A statistical method for build orientation determination in additive manufacturing
Abstract
Purpose For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and costly computation. To deal with these issues, this paper aims to introduce a new statistical method to develop fast automatic decision support tools for additive manufacturing build orientation determination. Design/methodology/approach The proposed method applies a non-supervised machine learning method, K-Means Clustering with Davies–Bouldin Criterion cluster measuring, to rapidly decompose a surface model into facet clusters and efficiently generate a set of meaningful alternative build orientations. To evaluate alternative build orientations at a generic level, a statistical approach is defined. Findings A group of illustrative examples and comparative case studies are presented in the paper for method validation. The proposed method can help production engineers solve decision problems related to identifying an optimal build orientation for complex and freeform CAD models, especially models from the medical and aerospace application domains with much efficiency. Originality/value The proposed method avoids the limitations of traditional feature-based methods and pure computation-based methods. It provides engineers a new efficient decision-making tool to rapidly determine the optimal build orientation for complex and freeform CAD models.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
These parameters include production path strategies, part locations, and build orientations to enhance the quality and characteristics of the final printed products.
“These parameters include production path strategies, part locations, and build orientations to enhance the quality and characteristics of the final printed products [425].”
From A comprehensive review of lunar-based manufacturing and construction (2024) · cites this paper as [425]
Cites
Algorithm AS 136: A K-Means Clustering Algorithm
Hartigan, J. A., & Wong, M. A. (1979) · Applied Statistics · doi:10.2307/2346830 · Cited by 14,523 · see citing works
Data clustering: 50 years beyond K-means
Jain, A. K. (2009) · Pattern Recognition Letters · doi:10.1016/j.patrec.2009.09.011 · Cited by 9,622 · see citing works
Davies, D. L., & Bouldin, D. W. (1979) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1979.4766909 · Cited by 9,145 · see citing works
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00293 · Cited by 6,205 · see citing works
Metal Additive Manufacturing: A Review
Frazier, W. E. (2014) · Journal of Materials Engineering and Performance · doi:10.1007/s11665-014-0958-z · Cited by 5,984 · see citing works
Design for Additive Manufacturing: Trends, opportunities, considerations, and constraints
Thompson, M. K., Moroni, G., Vaneker, T., Fadel, G., Campbell, R. I., Gibson, I., Bernard, A., Schulz, J., Graf, P., Ahuja, B., et al. (2016) · CIRP Annals · doi:10.1016/j.cirp.2016.05.004 · Cited by 2,025 · see citing works
Self-citationEvolutionary many-objective optimization: A short review
Ishibuchi, H., Tsukamoto, N., & Nojima, Y. (2008) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2008.4631121 · Cited by 916 · see citing works
A review of process planning techniques in layered manufacturing
Kulkarni, P., Marsan, A. L., & Dutta, D. (2000) · Rapid Prototyping Journal · doi:10.1108/13552540010309859 · Cited by 395 · see citing works
Part orientation and build cost determination in layered manufacturing
Alexander, P. W., Allen, S., & Dutta, D. (1998) · Computer-Aided Design · doi:10.1016/s0010-4485(97)00083-3 · Cited by 375 · see citing works
Multi‐objective optimization of part‐ building orientation in stereolithography
Cheng, W.-C., Fuh, J. Y. H., Nee, A. Y. C., Wong, Y. S., Loh, H. T., & MIYAZAWA, T. (1995) · Rapid Prototyping Journal · doi:10.1108/13552549510104429 · Cited by 267 · see citing works
Byun, H.-S., & Lee, K. H. (2005) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2005.03.001 · Cited by 205 · see citing works
