A STUDY ON THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN MATERIAL MOVEMENT BASED ON SCIENTIFIC PUBLICATIONS
DOI:
https://doi.org/10.61164/rmnm.v1i1.3420Palabras clave:
Artificial intelligence. Material handling. Smart technologies. Internal logistics. Material logistics.Resumen
Artificial intelligence is one of the information and communication technologies that has promoted major transformations in organizations and their production processes, especially material handling. The growing number of published studies led to the development of this study, which aimed to describe the main characteristics of studies that report the application of artificial intelligence in material handling. The method used was the conceptual bibliographic, bibliometric design based on four stages: formulation of research questions, collection of bibliographic data, analysis, organization of the collected data, and generation of answers to the guiding questions. The results showed that the focuses of the applications are a) improvement and optimization of the logistics process, increased rationality of human-machine actions, and optimization of the decision-making process, b) use of several simultaneous methods and techniques, c) facing problematic situations aimed at problem-solving and generation of technologies, d) application of multiple artificial intelligence tools, e) successful results have increased competitiveness and rationality in material handling and f) opening for new and interconnected applications. The conclusion shows that using artificial intelligence has provided an environment for enhancing human cognitive capacity. The main contribution of this study to science is the finding that professional training in logistics needs to incorporate mastery of artificial intelligence.
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ASI, N. et al. Culturally distinctive features in journalistic text: a case study on students’ vs. ai-generated translations. Yavana Bhasha: Journal of English Language Education, v. 7, n. 1, p. 54-67, 2024.
BAR-GIL, O.; RON, T.; CZERNIAK, O. AI for the people? Embedding AI ethics in HR and people analytics projects. Technology in Society, in press, p. 102527, 2024. https://doi.org/10.1016/j.techsoc.2024.102527.
BORGHI, D. et al. High energy computed tomography of high-density alloys using a 6 MeV linear accelerator: Detectability and use of artificial intelligence. 13th Conference on Industrial Computed Tomography, Wels, Austria (iCT 2024), p. 1-11, 2024.
CASTILLO, O. D. D. et al. Supervised learning system for detection of cardiac arrhythmias based on electrocardiographic data. In: 2019 IEEE International Conference on E-health Networking, Application & Services (HealthCom). IEEE, 2019. p. 1-4. https://doi.org/10.1109/HealthCom46333.2019.9009601.
CHIZOBA, C.; ISHOLA, R.; TEMITOPE, A. The economics and finance letters. Economics, v. 11, n. 1, p. 1-17, 2024. https^//doi.org/10.18488/29.v11i1.3596.
DHAND, S.; SINGH, S. K.; LE, T. M. Automating routine tasks to improve entrepreneurial productivity. In: TUNIO, M. N. (ed.). Improving entrepreneurial processes through advanced AI. Hershey: IGI Global, 2025, p. 99-128.
HE, T.-L. et al. Investigating the impact of situational cognition, emotions, and self-efficacy on creative thinking and collaborative intention in metaverse teaching scene. Thinking Skills and Creativity, v. 56, p. 101723, 2025. https://doi.org/10.1016/j.tsc.2024.101723.
KAN, C. H. Criminal liability of artificial intelligence from the perspective of criminal law: An evaluation in the context of the general theory of crime and fundamental principles. International Journal of Eurasia Social Sciences, v. 15, n. 55, p. 276-313, 2024. http://dx.doi.org/10.35826/ijoess.4434.
KOLEY, S. et al. Applications of artificial intelligence and machine learning‐enabled businesses: A SWOT analysis for human society. Artificial Intelligence‐Enabled Businesses: How to Develop Strategies for Innovation, p. 227-261, 2025. https://doi.org/10.1002/9781394234028.ch13.
KONECKA, S.; ŁUPICKA, A. The impact of the use of intelligent supply chain tools on the transport, forwarding and logistics industry. In: GOLINSKA-DOWSON, P. et al. (eds.). Smart and sustainable supply chain and logistics—Challenges, methods and best practices: Volume 2. Cham: Springer, 2023. p. 265-282.
