc. Prof. Dr. Aytac Aydın Research contributions focus on advancing quality management and performance appraisal within the forest products and wood-based materials industry through the systematic application of statistical analysis and artificial intelligence techniques. The work integrates process optimization, quality control modeling, and ergonomics to enhance productivity, material efficiency, and workplace safety across manufacturing environments. Multiple completed and ongoing research projects have addressed critical challenges in the evaluation of production performance, defect reduction, operational efficiency, and sustainable resource utilization. Innovative methodologies, including multi-criteria decision-making models, predictive analytics, and machine learning algorithms, have been applied to improve decision accuracy in material selection, process planning, and quality inspection. Published studies in SCI-indexed journals contribute valuable data-driven insights to both academia and industry, strengthening standards in forest industrial engineering and promoting evidence-based operational strategies. Research outcomes support environmentally responsible production while increasing economic efficiency in wood-based manufacturing systems. In addition, contributions extend to guiding postgraduate and doctoral-level research focused on quality systems, process improvement, and industrial performance metrics. These efforts collectively strengthen the scientific foundation of forest industry management, drive technological advancement, and support sustainable and intelligent manufacturing practices with a long-term impact on both regional and international forestry-based production sectors.