Determining fabrication orientations for rapid prototyping with Stereolithography apparatus
Lan, P.-T., Chou, S.-Y., Chen, L.-L., & Gemmill, D. D. (1997) · Computer-Aided Design · doi:10.1016/s0010-4485(96)00049-8 · Cited by 201 · see citing works
Build orientation optimization for multi-part production in additive manufacturing
Zhang, Y., Bernard, A., Harik, R., & Karunakaran, K. P. (2015) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-015-1057-1 · Cited by 193 · see citing works
Self-citationA new methodological framework for design for additive manufacturing
Kumke, M., Watschke, H., & Vietor, T. (2016) · Virtual and Physical Prototyping · doi:10.1080/17452759.2016.1139377 · Cited by 192 · see citing works
Optimal part deposition orientation in FDM by using a multicriteria genetic algorithm
Pandey, P. M., Thrimurthulu, K., & Reddy, N. V. (2004) · International Journal of Production Research · doi:10.1080/00207540410001708470 · Cited by 187 · see citing works
Expert system-based selection of the preferred direction of build for rapid prototyping processes
Frank, D., & Fadel, G. M. (1995) · Journal of Intelligent Manufacturing · doi:10.1007/bf00124677 · Cited by 186 · see citing works
Self-citationPaul, R., & Anand, S. (2014) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2014.06.014 · Cited by 157 · see citing works
Considerations and selection of optimal orientation for different rapid prototyping systems
Xu, F., Loh, H. T., & Wong, Y. S. (1999) · Rapid Prototyping Journal · doi:10.1108/13552549910267344 · Cited by 148 · see citing works
Part deposition orientation studies in layered manufacturing
Pandey, P. M., Reddy, N. V., & Dhande, S. G. (2006) · Journal of Materials Processing Technology · doi:10.1016/j.jmatprotec.2006.03.120 · Cited by 146 · see citing works
Haq, A. N., & Boddu, V. (2014) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-014-0957-9 · Cited by 142 · see citing works
A generic algorithm for a best part orientation system for complex parts in rapid prototyping
Masood, S. H., Rattanawong, W., & Iovenitti, P. (2003) · Journal of Materials Processing Technology · doi:10.1016/s0924-0136(03)00190-0 · Cited by 142 · see citing works
Modelling and optimisation of Rapid Prototyping
Choi, S.-H., & Samavedam, S. (2002) · Computers in Industry · doi:10.1016/s0166-3615(01)00140-3 · Cited by 141 · see citing works
Ulu, E., Korkmaz, E., Yay, K., Özdoğanlar, O. B., & Kara, L. B. (2015) · Journal of Mechanical Design · doi:10.1115/1.4030998 · Cited by 132 · see citing works
Genetic-algorithm-based multi-objective optimization of the build orientation in stereolithography
Canellidis, V., Giannatsis, J., & Dedoussis, V. (2009) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-009-2006-y · Cited by 116 · see citing works
Part Orientation in Stereolithography
Pham, D. T., Dimov, S., & Gault, R. (1999) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s001700050118 · Cited by 115 · see citing works
A new methodological framework for design for additive manufacturing*
Kumke, M., Watschke, H., & Vietor, T. (2017) · CRC Press eBooks · doi:10.1201/9781315119106-12 · Cited by 113 · see citing works
A process planning method for improving build performance in stereolithography
West, A. P., Sambu, S., & Rosen, D. W. (2001) · Computer-Aided Design · doi:10.1016/s0010-4485(00)00064-6 · Cited by 111 · see citing works
Determination of fabricating orientation and packing in SLS process
Hur, S.-M., Choi, K. H., Lee, S., & Chang, P.-K. (2001) · Journal of Materials Processing Technology · doi:10.1016/s0924-0136(01)00581-7 · Cited by 108 · see citing works
Multi‐objective optimisation and multi‐criteria decision making in SLS using evolutionary approaches
Padhye, N., & Deb, K. (2011) · Rapid Prototyping Journal · doi:10.1108/13552541111184198 · Cited by 104 · see citing works
Optimal orientation with variable slicing in stereolithography
Xu, F., Wong, Y. S., Loh, H. T., Fuh, J. Y. H., & MIYAZAWA, T. (1997) · Rapid Prototyping Journal · doi:10.1108/13552549710185644 · Cited by 99 · see citing works
