Artificial Intelligence-Driven Mechatronic System for Energy Efficiency in U.S Manufacturing Industries

References

[1] Adebiyi, O. M., Lawrence, S. A., Mayowa Adeoti, & Munashe Naphtali Mupa. (2025). Sustainable Supply Chain in The Energy Industry with A Focus on Finance. ResearchGate, 8(7), 357–364. https://www.researchgate.net/publication/388081315_Sustainable_Supply_Chain_in_The_Energy_Industry_with_A_Focus_on_Finance

[2] Adebiyi, O. M., Onyinye Nwokedi, & Munashe Naphtali Mupa. (2025). An Analysis of Financial Strategies, and Internal Controls for the Sustainability of SMME’S in the United... ResearchGate, 8(7), 340–356. https://www.researchgate.net/publication/388080729_An_Analysis_of_Financial_Strategies_and_Internal_Controls_for_the_Sustainability_of_SMME'S_in_the_United_States

[3] Atiah, P. A. (2021). Business Ethics and Corporate Governance issues in Worldcom ARTICLE CRITIQUE. SAGE Open, 20. https://www.researchgate.net/publication/355188669_Business_Ethics_and_Corporate_Governance_issues_in_Worldcom_ARTICLE_CRITIQUE

[4] Eliel Zhuwankinyu, Munashe Naphtali Mupa, & Moyo, T. M. (2025). Leveraging Generative AI for an Ethical and Adaptive Cybersecurity Framework in Enterprise Environments. ResearchGate, 8(6), 675. https://www.researchgate.net/publication/387906108_Leveraging_Generative_AI_for_an_Ethical_and_Adaptive_Cybersecurity_Framework_in_Enterprise_Environments

[5] Gande, M., Kaiyo, A., Kudakwashe Artwell Murapa, & Munashe Naphtali Mupa. (2024). Navigating Global Business: A Comparative Analysis of Rule-Based and Principle-Based Governance Systems in... ResearchGate, 8(4), 514–528. https://www.researchgate.net/publication/385384825_Navigating_Global_Business_A_Comparative_Analysis_of_Rule-Based_and_Principle-Based_Governance_Systems_in_Global_Strategy

[6] Kaiyo, A., Gande, M., Kudakwashe Artwell Murapa, & Munashe Naphtali Mupa. (2024). Unmet Standards for Diversity, Equity, and Inclusion (DEI) in the USA & recommendations to meet the standards. ResearchGate, 8(4), 499–513. https://www.researchgate.net/publication/385384829_Unmet_Standards_for_Diversity_Equity_and_Inclusion_DEI_in_the_USA_recommendations_to_meet_the_standards

[7] Lawrence, S. A., Gava, E., Adebiyi, O. M., & Munashe Naphtali Mupa. (2024, September 7). Optimizing Supply Chain and Logistics in Industrialization: A Strategic Analysis of Natural Gas Metrics... ResearchGate; unknown. https://www.researchgate.net/publication/383877196_Optimizing_Supply_Chain_and_Logistics_in_Industrialization_A_Strategic_Analysis_of_Natural_Gas_Metrics_and_Nigeria's_Impact_on_Europe_Energy_Security

[8] Lawrence, S. A., Kayode Inadagbo, Adebiyi, O. M., & Munashe Naphtali Mupa. (2024, September 5). Assessing the Challenges Associated with Food Supply in West African Cities Through Performance Metrics... ResearchGate; unknown. https://www.researchgate.net/publication/383877092_Assessing_the_Challenges_Associated_with_Food_Supply_in_West_African_Cities_Through_Performance_Metrics_and_Supply_Chain_Techniques

[9] Munashe Naphtali Mupa, Chiganze, F. R., Mpofu, T. I., & Mubvuta, M. (2024). The Evolving Role of Management Accountants in Risk Management and Internal Controls in the Energy Sector. ResearchGate, 8(2), 859–881. https://www.researchgate.net/publication/384055180_The_Evolving_Role_of_Management_Accountants_in_Risk_Management_and_Internal_Controls_in_the_Energy_Sector

[10] Naga, N. (2025). The Role of Artificial Intelligence in Risk Assessment and Mitigation in the Financial Sector. International Journal of Advanced Research in Science Communication and Technology, 633–641. https://doi.org/10.48175/ijarsct-23392

