AI-Based Optimization of Manufacturing Processes to Bring Pharma Production Back to the USA: Strategies and Outcomes
Keywords:
Manufacturing Processes, Pharma Production, OptimizationAbstract
Reassuring and improving the U.S. manufacturing base requires a level of automation and AI-enabled optimization that could virtually eliminate the cost differential between domestic and overseas manufacture. The pharmaceutical industry is particularly well-suited for this kind of re-visioning because a significant proportion of the production equipment and processes within the U.S. are older and overused, while production facilities distributed around the world are more modern, with international organizations being willing partners in the construction of new, compliant domestic facilities. In the post-modern American economy, artificial intelligence (AI) will transform the way we think about the positioning of worldwide pharma facilities, dropping costs to the point that the tariff differential would be more than covered by cost savings and the expense of moving product to a number of strategic places domestically.
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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. "Agile Project Management in Mergers and Acquisitions: Accelerating Enterprise Integration in Large Organizations." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 295-334.
Selvaraj, Amsa, Praveen Sivathapandi, and Gunaseelan Namperumal. "Privacy-Preserving Synthetic Data Generation in Financial Services: Implementing Differential Privacy in AI-Driven Data Synthesis for Regulatory Compliance." Journal of Artificial Intelligence Research 2.1 (2022): 203-247.
Paul, Debasish, Sharmila Ramasundaram Sudharsanam, and Yeswanth Surampudi. "Implementing Continuous Integration and Continuous Deployment Pipelines in Hybrid Cloud Environments: Challenges and Solutions." Journal of Science & Technology 2.1 (2021): 275-318.
Venkatachalam, Deepak, Debasish Paul, and Akila Selvaraj. "AI/ML Powered Predictive Analytics in Cloud Based Enterprise Systems: A Framework for Scalable Data-Driven Decision Making." Journal of Artificial Intelligence Research 2.2 (2022): 142-183.
Namperumal, Gunaseelan, Chandan Jnana Murthy, and Sharmila Ramasundaram Sudharsanam. "Integrating Artificial Intelligence with Cloud-Based Human Capital Management Solutions: Enhancing Workforce Analytics and Decision-Making." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 456-502.
Kurkute, Mahadu Vinayak, Akila Selvaraj, and Amsa Selvaraj. "End-to-End Cybersecurity Strategies for Autonomous Vehicles: Leveraging Multi-Layered Defence Mechanisms to Safeguard Automotive Ecosystems." Cybersecurity and Network Defense Research 3.2 (2023): 134-177.
Soundarapandiyan, Rajalakshmi, Sharmila Ramasundaram Sudharsanam, and Debasish Paul. "Integrating Kubernetes with CI/CD Pipelines in Cloud Computing for Enterprise Applications." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 161-200.
Sivathapandi, Praveen, Debasish Paul, and Sharmila Ramasundaram Sudharsanam. "Enhancing Cloud-Native CI/CD Pipelines with AI-Driven Automation and Predictive Analytics." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 226-265.
Sudharsanam, Sharmila Ramasundaram, Gunaseelan Namperumal, and Priya Ranjan Parida. "Risk Management in Large-Scale Mergers and Acquisitions: Project Management Techniques for Ensuring Enterprise Integration Success." Journal of Science & Technology 3.1 (2022): 79-116.
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