Feature based building orientation optimization for additive manufacturing
Zhang, Y., Bernard, A., Gupta, R. K., & Harik, R. (2016) · Rapid Prototyping Journal · doi:10.1108/rpj-03-2014-0037 · Cited by 93 · see citing works
Self-citationManufacturability analysis for additive manufacturing using a novel feature recognition technique
Shi, Y., Zhang, Y., Baek, S., Backer, W. D., & Harik, R. (2018) · Computer-Aided Design and Applications · doi:10.1080/16864360.2018.1462574 · Cited by 93 · see citing works
Self-citationDesign for Additive Manufacturing: Automated Build Orientation Selection and Optimization
Zwier, M. P., & Wits, W. W. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.08.040 · Cited by 92 · see citing works
An examination of procedures for determining the number of clusters in a data set
Hardy, A. (1994) · Studies in classification, data analysis, and knowledge organization · doi:10.1007/978-3-642-51175-2_20 · Cited by 91 · see citing works
Hur, J., & Lee, K. (1998) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/bf01199879 · Cited by 88 · see citing works
ON THE COMPUTATION OF PART ORIENTATION USING SUPPORT STRUCTURES IN LAYERED MANUFACTURING
Dutta, D. (2018) · Texas ScholarWorks (Texas Digital Library) · doi:10.15781/t24f1n368 · Cited by 83 · see citing works
Evaluating the Design for Additive Manufacturing: A Process Planning Perspective
Zhang, Y., Bernard, A., Gupta, R. K., & Harik, R. (2014) · Procedia CIRP · doi:10.1016/j.procir.2014.03.179 · Cited by 70 · see citing works
Self-citationReduction of post-processing for stereolithography systems by fabrication-direction optimization
Kim, H.-C., & Lee, S. (2004) · Computer-Aided Design · doi:10.1016/j.cad.2004.08.009 · Cited by 67 · see citing works
Strano, G., Hao, L., Everson, R., & Evans, K. (2011) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/0954405411402925 · Cited by 59 · see citing works
Computer‐aided build style decision support for stereolithography
McClurkin, J. E., & Rosen, D. W. (1998) · Rapid Prototyping Journal · doi:10.1108/13552549810197505 · Cited by 58 · see citing works
Functionality-based Part Orientation for Additive Manufacturing
Moroni, G., Syam, W. P., & Petrò, S. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.01.015 · Cited by 54 · see citing works
Zhang, Y., & Bernard, A. L. (2014) · Rapid Prototyping Journal · doi:10.1108/rpj-01-2013-0009 · Cited by 53 · see citing works
Self-citationUsing AM feature and multi-attribute decision making to orientate part in Additive Manufacturing
Zhang, Y., & Bernard, A. L. (2013) · CRC Press eBooks · doi:10.1201/b15961-76 · Cited by 23 · see citing works
Self-citationZhang, J., & Li, Y. (2012) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-012-4518-0 · Cited by 22 · see citing works
Zhang, Y., & Bernard, A. L. (2014) · Cited by 18 · see citing works
Self-citationZhang, Y., Wang, W., & Bernard, A. L. (2016) · HAL (Le Centre pour la Communication Scientifique Directe) · Cited by 16 · see citing works
Self-citationA tool for computer-aided orientation selection in additive manufacturing processes
Armillotta, A., Cavallaro, M., & Minnella, S. (2013) · CRC Press eBooks · doi:10.1201/b15961-86 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Machine Learning for industrial applications: A comprehensive literature review
Bertolini, M., Mezzogori, D., Neroni, M., & Zammori, F. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.114820 · Cited by 553 · see citing works
Research and application of machine learning for additive manufacturing
Qin, J., Hu, F., Liu, Y., Witherell, P., Wang, C. C. L., Rosen, D. W., Simpson, T. W., Lu, Y., & Tang, Q. (2022) · Additive Manufacturing · doi:10.1016/j.addma.2022.102691 · Cited by 391 · see citing works
Design for additive manufacturing: Framework and methodology
Vaneker, T., Bernard, A., Moroni, G., Gibson, I., & Zhang, Y. (2020) · CIRP Annals · doi:10.1016/j.cirp.2020.05.006 · Cited by 292 · see citing works
Self-citationPerspectives of using machine learning in laser powder bed fusion for metal additive manufacturing