[11] Nkomo, N., & Munashe Naphtali Mupa. (2024, November 20). The Impact of Artificial Intelligence on Predictive Customer Behaviour Analytics in E-commerce: A... ResearchGate; unknown. https://www.researchgate.net/publication/386135078_The_Impact_of_Artificial_Intelligence_on_Predictive_Customer_Behaviour_Analytics_in_E-commerce_A_Comparative_Study_of_Traditional_and_AI-driven_Models

[12] Nnanna Kalu-Mba, Munashe Naphtali Mupa, & Tafirenyika, S. (2025). Artificial Intelligence as a Catalyst for Innovation in the Public Sector: Opportunities, Risks, and... ResearchGate, 8(11), 716–724. https://www.researchgate.net/publication/391736874_Artificial_Intelligence_as_a_Catalyst_for_Innovation_in_the_Public_Sector_Opportunities_Risks_and_Policy_Imperatives

[13] Nnanna Kalu-Mba, Munashe Naphtali Mupa, & Tafirenyika, S. (2025). The Role of Machine Learning in Post-Disaster Humanitarian Operations: Case Studies and Strategic Implications. ResearchGate, 8(11), 725–734. https://www.researchgate.net/publication/391737365_The_Role_of_Machine_Learning_in_Post-Disaster_Humanitarian_Operations_Case_Studies_and_Strategic_Implications

[14] None Eliel Kundai Zhuwankinyu, None Munashe Naphtali Mupa, & None Sylvester Tafirenyika. (2025). Graph-based security models for AI-driven data storage: A novel approach to protecting classified documents. World Journal of Advanced Research and Reviews, 26(2), 1108–1124. https://doi.org/10.30574/wjarr.2025.26.2.1631

[15] Shiraishi, R. (2025). Rikuto SHIRAISHI | Master’s Student | Master of Business Administration | Hult International Business School, Cambridge | MBA Program | Research profile. ResearchGate. https://www.researchgate.net/profile/Rikuto-Shiraishi

[16] Shiraishi, R., & Munashe Naphtali Mupa. (2025). Cross-Border Tax Structuring and Valuation Optimization in Energy-Sector M&A: A U.S.-Japan Perspective. 8(11), 126–135. https://www.researchgate.net/publication/391485061_Cross-Border_Tax_Structuring_and_Valuation_Optimization_in_Energy-Sector_MA_A_US-Japan_Perspective

@article{1710658,
      author = {Hope Rufaro Matenga, Munashe Naphtali Mupa, Obert Batsirai Musemwa},
      title = {Artificial Intelligence-Driven Mechatronic System for Energy Efficiency in U.S Manufacturing Industries},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {3},
      pages = {792-801},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710658.pdf},
      abstract = {The study examines how Artificial Intelligence (AI) and mechatronics systems can be used strategically to facilitate the increase of energy efficiency within the manufacturing sector in the United States. Due to the growing needs of energy resources, climate issues, and the desire to establish sustainable industry, rising pressure on the manufacturers implores them to implement smart technologies that minimize consumption and enhance the operations. The gist of this research is related to the idea of the usage of AI-based mechatronic systems in operations that require consuming a lot of energy, such as the automotive industry, food processing, or precision engineering, where smart sensors, robotics, and adaptive control algorithms are applied. The methodology was a qualitative case study based on secondary data of industry reports, citations of published case studies, and simulations. Comparative and thematic analysis showed quantifiable results on energy consumption, less emission of CO?, quality of output, and efficiency of operation in the picked sectors. The results are consistent with the U.S. federal energy plans, such as the Department of Energy (DOE) modernization approach and the Inflation Reduction Act, which focuses on clean energy adoption and smart manufacturing. Also, AI and mechatronics integration was discovered to promote Environmental, Social, and Governance (ESG) objectives in terms of the enhanced efficiency of resources used and the adjustment of industrial experience to the sustainability indicators. Implications on strategy are explored with respect to shareholders of the industry, such as the managers, engineers, and corporate planners, and also on the national policy crafting. The research makes a contribution to current literature through the fact that it solves the existing gap between the theoretical concepts of intelligent automation and the practical challenge in the industrial field. It emphasizes the significance of spreading it to more domains, using policy to encourage retrofitting legacy systems, and conducting additional scholarly work in the field using cross-national case studies. All in all, the innovation of AI-mechatronics integration appears not to be just an innovative development but rather an agent of a sustainable industrial revolution capable of setting U.S. manufacturing on a profitable pathway as the world economy diversifies towards energy awareness and digitization. The findings highlight the prospects of smart systems that can support economic and environmental demands in the contemporary system of industrial settings.},
      month = {September},
      doi = {https://doi.org/10.64388/IREV9I3-1710658-1422}
  }