Vol. 4 No. 2 (2024): African Journal of Artificial Intelligence and Sustainable Development
Articles

The Application of Natural Language Processing in Enhancing Communication within U.S. Manufacturing Supply Chains: Methods and Case Studies

PDF
  • Prof. Hao Lin
Prof. Hao Lin
Chair of AI and Machine Learning, Tsinghua University, Beijing, China

Published 07-09-2024

Keywords

  • Natural Language Processing,
  • Manufacturing Supply Chains,
  • Enhancing Communication
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Prof. Hao Lin, “The Application of Natural Language Processing in Enhancing Communication within U.S. Manufacturing Supply Chains: Methods and Case Studies”, African J. of Artificial Int. and Sust. Dev., vol. 4, no. 2, pp. 193–209, Sep. 2024, Accessed: Nov. 21, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/160

Abstract

With the rise of globalization and emerging markets, the manufacturing supply chain has become more strained and complex. In complementary to the globalized landscape, the COVID-19 pandemic unveiled numerous vulnerabilities in the country's supply chain network. As the demand for manufactured goods and industrial supplies increases in the United States, understanding and using the latest technologies for improved communication with supply chain partners becomes a necessity. Increased communication with supply chain partners may assist in mitigating the risks arising from the rapid change in the manufacturing landscape. Recent advances in Natural Language Processing (NLP) and its supporting Artificial Intelligence (AI) technologies have promoted several innovative tools and solutions for enhanced communication with supply chain networks. However, such tools and technologies have been tricky to adopt in the manufacturing industry due to the industrial barriers and challenges. This paper discusses recent studies and case studies related to the implementation and adoption of Natural Language Processing (NLP) technologies and tools to augment communication within the primarily unstructured communication landscape of the U.S. Manufacturing Supply Chain Network.

PDF

Downloads

Download data is not yet available.

References

  1. Sengottaiyan, Krishnamoorthy, and Manojdeep Singh Jasrotia. "Relocation of Manufacturing Lines-A Structured Approach for Success." International Journal of Science and Research (IJSR) 13.6 (2024): 1176-1181.
  2. Gayam, Swaroop Reddy. "Artificial Intelligence for Natural Language Processing: Techniques for Sentiment Analysis, Language Translation, and Conversational Agents." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 175-216.
  3. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Compliance and Regulatory Reporting in Banking: Advanced Techniques, Models, and Real-World Applications." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 151-189.
  4. Putha, Sudharshan. "AI-Driven Natural Language Processing for Voice-Activated Vehicle Control and Infotainment Systems." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 255-295.
  5. Sahu, Mohit Kumar. "Machine Learning Algorithms for Personalized Financial Services and Customer Engagement: Techniques, Models, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 272-313.
  6. Kasaraneni, Bhavani Prasad. "Advanced Machine Learning Models for Risk-Based Pricing in Health Insurance: Techniques and Applications." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 170-207.
  7. Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Models for Predictive Analytics in Insurance: Techniques, Applications, and Real-World Case Studies." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 244-290.
  8. Kasaraneni, Ramana Kumar. "AI-Enhanced Pharmacoeconomics: Evaluating Cost-Effectiveness and Budget Impact of New Pharmaceuticals." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 291-327.
  9. Pattyam, Sandeep Pushyamitra. "AI-Driven Data Science for Environmental Monitoring: Techniques for Data Collection, Analysis, and Predictive Modeling." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 132-169.
  10. Kuna, Siva Sarana. "Reinforcement Learning for Optimizing Insurance Portfolio Management." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 289-334.
  11. Gayam, Swaroop Reddy, Ramswaroop Reddy Yellu, and Praveen Thuniki. "Artificial Intelligence for Real-Time Predictive Analytics: Advanced Algorithms and Applications in Dynamic Data Environments." Distributed Learning and Broad Applications in Scientific Research 7 (2021): 18-37.
  12. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Customer Behavior Analysis in Insurance: Advanced Models, Techniques, and Real-World Applications." Journal of AI in Healthcare and Medicine 2.1 (2022): 227-263.
  13. Putha, Sudharshan. "AI-Driven Personalization in E-Commerce: Enhancing Customer Experience and Sales through Advanced Data Analytics." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 225-271.
  14. Sahu, Mohit Kumar. "Machine Learning for Personalized Insurance Products: Advanced Techniques, Models, and Real-World Applications." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 60-99.
  15. Kasaraneni, Bhavani Prasad. "AI-Driven Approaches for Fraud Prevention in Health Insurance: Techniques, Models, and Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 136-180.
  16. Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Techniques for Demand Forecasting in Retail Supply Chains: Models, Applications, and Real-World Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 180-218.
  17. Kasaraneni, Ramana Kumar. "AI-Enhanced Portfolio Optimization: Balancing Risk and Return with Machine Learning Models." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 219-265.
  18. Pattyam, Sandeep Pushyamitra. "AI-Driven Financial Market Analysis: Advanced Techniques for Stock Price Prediction, Risk Management, and Automated Trading." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 100-135.
  19. Kuna, Siva Sarana. "The Impact of AI on Actuarial Science in the Insurance Industry." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 451-493.
  20. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Dynamic Pricing in Insurance: Advanced Techniques, Models, and Real-World Application." Hong Kong Journal of AI and Medicine 4.1 (2024): 258-297.
  21. Selvaraj, Akila, Praveen Sivathapandi, and Rajalakshmi Soundarapandiyan. "Blockchain-Based Cybersecurity Solutions for Automotive Industry: Protecting Over-the-Air (OTA) Software Updates in Autonomous and Connected Vehicles." Cybersecurity and Network Defense Research 3.2 (2023): 86-134.
  22. Paul, Debasish, Gunaseelan Namperumal, and Akila Selvaraj. "Cloud-Native AI/ML Pipelines: Best Practices for Continuous Integration, Deployment, and Monitoring in Enterprise Applications." Journal of Artificial Intelligence Research 2.1 (2022): 176-231.
  23. Namperumal, Gunaseelan, Sharmila Ramasundaram Sudharsanam, and Rajalakshmi Soundarapandiyan. "Data-Driven Workforce Management in Cloud HCM Solutions: Utilizing Big Data and Analytics for Strategic Human Resources Planning." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 549-591.
  24. Soundarapandiyan, Rajalakshmi, Yeswanth Surampudi, and Akila Selvaraj. "Intrusion Detection Systems for Automotive Networks: Implementing AI-Powered Solutions to Enhance Cybersecurity in In-Vehicle Communication Protocols." Cybersecurity and Network Defense Research 3.2 (2023): 41-86.
  25. Sudharsanam, Sharmila Ramasundaram, Praveen Sivathapandi, and Yeswanth Surampudi. "Cloud-Based Telematics and Real-Time Data Integration for Fleet Management: A Comprehensive Analysis of IoT-Driven Predictive Analytics Models." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 622-657.
  26. Prabu Ravichandran. “Extensive Experience in Aws Services in Develop and Deploying and Highly Available, Scalable and Fault Tolerant Systems”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 12, no. 2, Sept. 2024, pp. 856-64

Similar Articles

You may also start an advanced similarity search for this article.