Enhancing Quality Control in Medical Devices Supply Chain Using Artificial Intelligence and Machine Learning


  • Phani Chandra Barla Senseonics Inc.,20451 Seneca Meadows Parkway, Germantown, MD 20876-7005, USA


Medical Devices, Supply chain, Artificial intelligence, Machine learning


Due to its significance, it plays in the management of public health, the healthcare industry is among the most important sectors. The rapid spread of several diseases, most notably the COVID-19 pandemic, has put this sector of the economy in the spotlight. The healthcare supply chain (HSC) has had its weaknesses exposed by the pandemic. The healthcare supply chain is undergoing a period of revolutionary change due to new inventions such as the advent of various cutting-edge technologies such as Industry 4.0 and artificial intelligence. Within the context of a growing economy, this research aims to identify the most critical success factors for using AI in HRM. Using an approximation of SWARA, the HSC ranks CSFs of AI adoption. According to the findings, technological (TEC) factors have the greatest impact on the adoption of AI in HCI within the setting of developing nations. The following dimensions pertain to human beings, groups, and institutions: INT, HUM, and ORG.


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How to Cite

Phani Chandra Barla. (2024). Enhancing Quality Control in Medical Devices Supply Chain Using Artificial Intelligence and Machine Learning. American Scientific Research Journal for Engineering, Technology, and Sciences, 98(1), 1–11. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/10338