LAGARINHOS, C. A. F.; AZEVEDO, L. P. Challenges and opportunities of hydrogen economy in Industrial Revolution 4.0 era. Accelerating the Transition to a Hydrogen Economy, v. 1: Achieving Carbon Neutrality, p. 237-255, 2025. https://doi.org/10.1016/B978-0-443-14039-6.00009-9.
LI, Y. Constructing the intelligent expressway traffic monitoring system using the internet of things and inspection robot. The Journal of Supercomputing, v. 80, n. 7, p. 8742-8766, 2024. https://doi.org/10.1007/s11227-023-05794-z.
MALHOTRA, G.; KHARUB, M. Elevating logistics performance: harnessing the power of artificial intelligence in e-commerce. The International Journal of Logistics Management, v. 36, n. 1, p. 290-321, 2025. https://doi.org/10.1108/IJLM-01-2024-0046.
MARAK, Z. R.; SHARMA, A.; UIKEY, A. A. Exploring the interlinkages between industry 4.0, circular economy, and sustainable performance. In: TRIPATHI, V. et al. (eds). Implementing ESG Frameworks Through Capacity Building and Skill Development. Hershey: IGI Global, 2025. p. 301-328.
MATHUR, S.; CHANDEL, M. Assessment of sports-specific dietary methods. In: CHATTERJEE, A.; SARKAR, T. (eds.). Examining physiology, nutrition, and body composition in sports science. Hershey: IGI Global, 2025, p. 299-336.
MOSKVICHENKO, I.; STADNIK, V.; KUSHNIR, L. Improvement of the quality management system in the transport and logistics sector. Baltic Journal of Economic Studies, v. 10, n. 4, p. 301-309, 2024. https://doi.org/10.30525/2256-0742/2024-10-4-301-309.
MU, M.; QIN, B.; DAI, G. Predictability study of weather and climate events related to artificial intelligence models. Advances in Atmospheric Sciences, v. 42, n. 1, p. 1-8, 2025. https://doi.org/10.1007/s00376-024-4372-7.
NASCIMENTO-E-SILVA, D. Handbook of the scientific-technological method: edição sintética. Manaus: DNS Editor, 2021a.
NASCIMENTO-E-SILVA, D. Manual do método científico-tecnológico: edição sintética. Florianópolis: DNS Editor, 2020.
NASCIMENTO-E-SILVA, D. Metodologia da pesquisa e elaboração de projetos tecnológicos. Manaus: DNS Editor, 2021d.
NASCIMENTO-E-SILVA, D. O método científico-tecnológico: coleta de dados. Manaus: DNS Editor, 2023.
NASCIMENTO-E-SILVA, D. O método científico-tecnológico: fundamentos. Manaus: DNS Editor, 2021b.
NASCIMENTO-E-SILVA, D. O método científico-tecnológico: questões de pesquisa. Manaus: DNS Editor, 2021c.
NOVIANA, M. et al. Automation of the BERT and RESNET50 model inference configuration analysis process. JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer), v. 10, n. 2, p. 324-332, 2024. https://doi.org/10.33480/jitk.v10i2.5053.
OGIDAN, E. T.; OLAWALE, O. P.; DIMILILER, K. Machine learning applications in industry 4.0: opportunities and challenges. In: KUMAR, A. et al. (eds). Handbook of intelligent and sustainable manufacturing. Boca Raton: CRC, 2025, p. 284-304.
ÖZBEK, A. Muhasebe meslek mensuplarinin yapay zekâ kaygilarinin gelecekte istihdam edilebilirlik algilari üzerine bir çalişma. Alanya Akademik Bakış, v. 8, n. 1, p. 254-267, 2024. https://doi.org/10.29023/alanyaakademik.1329511.
PASANG, S. et al. The use of kuki chatbot application to improve english achievement. International Journal of English Language Studies, v. 6, n. 1, p. 15-46, 2024.
https://doi.org/10.32996/ijels.2024.6.1.3.
