Vol. 4 No. 2 (2024): Journal of AI-Assisted Scientific Discovery
Articles

Leveraging AI for Process Optimization in Tech Product Manufacturing: Case Studies in Mobile, Laptops, and Semiconductor Industries

PDF
  • Dr. Daniel Koppelman
Dr. Daniel Koppelman
Professor of Computer Science, University of Haifa, Israel
Cover

Published 03-10-2024

Keywords

  • Process Optimization,
  • Tech Product Manufacturing,
  • Semiconductor Industries
Creative Commons License

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

How to Cite

[1]
Dr. Daniel Koppelman, “Leveraging AI for Process Optimization in Tech Product Manufacturing: Case Studies in Mobile, Laptops, and Semiconductor Industries”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 2, pp. 136–157, Oct. 2024, Accessed: Nov. 24, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/154

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have become integral in the manufacturing industry, particularly in optimizing processes within the tech product manufacturing sector. [1] emphasize the significance of AI technologies such as ML, knowledge graphs, and human-computer interaction in improving system performance metrics within manufacturing. They highlight the role of intelligent manufacturing systems, which encompass smart manufacturing devices and intelligent manufacturing services, and the utilization of ML algorithms at the device layer to meet real-time requirements. Moreover, AI is employed in wireless channel prediction, mobile network handoff optimization, and network congestion control, demonstrating the diverse applications of AI in manufacturing.

Furthermore, [2] underscore the development of centralized and automated real-time monitoring systems using machine learning-based techniques to reduce labor costs and enhance energy efficiency in smart manufacturing. They discuss the deployment of intelligent data analysis, real-time supervision, and IoT techniques, as well as the application of deep learning-based object detection and text recognition methods in industrial production supervision. These references collectively illustrate the broad spectrum of AI applications in manufacturing, setting the stage for understanding the subsequent case studies in mobile, laptop, and semiconductor industries.

PDF

Downloads

Download data is not yet available.