Sing, S. L., Kuo, C. N., Shih, C., Ho, C. C., & Chua, C. K. (2021) · Virtual and Physical Prototyping · doi:10.1080/17452759.2021.1944229 · Cited by 186 · see citing works
He, F., Yuan, L., Mu, H., Ros, M., Ding, D., Pan, Z. S., & Li, H. (2023) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2023.102525 · Cited by 149 · see citing works
Optimization with artificial intelligence in additive manufacturing: a systematic review
Ciccone, F., Bacciaglia, A., & Ceruti, A. (2023) · Journal of the Brazilian Society of Mechanical Sciences and Engineering · doi:10.1007/s40430-023-04200-2 · Cited by 139 · see citing works
Haleem, A., & Javaid, M. (2019) · Clinical Epidemiology and Global Health · doi:10.1016/j.cegh.2019.03.001 · Cited by 132 · see citing works
Wang, Y., Zheng, P., Peng, T., Yang, H., & Zou, J. T. (2020) · Science China Technological Sciences · doi:10.1007/s11431-020-1581-2 · Cited by 108 · see citing works
Zhang, Y., Wang, Z., Zhang, Y., Gomes, S., & Bernard, A. (2020) · CIRP Annals · doi:10.1016/j.cirp.2020.04.091 · Cited by 102 · see citing works
Self-citationTaborda, L. L. L., Maury, H., & Pacheco, J. (2021) · Rapid Prototyping Journal · doi:10.1108/rpj-11-2019-0296 · Cited by 63 · see citing works
Multicriteria decision analysis framework for part orientation analysis in additive manufacturing
Ransikarbum, K., Pitakaso, R., Kim, N., & Ma, J. (2021) · Journal of Computational Design and Engineering · doi:10.1093/jcde/qwab037 · Cited by 62 · see citing works
A comprehensive review of lunar-based manufacturing and construction
Azami, M., Kazemi, Z., Moazen, S., Dubé, M., Potvin, M.-J., & Skonieczny, K. (2024) · Progress in Aerospace Sciences · doi:10.1016/j.paerosci.2024.101045 · Cited by 57 · see citing works
A constructive solid geometry-based generative design method for additive manufacturing
Wang, Z., Zhang, Y., & Bernard, A. (2021) · Additive manufacturing · doi:10.1016/j.addma.2021.101952 · Cited by 55 · see citing works
Self-citationA review of machine learning in additive manufacturing: design and process
Chen, K., Zhang, P., Yan, H., Chen, G., Sun, T., Lu, Q., Chen, Y., & Shi, H. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-14543-2 · Cited by 49 · see citing works
Automatic determination of part build orientation for laser powder bed fusion
Qin, Y., Qi, Q., Shi, P., Scott, P. J., & Jiang, X. (2020) · Virtual and Physical Prototyping · doi:10.1080/17452759.2020.1832793 · Cited by 48 · see citing works
Ramalingam, P. S., Kalimuthu, M., Balasubramanian, V., Chandrasekar, K., Stalany, V. M., & Munaf, A. A. (2020) · Materials Today Proceedings · doi:10.1016/j.matpr.2020.10.467 · Cited by 48 · see citing works
Support point determination for support structure design in additive manufacturing
Wang, Z., Zhang, Y., Tan, S., Ding, L., & Bernard, A. (2021) · Additive manufacturing · doi:10.1016/j.addma.2021.102341 · Cited by 43 · see citing works
Self-citationQin, Y., Qi, Q., Scott, P. J., & Jiang, X. (2019) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01497-6 · Cited by 42 · see citing works
Issues in Metal Matrix Composites Fabricated by Laser Powder Bed Fusion Technique: A Review
Essien, U. A., & Vaudreuil, S. (2022) · Advanced Engineering Materials · doi:10.1002/adem.202200055 · Cited by 41 · see citing works
Pirinu, A., Primo, T., Prete, A. D., Panella, F. W., & Pascalis, F. D. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-10390-1 · Cited by 40 · see citing works
Multi-Attribute Decision-Making Methods in Additive Manufacturing: The State of the Art
Qin, Y., Qi, Q., Shi, P., Lou, S., Scott, P. J., & Jiang, X. (2023) · Processes · doi:10.3390/pr11020497 · Cited by 40 · see citing works
Status, issues, and future of computer-aided part orientation for additive manufacturing
Qin, Y., Qi, Q., Shi, P., Scott, P. J., & Jiang, X. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-06996-6 · Cited by 37 · see citing works
Qin, Y., Qi, Q., Shi, P., Scott, P. J., & Jiang, X. (2020) · Virtual and Physical Prototyping · doi:10.1080/17452759.2020.1756086 · Cited by 35 · see citing works