PATEL, K. Artificial intelligence and its scope in different areas with special reference to the field of education. International Research Journal of Modernization in Engineering Technology and Science, v. 6, n. 1, p. 2500-2507, 2024.
PRASETYA, S. P. Artificial intelligence in social sciences education presents new challenges and opportunities. In: 4th International Conference on Social Sciences and Law (ICSSL 2024). Atlantis Press, 2024. p. 111-121. https://doi.org/10.2991/978-2-38476-303-0_12.
QUY, N. M. et al. A novel multi agents-based clustering algorithm for VANETs in 5G networks. Wireless Networks, p. 1-13, 2024. https://doi.org/10.1007/s11276-023-03627-8.
REHMAN, S. U. et al. Industry 4.0 technologies and international performance of SMEs: mediated-moderated perspectives. International Entrepreneurship and Management Journal, v. 21, n. 1, p. 1-32, 2025. https://doi.org/10.1007/s11365-024-01048-3.
SHAHZAD, M. F.; LIU, H.; ZAHID, H. Industry 4.0 technologies and sustainable performance: do green supply chain collaboration, circular economy practices, technological readiness and environmental dynamism matter? Journal of Manufacturing Technology Management, v. 36, n. 1, p. 1-22, 2025. https://doi.org/10.1108/JMTM-05-2024-0236.
SHAMSUDDOHA, M. et al. From Industry 4.0 to Industry 5.0: Transitioning to circular business paradigms—A review. In: BADAR, M. A. et al. (eds.). Handbook of digital innovation, transformation, and sustainable development in a post-pandemic era. Boca Raton: CRC, 2025, p. 215-231.
SHARMA, J.; BHARDWAJ, M.; CHANTOLA, N. Emerging applications and future scope of internet of vehicles for smart cities: A Survey. In: MALIK, K. (eds.). Explainable artificial intelligence for autonomous vehicles, Boca Raton: CRC, 2025, p. 100-115.
SINGH, J. et al. Implementation and evaluation of a smart machine monitoring system under industry 4.0 concept. Journal of Industrial Information Integration, v. 43, p. 100746, 2025. https://doi.org/10.1016/j.jii.2024.100746.
SKLAVOS, G. et al. Reinforcing sustainability and efficiency for agrifood firms: A theoretical framework. In: RAGAZOU, K. et al. (eds.). Sustainability Through Green HRM and Performance Integration. Hershey: IGI Global, 2025. p. 101-120.
TANRIVERDI, İ.; AYDIN, H. A bibliometric review of the omnichannel logistics literature. The International Review of Retail, Distribution and Consumer Research, v. 34, n. 3, p. 310-330, 2024. https://doi.org/10.1080/09593969.2023.2259645.
TYNDALL, D. A. A primer and overview of the role of artificial intelligence in oral and maxillofacial radiology. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology, in press, p. 1-6, 2024. https://doi.org/10.1016/j.oooo.2024.02.009.
WANG, S.; JIAO, R. J. Cognitive intelligent task allocation for human-automation symbiosis in Industry 5.0 manufacturing systems via non-cooperative game theory: a bi-level optimization approach. The International Journal of Advanced Manufacturing Technology, p. 1-23, 2025. https://doi.org/10.1007/s00170-024-14890-0.
YÁÑEZ-VALDÉS, C.; GUERRERO, M. Determinants and impacts of digital entrepreneurship: A pre-and post-COVID-19 perspective. Technovation, v. 132, p. 102983, 2024. https://doi.org/10.1016/j.technovation.2024.102983.
YILDIZ, T. The minds we make: A philosophical inquiry into theory of mind and artificial intelligence. Integrative Psychological and Behavioral Science, v. 59, n. 1, p. 1-23, 2025. https://doi.org/10.1007/s12124-024-09876-2.
ZAFRULLAH, Z.; MEISYA, A.; AYUNI, R. T. Artificial intelligence as a learning media in English education: Bibliometric using biblioshiny analysis (2009-2023). ELTR Journal, v. 8, n. 1, p. 71-81, 2024. https://doi.org/10.37147/eltr.v8i1.179.
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