AI-Based Optimization of Manufacturing Processes to Bring Tech Product Production Back to the USA
Strategies and Outcomes
Keywords:
Manufacturing Processes, Tech ProductAbstract
Access to high-quality products has never been more important than it is today. In this context, it is worth referring to the desire of companies to localize the production of high-margin products in order to ensure immediate delivery to consumers and shorten the time of their stay on the market, taking into account high demand and the need to use FSCW (fast secure coolware) and versioning. Created, in addition to customization, is the deliberate creation of FSCW-based cognitive products. Since cognitive product features significantly improve product value, the loss of these properties is deeply intrusive for the buyer. This, in turn, represents an opportunity for interested research teams to use efficient polynomial optimization to provide keynote papers that lead the international community. At the level of minor features, the application is also a contribution of interesting knowledge, the conclusion of which is linked to the years of refined literature.
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References
Pelluru, Karthik. "Cryptographic Assurance: Utilizing Blockchain for Secure Data Storage and Transactions." Journal of Innovative Technologies 4.1 (2021).
Nimmagadda, Venkata Siva Prakash. "AI-Powered Risk Management and Mitigation Strategies in Finance: Advanced Models, Techniques, and Real-World Applications." Journal of Science & Technology 1.1 (2020): 338-383.
Machireddy, Jeshwanth Reddy. "Integrating Machine Learning-Driven RPA with Cloud-Based Data Warehousing for Real-Time Analytics and Business Intelligence." Hong Kong Journal of AI and Medicine 4.1 (2024): 98-121.
Rachakatla, Sareen Kumar, Prabu Ravichandran, and Jeshwanth Reddy Machireddy. "Advanced Data Science Techniques for Optimizing Machine Learning Models in Cloud-Based Data Warehousing Systems." Australian Journal of Machine Learning Research & Applications 3.1 (2023): 396-419.
Potla, Ravi Teja. "Enhancing Customer Relationship Management (CRM) through AI-Powered Chatbots and Machine Learning." Distributed Learning and Broad Applications in Scientific Research 9 (2023): 364-383.
Singh, Puneet. "AI-Powered IVR and Chat: A New Era in Telecom Troubleshooting." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 143-185.
Sreerama, Jeevan, Venkatesha Prabhu Rambabu, and Chandan Jnana Murthy. "Machine Learning-Driven Data Integration: Revolutionizing Customer Insights in Retail and Insurance." Journal of Artificial Intelligence Research and Applications 3.2 (2023): 485-533.
Rambabu, Venkatesha Prabhu, Amsa Selvaraj, and Chandan Jnana Murthy. "Integrating IoT Data in Retail: Challenges and Opportunities for Enhancing Customer Engagement." Journal of Artificial Intelligence Research 3.2 (2023): 59-102.
Selvaraj, Amsa, Bhavani Krothapalli, and Venkatesha Prabhu Rambabu. "Data Governance in Retail and Insurance Integration Projects: Ensuring Quality and Compliance." Journal of Artificial Intelligence Research 3.1 (2023): 162-197.
Althati, Chandrashekar, Venkatesha Prabhu Rambabu, and Munivel Devan. "Big Data Integration in the Insurance Industry: Enhancing Underwriting and Fraud Detection." Journal of Computational Intelligence and Robotics 3.1 (2023): 123-162.
Murthy, Chandan Jnana, Venkatesha Prabhu Rambabu, and Jim Todd Sunder Singh. "AI-Powered Integration Platforms: A Case Study in Retail and Insurance Digital Transformation." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 116-162.
Venkatasubbu, Selvakumar, Venkatesha Prabhu Rambabu, and Jawaharbabu Jeyaraman. "Predictive Analytics in Retail: Transforming Inventory Management and Customer Insights." Australian Journal of Machine Learning Research & Applications 2.1 (2022): 202-246.
Althati, Chandrashekar, Venkatesha Prabhu Rambabu, and Lavanya Shanmugam. "Cloud Integration in Insurance and Retail: Bridging Traditional Systems with Modern Solutions." Australian Journal of Machine Learning Research & Applications 1.2 (2021): 110-144.
Krothapalli, Bhavani, Selvakumar Venkatasubbu, and Venkatesha Prabhu Rambabu. "Legacy System Integration in the Insurance Sector: Challenges and Solutions." Journal of Science & Technology 2.4 (2021): 62-107.
Perumalsamy, Jegatheeswari, Bhavani Krothapalli, and Chandrashekar Althati. "Machine Learning Algorithms for Customer Segmentation and Personalized Marketing in Life Insurance: A Comprehensive Analysis." Journal of Artificial Intelligence Research 2.2 (2022): 83-123.
Devan, Munivel, Bhavani Krothapalli, and Mahendher Govindasingh Krishnasingh. "Hybrid Cloud Data Integration in Retail and Insurance: Strategies for Seamless Interoperability." Journal of Artificial Intelligence Research 3.2 (2023): 103-145.