Wang, T., Li, Y., Li, T., Liu, B., Li, X., & Zhang, X. (2025) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-025-02568-7 · Cited by 26 · see citing works
Lettori, J., Raffaeli, R., Bilancia, P., Peruzzini, M., & Pellicciari, M. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-10432-8 · Cited by 27 · see citing works
Ma, Z., Gao, M., Guo, K., Wang, Q., Li, L., Liu, C., Zhu, G., & Liu, Z. (2022) · International Journal of Precision Engineering and Manufacturing-Green Technology · doi:10.1007/s40684-022-00450-y · Cited by 23 · see citing works
Wang, Z., Zhang, Y., & Bernard, A. (2022) · Virtual and Physical Prototyping · doi:10.1080/17452759.2022.2090015 · Cited by 22 · see citing works
Self-citationHaleem, A., & Javaid, M. (2019) · Journal of Industrial Integration and Management · doi:10.1142/s242486221950009x · Cited by 20 · see citing works
A conceptual vision for a bio-intelligent manufacturing cell for Selective Laser Melting
Wegener, K., Spierings, A. B., Teti, R., Caggiano, A., Knüttel, D., & Staub, A. (2021) · CIRP journal of manufacturing science and technology · doi:10.1016/j.cirpj.2020.11.009 · Cited by 20 · see citing works
Stiffness modulation for soft robot joint via lattice structure configuration design
Wang, Z., Zhang, Y., Li, G., Jin, G., & Bernard, A. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.05.149 · Cited by 15 · see citing works
Self-citationA generic method for multi-criterion decision-making problems in design for additive manufacturing
Huang, M., Chen, L., Zhong, Y., & Qin, Y. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-06832-x · Cited by 14 · see citing works
Shi, P., Qi, Q., Qin, Y., Meng, F., Lou, S., Scott, P. J., & Jiang, X. (2023) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2023.3249751 · Cited by 14 · see citing works
Li, Z., Huang, M., Zhong, Y., & Qin, Y. (2022) · Applied Sciences · doi:10.3390/app12094612 · Cited by 13 · see citing works
Abdulhameed, O., Mian, S. H., Moiduddin, K., Al-Ahmari, A. M., Ahmed, N., & Aboudaif, M. K. (2022) · Micromachines · doi:10.3390/mi13101777 · Cited by 13 · see citing works
An autonomous intelligent framework for optimal orientation detection in 3D printing
Rezaei, M. R., Houshmand, M., & Valilai, O. F. (2023) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2022.2162587 · Cited by 12 · see citing works
Sheng, H., Xu, J., Zhang, S., & Tan, J. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-10237-9 · Cited by 11 · see citing works
Enhancing additive manufacturing with computer vision: a comprehensive review
Yu, H., Li, W., Li, D., Wang, L., & Wang, Y. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-13689-3 · Cited by 12 · see citing works
Build Orientation Optimization Based on Weighted Analysis of Local Surface Region Curvature
Guo, H., Xu, J., Zhang, S., & Yi, G. (2020) · Applied Sciences · doi:10.3390/app11010304 · Cited by 10 · see citing works
Deterministic part orientation in additive manufacturing using feature recognition
Leirmo, T. L., & Martinsen, K. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.05.070 · Cited by 9 · see citing works
AI-enabled end-to-end processing in additive manufacturing: From pre-processing to post-processing
Chen, M., Wang, J., Wang, L., Liu, Y., Liu, R., Jin, Q., Yang, J., Tang, W., Wang, R., & Zhu, S. (2026) · Additive Manufacturing Frontiers · doi:10.1016/j.amf.2026.200315 · Cited by 8 · see citing works
A kinematics-aware part clustering approach for part integration using additive manufacturing
Pan, W., & Lu, W. F. (2021) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2021.102171 · Cited by 8 · see citing works
Artificial Intelligence Technologies and Applications in Additive Manufacturing
Shah, S. A., Lee, I. H., & Kim, H.-C. (2025) · International Journal of Precision Engineering and Manufacturing · doi:10.1007/s12541-025-01288-5 · Cited by 6 · see citing works