References

  1. Pelluru, Karthik. "Integrate security practices and compliance requirements into DevOps processes." MZ Computing Journal 2.2 (2021): 1-19.
  2. 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.
  3. Machireddy, Jeshwanth Reddy, and Harini Devapatla. "Leveraging Robotic Process Automation (RPA) with AI and Machine Learning for Scalable Data Science Workflows in Cloud-Based Data Warehousing Environments." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 234-261.
  4. Potla, Ravi Teja. "Integrating AI and IoT with Salesforce: A Framework for Digital Transformation in the Manufacturing Industry." Journal of Science & Technology 4.1 (2023): 125-135.
  5. Singh, Puneet. "Streamlining Telecom Customer Support with AI-Enhanced IVR and Chat." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 443-479.
  6. Sreerama, Jeevan, Mahendher Govindasingh Krishnasingh, and Venkatesha Prabhu Rambabu. "Machine Learning for Fraud Detection in Insurance and Retail: Integration Strategies and Implementation." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 205-260.
  7. Rambabu, Venkatesha Prabhu, Munivel Devan, and Chandan Jnana Murthy. "Real-Time Data Integration in Retail: Improving Supply Chain and Customer Experience." Journal of Computational Intelligence and Robotics 3.1 (2023): 85-122.
  8. 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.
  9. Krothapalli, Bhavani, Lavanya Shanmugam, and Jim Todd Sunder Singh. "Streamlining Operations: A Comparative Analysis of Enterprise Integration Strategies in the Insurance and Retail Industries." Journal of Science & Technology 2.3 (2021): 93-144.
  10. Amsa Selvaraj, Priya Ranjan Parida, and Chandan Jnana Murthy, “AI/ML-Based Entity Recognition from Images for Parsing Information from US Driver’s Licenses and Paychecks”, Journal of AI-Assisted Scientific Discovery, vol. 3, no. 1, pp. 475–515, May 2023
  11. Deepak Venkatachalam, Pradeep Manivannan, and Jim Todd Sunder Singh, “Enhancing Retail Customer Experience through MarTech Solutions: A Case Study of Nordstrom”, J. Sci. Tech., vol. 3, no. 5, pp. 12–47, Sep. 2022
  12. Pradeep Manivannan, Deepak Venkatachalam, and Priya Ranjan Parida, “Building and Maintaining Robust Data Architectures for Effective Data-Driven Marketing Campaigns and Personalization”, Australian Journal of Machine Learning Research & Applications, vol. 1, no. 2, pp. 168–208, Dec. 2021
  13. Praveen Sivathapandi, Priya Ranjan Parida, and Chandan Jnana Murthy. “Transforming Automotive Telematics With AI/ML: Data Analysis, Predictive Maintenance, and Enhanced Vehicle Performance”. Journal of Science & Technology, vol. 4, no. 4, Aug. 2023, pp. 85-127
  14. Priya Ranjan Parida, Jim Todd Sunder Singh, and Amsa Selvaraj, “Real-Time Automated Anomaly Detection in Microservices Using Advanced AI/ML Techniques”, J. of Artificial Int. Research and App., vol. 3, no. 1, pp. 514–545, Apr. 2023
  15. Sharmila Ramasundaram Sudharsanam, Pradeep Manivannan, and Deepak Venkatachalam. “Strategic Analysis of High Conversion Ratios from Marketing Qualified Leads to Sales Qualified Leads in B2B Campaigns: A Case Study on High MQL-to-SQL Ratios”. Journal of Science & Technology, vol. 2, no. 2, Apr. 2021, pp. 231-269
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. Sengottaiyan, Krishnamoorthy, and Manojdeep Singh Jasrotia. "SLP (Systematic Layout Planning) for Enhanced Plant Layout Efficiency." International Journal of Science and Research (IJSR) 13.6 (2024): 820-827.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. Selvaraj, Akila, Deepak Venkatachalam, and Jim Todd Sunder Singh. "Advanced Telematics and Real-Time Data Analytics in the Automotive Industry: Leveraging Edge Computing for Predictive Vehicle Maintenance and Performance Optimization." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 581-622.
  37. Selvaraj, Amsa, Debasish Paul, and Rajalakshmi Soundarapandiyan. "Synthetic Data for Customer Behavior Analysis in Financial Services: Leveraging AI/ML to Model and Predict Consumer Financial Actions." Journal of Artificial Intelligence Research 2.2 (2022): 218-258.
  38. Paul, Debasish, Rajalakshmi Soundarapandiyan, and Gowrisankar Krishnamoorthy. "Security-First Approaches to CI/CD in Cloud-Computing Platforms: Enhancing DevSecOps Practices." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 184-225.
  39. Venkatachalam, Deepak, Jeevan Sreeram, and Rajalakshmi Soundarapandiyan. "Large Language Models in Retail: Best Practices for Training, Personalization, and Real-Time Customer Interaction in E-Commerce Platforms." Journal of Artificial Intelligence Research and Applications 4.1 (2024): 539-592.
  40. Namperumal, Gunaseelan, Rajalakshmi Soundarapandiyan, and Priya Ranjan Parida. "Cloud-Driven Human Capital Management Solutions: A Comprehensive Analysis of Scalability, Security, and Compliance in Global Enterprises." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 501-549.
  41. Kurkute, Mahadu Vinayak, Gunaseelan Namperumal, and Akila Selvaraj. "Scalable Development and Deployment of LLMs in Manufacturing: Leveraging AI to Enhance Predictive Maintenance, Quality Control, and Process Automation." Australian Journal of Machine Learning Research & Applications 3.2 (2023): 381-430.
  42. Soundarapandiyan, Rajalakshmi, Deepak Venkatachalam, and Akila Selvaraj. "Real-Time Data Analytics in Connected Vehicles: Enhancing Telematics Systems for Autonomous Driving and Intelligent Transportation Systems." Australian Journal of Machine Learning Research & Applications 3.1 (2023): 420-461.
  43. Sivathapandi, Praveen, Venkatesha Prabhu Rambabu, and Yeswanth Surampudi. "Advanced CI/CD Pipelines in Multi-Tenant Cloud Platforms: Strategies for Secure and Efficient Deployment." Journal of Science & Technology 2.4 (2021): 212-252.
  44. Sudharsanam, Sharmila Ramasundaram, Gunaseelan Namperumal, and Akila Selvaraj. "Integrating AI/ML Workloads with Serverless Cloud Computing: Optimizing Cost and Performance for Dynamic, Event-Driven Applications." Journal of Science & Technology 3.3 (2022): 286-325.

Similar Articles

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