Exploring the Role of Artificial Intelligence in Optimizing Additive Manufacturing – A Bibliometric Analysis

Exploring the Role of Artificial Intelligence in Optimizing Additive Manufacturing – A Bibliometric Analysis.

Background Additive Manufacturing (AM) began in the 1980s with the production of rapid prototypes using Stereolithography (SLA) machines, which utilized materials like plastics and polylactic acid. Artificial intelligence (AI) was introduced to develop and create “thinking machines” that are capable of mimicking, learning, and replacing human intelligence. (Min et al., 2009). With revolution of manufacturing industry AM integrated with AI in the industry 4.0 Era(Dilberoglu et al., 2017). Additive Manufacturing is having capacity to produce customized items and complicated geometries product also revolutionizing the manufacturing Industry (Peng et al., 2021). To improve efficiency, creativity and Get High-Quality outcomes of AM , AM methods are increasingly connected with AI (Ciccone et al., 2023)..

Research GAPs. How AI Contributes to AM's Development of New Materials Specifically, human-centered products (Liu et al., 2022). The Role of AI in Optimizing the Supply Chain for AM and Third-Party Raw Material Supply for AM (Pournader, M et al., 2021). Customized Products Made Through AM with AI Enhancements (Liu et al., 2022). Automation Post-Processing Technique and Its Impact on Manufacturing Costs(Peng, X et al., 2021)..

Aim of the Research This research aims to enhance theoretical understanding through bibliometric analysis, identifying the current trends , patterns and Gaps in the Role of AI in additive manufacturing (AM) and providing clear direction to future research..

Methodology. Bibliometric and Network analysis Scientific Database:- Scopus Web of science This method is ideal for systematically understand the current application and guiding for future research (Donthu et al., 2021). Research Method Steps (Šūmakaris et al., 2020)..

Significance and Impact. [image] Chemical formulae are written on paper.

Research Plan:-. Research Proposal Literature review Data Collection Bibliometric analysis Drafting thesis Final submission.

References. Peng, X., Kong, L., Fuh, J. Y. H., & Wang, H. (2021). A Review of Post-Processing Technologies in Additive Manufacturing. In Journal of Manufacturing and Materials Processing (Vol. 5, p. 38). https://doi.org/10.3390/jmmp5020038 Pournader, M., Ghaderi, H., Hassanzadegan, A., & Fahimnia, B. (2021b). Artificial intelligence applications in supply chain management. In Int. J. Production Economics (Vol. 241, p. 108250). https://doi.org/10.1016/j.ijpe.2021.108250 Nyamekye, P., Lakshmanan, R., Tepponen, V., & Westman, S. (2024). Sustainability aspects of additive manufacturing: Leveraging resource efficiency via product design optimization and laser powder bed fusion. Heliyon, 10(1), e23152. https://doi.org/10.1016/j.heliyon.2023.e23152 Liu, C., Tian, W., & Kan, C. (2022). When AI Meets Additive Manufacturing: Challenges and Emerging Opportunities for Human-Centered Products Development. In Manufacturing Letters (Vol. 00). Elsevier Ltd. Dilberoglu, U. M., Gharehpapagh, B., Yaman, U., & Dolen, M. (2017). The Role of Additive Manufacturing in the Era of Industry 4.0. Procedia Manufacturing, 11, 545–554. https://doi.org/10.1016/j.promfg.2017.07.148 Ciccone, F., Bacciaglia, A., Ceruti, A., & Ceruti, A. (2023). Optimization with artificial intelligence in additive manufacturing: a systematic review. In Journal of the Brazilian Society of Mechanical Sciences and Engineering (Vol. 45, p. 303). https://doi.org/10.1007/s40430-023-04200-2.

Reference. Min, H. (2009). Artificial intelligence in supply chain management: theory and applications. International Journal of Logistics Research and Applications, 13(1), 13–39. https://doi.org/10.1080/13675560902736537 Šūmakaris, P., Ščeulovs, D., & Korsakienė, R. (2020). Current Research Trends on Interrelationships of Eco-Innovation and Internationalisation: A Bibliometric Analysis. Journal of Risk and Financial Management, 13(5), 85. https://doi.org/10.3390/jrfm13050085 Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070.

Thank you. 10.

11. RQ1- What are the key themes Gaps and current state in the literature review on the application of Artificial Intelligent(AI) in different areas of Additive manufacturing(AM)? RQ2- Which potential future directions can be identified for the field?.