AI-Driven Predictive Maintenance Models for Supply Chain Optimization: Case Studies and Insights

Professor Michael Brown

Abstract


Predictive maintenance powered by artificial intelligence (AI) holds significant potential for optimizing supply chain operations and minimizing disruptions. This paper presents case studies and insights into AI-driven predictive maintenance models in the context of supply chain management. Through empirical analysis and industry examples, we demonstrate the effectiveness of AI in enabling proactive maintenance strategies and enhancing supply chain resilience.


 


References


Gutta, L. M., Bammidi, T. R., Batchu, R. K., & Kanchepu, N. (2024). REAL-TIME REVELATIONS: ADVANCED DATA ANALYSIS TECHNIQUES. International Journal of Sustainable Development Through AI, ML and IoT, 3(1), 1-22.

Singhal, S., Kothuru, S. K., Sethibathini, V. S. K., & Bammidi, T. R. (2024). ERP EXCELLENCE A DATA GOVERNANCE APPROACH TO SAFEGUARDING FINANCIAL TRANSACTIONS. International Journal of Managment Education for Sustainable Development, 7(7), 1-18.

Pansara, R. (2023). From Fields to Factories A Technological Odyssey in Agtech and Manufacturing. International Journal of Managment Education for Sustainable Development, 6(6), 13-23.

Pansara, R. (2023). Navigating Data Management in the Cloud-Exploring Limitations and Opportunities. Transactions on Latest Trends in IoT, 6(6), 57-66.

Pansara, R. (2023). Review & Analysis of Master Data Management in Agtech & Manufacturing industry. International Journal of Sustainable Development in Computing Science, 5(3), 51-59.

Oku, K., krishna Vaddy, R., Yada, A., & Batchu, R. K. (2024). DATA ENGINEERING EXCELLENCE: A CATALYST FOR ADVANCED DATA ANALYTICS IN MODERN ORGANIZATIONS. International Journal of Creative Research In Computer Technology and Design, 6(6), 1-10.

Krishnamurthy, O. (2023). Genetic Algorithms, Data Analytics and it’s applications, Cybersecurity: verification systems. International Transactions in Artificial Intelligence, 7(7), 1-25.

Krishnamurthy, O. (2023). A mathematical approach (matrix multiplication), General data science. International Journal of Sustainable Development in Computing Science, 5(2), 1-22.

Pillai, S. E. V. S., & Polimetla, K. (2024, February). Privacy-Preserving Network Traffic Analysis Using Homomorphic Encryption. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-6). IEEE.

Pillai, S. E. V. S., & Polimetla, K. (2024, February). Enhancing Network Privacy through Secure Multi-Party Computation in Cloud Environments. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-6). IEEE

Pansara, Ronak. "“MASTER DATA MANAGEMENT IMPORTANCE IN TODAY’S ORGANIZATION." International Journal of Management (IJM)12.10 (2021).

Ronak Pansara, Master Data Management Challenges, International Journal of Computer Science and Mobile Computing, Vol.10 Issue.10, October- 2021, pg. 47-49

Pansara, R. (2023). MDM Governance Framework in the Agtech & Manufacturing Industry. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.


Refbacks

  • There are currently no refbacks.