The Impact of Machine Learning on Sustainable Manufacturing Practices in the USA with a Focus on Defense Sector
Keywords:
Sustainable Manufacturing, Defense SectorAbstract
Sustainable manufacturing and machine learning technologies have the potential to transform manufacturing processes and operations around the world. These two capabilities are significant for the USA as its manufacturing policy is currently shifting towards being connected to the same aspect of commercial and defense sectors through different policies. Though there are many works on the smart manufacturing process, very few examine the decision making in sustainable and smart manufacturing process. There are very few works to investigate the impact of machine learning technologies on sustainable manufacturing practices. This synthesis aims to examine the role of machine learning technologies in the sustainable manufacturing practices in the USA and particularly focuses on the defense sector.
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References
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.
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.
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.
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.
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.
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.
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.
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.
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.
Kuna, Siva Sarana. "Reinforcement Learning for Optimizing Insurance Portfolio Management." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 289-334.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Selvaraj, Akila, Praveen Sivathapandi, and Deepak Venkatachalam. "Artificial Intelligence-Enhanced Telematics Systems for Real-Time Driver Behaviour Analysis and Accident Prevention in Modern Vehicles." Journal of Artificial Intelligence Research 3.1 (2023): 198-239.
Paul, Debasish, Gowrisankar Krishnamoorthy, and Sharmila Ramasundaram Sudharsanam. "Platform Engineering for Continuous Integration in Enterprise Cloud Environments: A Case Study Approach." Journal of Science & Technology 2.3 (2021): 179-214.
Namperumal, Gunaseelan, Akila Selvaraj, and Priya Ranjan Parida. "Optimizing Talent Management in Cloud-Based HCM Systems: Leveraging Machine Learning for Personalized Employee Development Programs." Journal of Science & Technology 3.6 (2022): 1-42.
Soundarapandiyan, Rajalakshmi, Priya Ranjan Parida, and Yeswanth Surampudi. "Comprehensive Cybersecurity Framework for Connected Vehicles: Securing Vehicle-to-Everything (V2X) Communication Against Emerging Threats in the Automotive Industry." Cybersecurity and Network Defense Research 3.2 (2023): 1-41.
Sivathapandi, Praveen, Debasish Paul, and Akila Selvaraj. "AI-Generated Synthetic Data for Stress Testing Financial Systems: A Machine Learning Approach to Scenario Analysis and Risk Management." Journal of Artificial Intelligence Research 2.1 (2022): 246-287.
Sudharsanam, Sharmila Ramasundaram, Deepak Venkatachalam, and Debasish Paul. "Securing AI/ML Operations in Multi-Cloud Environments: Best Practices for Data Privacy, Model Integrity, and Regulatory Compliance." Journal of Science & Technology 3.4 (2022): 52-87.
