TIS: Three-Tiered Intelligent Supply Chain Management to Enhance Quality and Supervision

Efficient supplier management and collaboration with top-tier suppliers are crucial for maintaining competitiveness in today's automotive industry, where competition is fierce, and globalization presents both challenges and opportunities. This study introduces an innovative approach that harnesses artificial intelligence with the aim of Digital Transformation and implements Industry 4.0 for the automotive industry to improve supply chain operations by establishing a tiered and hierarchical system. The proposed approach helps minimize errors, prevent fraud, and enhance product quality in this industry. The methodology involves extracting key features from supplier data, applying the K-means algorithm for clustering, and implementing a hierarchical system for efficient supplier management. Furthermore, techniques like Gartner Magic Quadrant charts are incorporated to increase understanding and support decisions for company experts to overcome challenges and enhance decision-making in selecting and contracting with stable suppliers. We can consolidate our suppliers to a small number of delegates to represent suppliers per system, reducing our contracts by 84.33% - 92.17% and improving operational efficiency by using this system in the company of this case study. Moreover, by reducing the number of unique parts by 99.66%, we aim to simplify logistics, optimize supply chain operations, and improve inventory management. Additionally, implementing this intelligent system can reduce the workforce directly involved in these operations by 93.290/0 and save 39,180,000 person-hours over 20 years. The results show that this approach effectively categorizes suppliers, highlights key evaluation criteria, and supports decision-making processes. Ultimately, this leads to a more efficient supply chain, improved overall performance, and increased company revenue.