Sheng, H., Xu, J., Zhang, S., Tan, J., & Wang, K. (2023) · Frontiers of Mechanical Engineering · doi:10.1007/s11465-022-0737-8 · Cited by 6 · see citing works
Mathur, J., Miller, S. R., Simpson, T. W., & Meisel, N. A. (2024) · Journal of Mechanical Design · doi:10.1115/1.4065232 · Cited by 5 · see citing works
Yang, Y., Liu, B., Li, H., Li, X., Liu, X., & Wang, G. (2022) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-022-01945-w · Cited by 5 · see citing works
Description Logic Ontology-Supported Part Orientation for Fused Deposition Modelling
Huang, M., Zheng, N., Qin, Y., Tang, Z., Zhang, H., Fan, B., & Qin, L. (2022) · Processes · doi:10.3390/pr10071290 · Cited by 5 · see citing works
Amor, R. B., Souissi, S., Elloumi, A., & Bentaher, H. (2025) · International Journal on Interactive Design and Manufacturing (IJIDeM) · doi:10.1007/s12008-025-02418-z · Cited by 3 · see citing works
Malbašić, S., Đorđević, A., Živković, S., Džunić, D. S., & Sokolović, V. (2024) · Symmetry · doi:10.3390/sym16121616 · Cited by 3 · see citing works
Costa, J. B., Silva‐Correia, J., Reis, R. L., & Oliveira, J. M. (2021) · Journal of 3D Printing in Medicine · doi:10.2217/3dp-2021-0007 · Cited by 3 · see citing works
Importance of Multi‐objective Evaluation in 3D Printing
Ransikarbum, K., & Kim, N. (2024) · doi:10.1002/9781394150335.ch6 · Cited by 3 · see citing works
Guo, H., Zhang, S., Zhang, N., Liu, X., & Yi, G. (2024) · Robotic Intelligence and Automation · doi:10.1108/ria-09-2023-0124 · Cited by 2 · see citing works
Leirmo, T. L., & Semeniuta, O. (2022) · Open Engineering · doi:10.1515/eng-2022-0032 · Cited by 2 · see citing works
Applications in Data-Driven Additive Manufacturing
Safdar, M., Lamouche, G., Paul, P. P., Wood, G., & Zhao, Y. F. (2023) · SpringerBriefs in applied sciences and technology · doi:10.1007/978-3-031-32154-2_3 · Cited by 1 · see citing works
Kazemi, Z., & Steeves, C. A. (2025) · Acta Mechanica · doi:10.1007/s00707-025-04371-0 · Cited by 2 · see citing works
Das, B., Kumar, P., & Bandyopadhyay, T. K. (2026) · Composites Part B Engineering · doi:10.1016/j.compositesb.2026.114116 · Cited by 2 · see citing works
Tan, S., Wang, Z., Li, M., & Zhang, Y. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.02.132 · Cited by 1 · see citing works
Self-citation(2020) · Dunod eBooks · doi:10.3917/dunod.barli.2020.02.0464
Significance of Machine Learning in Industry 4.0 Scenario—A Review
Kiran, M. B. (2022) · Lecture notes in mechanical engineering · doi:10.1007/978-981-16-9952-8_17
Bhaskar, A. S., & Khan, A. (2025) · Journal of Materials Engineering and Performance · doi:10.1007/s11665-025-12701-5
Omede’, B., Festa, S., & Grande, A. M. (2026) · International Journal of Production Research · doi:10.1080/00207543.2026.2647003
Chen, Y., Li, J., Lan, Z., Liu, K., Liu, R., Wang, L., Wang, Z., & Wang, J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6469735
Application of machine vision for in-situ monitoring in metal additive manufacturing: A review
Cao, Y., Tang, W., Chen, Z., Ma, J., Xiaoke, L. I., & Ming, W. (2026) · Measurement · doi:10.1016/j.measurement.2026.121307
- Authors
- Zhang, Y., Harik, R., Fadel, G., & Bernard, A.
- Affiliations
- Université de technologie de belfort-montbéliard (FR)
- University of South Carolina (US)
- Clemson University (US)
- École Centrale de Nantes (FR)
- Venue
- Rapid Prototyping Journal
- Publisher
- Emerald
- Published
- 2019-01-07
- Volume
- 25
- Issue
- 1
- Pages
- 187-207
- ISSN
- 1355-2546 (ISSN-L)
- OpenAlex
- W2903832848
- Cited by
- 63
- References
- 47
- Citations by year
- 2026: 5 · 2025: 5 · 2024: 7 · 2023: 8 · 2022: 13 · 2021: 13 · 2020: 9 · 2019: 3
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Rapid Prototyping Journal (publishedVersion)
- HAL (submittedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Manufacturing Process and Optimization
- Physical Sciences › Engineering › Mechanical Engineering › Additive Manufacturing Materials and Processes
- Keywords
- additive manufacturing, K-means clustering, decision support system
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
