روشی بدیع در فرایند کاوی آگاه از زمینه برای کشف علل اصلی گلوگاه ها و عدم تطابق با فرایند طراحی شده مبتنی بر هوش مصنوعی

In today’s world, improving efficiency and reducing costs in logistics services are critical challenges for organizations, as bottlenecks and process non-conformities can significantly disrupt performance and competitiveness. this research, using a process mining approach, aims to identify and analyze these issues in detail. data related to logistics processes were collected from organizational management systems, and after cleaning, were analyzed using k-prototype models for clustering, random forest classifier for prediction, and apriori for discovering association rules. the results indicate that process mining can effectively identify bottlenecks and process inconsistencies, providing innovative solutions to improve operational times, reduce costs, and enhance process alignment with designed models. this study highlights the importance and effectiveness of process mining in improving performance and increasing the competitiveness of logistics services.