Amsa Selvaraj, Deepak Venkatachalam, and Priya Ranjan Parida, “Advanced Image Processing Techniques for Document Verification: Emphasis on US Driver’s Licenses and Paychecks”, Journal of AI-Assisted Scientific Discovery, vol. 3, no. 1, pp. 516–555, Jun. 2023
Deepak Venkatachalam, Pradeep Manivannan, and Rajalakshmi Soundarapandiyan, “Case Study on the Integration of Customer Data Platforms with MarTech and AdTech in Pharmaceutical Marketing for Enhanced Efficiency and Compliance”, J. of Artificial Int. Research and App., vol. 2, no. 1, pp. 197–235, Apr. 2022
Pradeep Manivannan, Rajalakshmi Soundarapandiyan, and Chandan Jnana Murthy, “Application of Agile Methodologies in MarTech Program Management: Best Practices and Real-World Examples”, Australian Journal of Machine Learning Research & Applications, vol. 2, no. 1, pp. 247–280, Jul. 2022
Praveen Sivathapandi, Sharmila Ramasundaram Sudharsanam, and Pradeep Manivannan. “Development of Adaptive Machine Learning-Based Testing Strategies for Dynamic Microservices Performance Optimization”. Journal of Science & Technology, vol. 4, no. 2, Mar. 2023, pp. 102-137
Priya Ranjan Parida, Chandan Jnana Murthy, and Deepak Venkatachalam, “Predictive Maintenance in Automotive Telematics Using Machine Learning Algorithms for Enhanced Reliability and Cost Reduction”, J. Computational Intel. & Robotics, vol. 3, no. 2, pp. 44–82, Oct. 2023
Rajalakshmi Soundarapandiyan, Pradeep Manivannan, and Chandan Jnana Murthy. “Financial and Operational Analysis of Migrating and Consolidating Legacy CRM Systems for Cost Efficiency”. Journal of Science & Technology, vol. 2, no. 4, Oct. 2021, pp. 175-211
Sharmila Ramasundaram Sudharsanam, Praveen Sivathapandi, and D. Venkatachalam, “Enhancing Reliability and Scalability of Microservices through AI/ML-Driven Automated Testing Methodologies”, J. of Artificial Int. Research and App., vol. 3, no. 1, pp. 480–514, Jan. 2023
Jasrotia, Manojdeep Singh. "Unlocking Efficiency: A Comprehensive Approach to Lean In-Plant Logistics." International Journal of Science and Research (IJSR) 13.3 (2024): 1579-1587.
Gayam, Swaroop Reddy. "AI-Driven Customer Support in E-Commerce: Advanced Techniques for Chatbots, Virtual Assistants, and Sentiment Analysis." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 92-123.
Nimmagadda, Venkata Siva Prakash. "AI-Powered Predictive Analytics for Retail Supply Chain Risk Management: Advanced Techniques, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 152-194.
Putha, Sudharshan. "AI-Driven Energy Management in Manufacturing: Optimizing Energy Consumption and Reducing Operational Costs." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 313-353.
Sahu, Mohit Kumar. "Machine Learning for Anti-Money Laundering (AML) in Banking: Advanced Techniques, Models, and Real-World Case Studies." Journal of Science & Technology 1.1 (2020): 384-424.
Kasaraneni, Bhavani Prasad. "Advanced Artificial Intelligence Techniques for Predictive Analytics in Life Insurance: Enhancing Risk Assessment and Pricing Accuracy." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 547-588.
Kondapaka, Krishna Kanth. "Advanced AI Techniques for Optimizing Claims Management in Insurance: Models, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 637-668.
Kasaraneni, Ramana Kumar. "AI-Enhanced Cybersecurity in Smart Manufacturing: Protecting Industrial Control Systems from Cyber Threats." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 747-784.
Pattyam, Sandeep Pushyamitra. "AI in Data Science for Healthcare: Advanced Techniques for Disease Prediction, Treatment Optimization, and Patient Management." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 417-455.
Kuna, Siva Sarana. "AI-Powered Solutions for Automated Customer Support in Life Insurance: Techniques, Tools, and Real-World Applications." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 529-560.
Sontakke, Dipti Ramrao, and Pankaj Shamrao Zanke. "AI Based Insurance Claim Assisting Device." Patent (2024): 1-17.
Machireddy, Jeshwanth Reddy, Sareen Kumar Rachakatla, and Prabu Ravichandran. "Advanced Business Analytics with AI: Leveraging Predictive Modeling for Strategic Decision-Making." Journal of AI-Assisted Scientific Discovery 3.2 (2023): 396-418.
Potla, Ravi Teja. "Hybrid Deep Learning Models for Big Data: A Case Study in Predictive Healthcare Analytics." Distributed Learning and Broad Applications in Scientific Research 10 (2024): 319-325.
