ARTIFICIAL INTELLIGENCE IN ENGINEERING AND INDUSTRY 4.0: FOUNDATIONS, APPLICATIONS, AND CONTEMPORARY CHALLENGES
DOI:
https://doi.org/10.63330/armv2n3-006Keywords:
Artificial Intelligence, Industry 4.0, Engineering, Smart manufacturing, Cyber-physical systemsAbstract
The consolidation of Industry 4.0 redefines productive paradigms by integrating cyber-physical systems, the Internet of Things (IoT), big data, and cloud computing into industrial processes. In this scenario, artificial intelligence (AI) emerges as a structuring technology, capable of optimizing operations, expanding productive efficiency, and promoting real-time data-driven decision-making. This study critically examines the role of AI in engineering and Industry 4.0, discussing its applications in smart manufacturing, predictive maintenance, automated quality control, collaborative robotics, and supply chain management. It departs from the premise that AI does not operate in isolation but rather as an integrated component of complex digital architectures connecting sensors, machines, and analytical systems. The analysis argues that AI adoption delivers significant productivity gains, operational cost reduction, and increased precision in industrial processes, while simultaneously posing challenges related to professional qualification, cybersecurity, and data governance. The findings indicate that contemporary engineering demands new technical and strategic competencies, articulating knowledge in automation, data science, and intelligent systems. The study concludes that artificial intelligence constitutes a central axis of Industry 4.0, driving structural transformation in productive models and requiring integration among technological innovation, strategic management, and ethical responsibility within industrial settings.
Downloads
References
BARDIN, Laurence. Análise de conteúdo. São Paulo: Edições 70, 2011.
BRYNJOLFSSON, Erik; MCAFEE, Andrew. The second machine age: work, progress, and prosperity in a time of brilliant technologies. New York: W. W. Norton, 2014.
BUYYA, Rajkumar et al. A manifesto for future generation cloud computing. ACM Computing Surveys, v. 51, n. 5, 2019.
GIL, Antonio Carlos. Métodos e técnicas de pesquisa social. 7. ed. São Paulo: Atlas, 2019.
IEA. Digitalization and Energy. Paris: IEA, 2017.
KAGERMANN, Henning; WAHLSTER, Wolfgang; HELBIG, Johannes. Recommendations for implementing the strategic initiative INDUSTRIE 4.0. Frankfurt: Acatech, 2013.
LASI, Heiner et al. Industry 4.0. Business & Information Systems Engineering, v. 6, n. 4, p. 239-242, 2014.
LEE, Jay; BAGHERI, Behrad; KAO, Hung-An. A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, v. 3, p. 18-23, 2015.
OECD. The future of productivity. Paris: OECD Publishing, 2015.
PAIXÃO, Joelson Lopes da. Internet das Coisas (IoT): conceitos, desafios e aplicações no contexto das redes elétricas inteligentes. In: Inovações Multidisciplinares na Engenharia. 1. ed. Curitiba: Aurum Editora, 2025a. p. 1-11.
PAIXÃO, Joelson Lopes da. Redes neurais artificiais: estrutura, modelagem matemática e exemplo de aplicação. In: Inovações Multidisciplinares na Engenharia. 1. ed. Curitiba: Aurum Editora, 2025b. p. 12-22.
PAIXÃO, Joelson Lopes da. Transformação digital no setor elétrico: o papel central das redes inteligentes. Revista Tópicos, v. 4, p. 1-19, 2026.
PATTERSON, David et al. Carbon emissions and large neural network training. arXiv preprint, 2021.
PORTER, Michael E.; HEPPELMANN, James E. How smart, connected products are transforming competition. Harvard Business Review, v. 92, n. 11, p. 64-88, 2014.
RAJKUMAR, Buyya; BROBERG, James; GOSCINSKI, Andrzej (org.). Cloud computing: principles and paradigms. Hoboken: Wiley, 2011.
SANTOS, Boaventura de Sousa. A crítica da razão indolente. São Paulo: Cortez, 2000.
SCHWAB, Klaus. The fourth industrial revolution. Geneva: World Economic Forum, 2016.
TAYLOR, Frederick W. The principles of scientific management. New York: Harper & Brothers, 1911.
WANG, Shiyong et al. Implementing smart factory of Industry 4.0: an outlook. International Journal of Distributed Sensor Networks, v. 12, n. 1, 2016.
WORLD ECONOMIC FORUM. Shaping the future of advanced manufacturing and production. Geneva: WEF, 2018.
XU, Li Da; XU, Eric L.; LI, Ling. Industry 4.0: state of the art and future trends. International Journal of Production Research, v. 56, n. 8, p. 2941-2962, 2018.
ZHOU, Zhi-Hua et al. Deep learning in industrial automation. IEEE Transactions on Industrial Informatics, v. 15, n. 6, p. 3529-3538, 2019.
ZUBOFF, Shoshana. The age of surveillance capitalism. New York: PublicAffairs, 2019.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