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. "AI-Driven Fraud Detection in E-Commerce: Advanced Techniques for Anomaly Detection, Transaction Monitoring, and Risk Mitigation." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 124-151.
Nimmagadda, Venkata Siva Prakash. "AI-Powered Risk Assessment Models in Property and Casualty Insurance: Techniques, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 194-226.
Putha, Sudharshan. "AI-Driven Metabolomics: Uncovering Metabolic Pathways and Biomarkers for Disease Diagnosis and Treatment." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 354-391.
Sahu, Mohit Kumar. "AI-Based Supply Chain Optimization in Manufacturing: Enhancing Demand Forecasting and Inventory Management." Journal of Science & Technology 1.1 (2020): 424-464.
Kasaraneni, Bhavani Prasad. "Advanced Machine Learning Algorithms for Loss Prediction in Property Insurance: Techniques and Real-World Applications." Journal of Science & Technology 1.1 (2020): 553-597.
Kondapaka, Krishna Kanth. "Advanced AI Techniques for Retail Supply Chain Sustainability: Models, Applications, and Real-World Case Studies." Journal of Science & Technology 1.1 (2020): 636-669.
Kasaraneni, Ramana Kumar. "AI-Enhanced Energy Management Systems for Electric Vehicles: Optimizing Battery Performance and Longevity." Journal of Science & Technology 1.1 (2020): 670-708.
Pattyam, Sandeep Pushyamitra. "AI in Data Science for Predictive Analytics: Techniques for Model Development, Validation, and Deployment." Journal of Science & Technology 1.1 (2020): 511-552.
Kuna, Siva Sarana. "AI-Powered Solutions for Automated Underwriting in Auto Insurance: Techniques, Tools, and Best Practices." Journal of Science & Technology 1.1 (2020): 597-636.
Selvaraj, Akila, Mahadu Vinayak Kurkute, and Gunaseelan Namperumal. "Strategic Project Management Frameworks for Mergers and Acquisitions in Large Enterprises: A Comprehensive Analysis of Integration Best Practices." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 200-248.
Selvaraj, Amsa, Akila Selvaraj, and Deepak Venkatachalam. "Generative Adversarial Networks (GANs) for Synthetic Financial Data Generation: Enhancing Risk Modeling and Fraud Detection in Banking and Insurance." Journal of Artificial Intelligence Research 2.1 (2022): 230-269.
Krishnamoorthy, Gowrisankar, Mahadu Vinayak Kurkute, and Jeevan Sreeram. "Integrating LLMs into AI-Driven Supply Chains: Best Practices for Training, Development, and Deployment in the Retail and Manufacturing Industries." Journal of Artificial Intelligence Research and Applications 4.1 (2024): 592-627.
Paul, Debasish, Rajalakshmi Soundarapandiyan, and Praveen Sivathapandi. "Optimization of CI/CD Pipelines in Cloud-Native Enterprise Environments: A Comparative Analysis of Deployment Strategies." Journal of Science & Technology 2.1 (2021): 228-275.
Venkatachalam, Deepak, Gunaseelan Namperumal, and Amsa Selvaraj. "Advanced Techniques for Scalable AI/ML Model Training in Cloud Environments: Leveraging Distributed Computing and AutoML for Real-Time Data Processing." Journal of Artificial Intelligence Research 2.1 (2022): 131-177.
Namperumal, Gunaseelan, Deepak Venkatachalam, and Akila Selvaraj. "Enterprise Integration Post-M&A: Managing Complex IT Projects for Large-Scale Organizational Alignment." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 248-291.
Kurkute, Mahadu Vinayak, Deepak Venkatachalam, and Priya Ranjan Parida. "Enterprise Architecture and Project Management Synergy: Optimizing Post-M&A Integration for Large-Scale Enterprises." Journal of Science & Technology 3.2 (2022): 141-182.
Soundarapandiyan, Rajalakshmi, Gowrisankar Krishnamoorthy, and Debasish Paul. "The Role of Infrastructure as Code (IaC) in Platform Engineering for Enterprise Cloud Deployments." Journal of Science & Technology 2.2 (2021): 301-344.
Sivathapandi, Praveen, Rajalakshmi Soundarapandiyan, and Gowrisankar Krishnamoorthy. "Platform Engineering for Multi-Cloud Enterprise Architectures: Design Patterns and Best Practices." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 132-183.
Sudharsanam, Sharmila Ramasundaram, Venkatesha Prabhu Rambabu, and Yeswanth Surampudi. "Scaling CI/CD Pipelines in Microservices Architectures for Large Enterprises: Performance and Reliability Considerations." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 115-160.
Prabu Ravichandran. “Analysis on Agile Software Development Using Cloud Computing Based on Agile Methodology and Scrum Framework”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 12, no. 2, Sept. 2024, pp. 865-71