{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T03:03:25Z","timestamp":1790651005251,"version":"4.1.0"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,1,22]],"date-time":"2022-01-22T00:00:00Z","timestamp":1642809600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,22]],"date-time":"2022-01-22T00:00:00Z","timestamp":1642809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Manuf"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s10845-021-01902-z","type":"journal-article","created":{"date-parts":[[2022,1,22]],"date-time":"2022-01-22T11:03:01Z","timestamp":1642849381000},"page":"1975-1993","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Predicting part distortion field in additive manufacturing: a data-driven framework"],"prefix":"10.1007","volume":"34","author":[{"given":"Osama","family":"Aljarrah","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0162-1063","authenticated-orcid":false,"given":"Jun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alfa","family":"Heryudono","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenzhen","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Bi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,1,22]]},"reference":[{"key":"1902_CR1","unstructured":"3dexperience platform. https:\/\/make.3dexperience.3ds.com\/processes\/powder-bed-fusion Accessed 2021-12-19"},{"key":"1902_CR2","unstructured":"Additive manufacturing scenario essentials. https:\/\/www.3ds.com\/products-services\/simulia\/training\/course-descriptions\/additive-manufacturing-scenario-essentials\/ Accessed 2021-12-19"},{"issue":"1\u20132","key":"1902_CR3","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1007\/s00170-019-04315-8","volume":"106","author":"O Aljarrah","year":"2020","unstructured":"Aljarrah, O., Li, J., Huang, W., Heryudono, A., & Bi, J. (2020). ARIMA-GMDH: A low-order integrated approach for predicting and optimizing the additive manufacturing process parameters. The International Journal of Advanced Manufacturing Technology, 106(1\u20132), 701\u2013717. https:\/\/doi.org\/10.1007\/s00170-019-04315-8.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"issue":"6","key":"1902_CR4","doi-asserted-by":"publisher","first-page":"2505","DOI":"10.1007\/s10845-018-1412-0","volume":"30","author":"M Aminzadeh","year":"2019","unstructured":"Aminzadeh, M., & Kurfess, T. R. (2019). Online quality inspection using Bayesian classification in powder-bed additive manufacturing from high-resolution visual camera images. Journal of Intelligent Manufacturing, 30(6), 2505\u20132523. https:\/\/doi.org\/10.1007\/s10845-018-1412-0.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"9\u201312","key":"1902_CR5","doi-asserted-by":"publisher","first-page":"1567","DOI":"10.1007\/s00170-014-6091-1","volume":"74","author":"G Beruvides","year":"2014","unstructured":"Beruvides, G., Quiza, R., Rivas, M., Casta\u00f1o, F., & Haber, R. E. (2014). Online detection of run out in microdrilling of tungsten and titanium alloys. The International Journal of Advanced Manufacturing Technology, 74(9\u201312), 1567\u20131575. https:\/\/doi.org\/10.1007\/s00170-014-6091-1.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"1902_CR6","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1016\/j.addma.2018.10.041","volume":"25","author":"B Brenken","year":"2019","unstructured":"Brenken, B., Barocio, E., Favaloro, A., Kunc, V., & Pipes, R. B. (2019). Development and validation of extrusion deposition additive manufacturing process simulations. Additive Manufacturing, 25, 218\u2013226. https:\/\/doi.org\/10.1016\/j.addma.2018.10.041.","journal-title":"Additive Manufacturing"},{"key":"1902_CR7","doi-asserted-by":"publisher","first-page":"1762","DOI":"10.1016\/j.procs.2015.05.383","volume":"51","author":"K Burrage","year":"2015","unstructured":"Burrage, K., Burrage, P., Donovan, D., & Thompson, B. (2015). Populations of models, experimental designs and coverage of parameter space by latin hypercube and orthogonal sampling. Procedia Computer Science, 51, 1762\u20131771. https:\/\/doi.org\/10.1016\/j.procs.2015.05.383.","journal-title":"Procedia Computer Science"},{"issue":"4","key":"1902_CR8","first-page":"495","volume":"26","author":"F Castano","year":"2020","unstructured":"Castano, F., Haber, R. E., Mohammed, W. M., Nejman, M., Villalonga, A., & Lastra, J. L. M. (2020). Quality monitoring of complex manufacturing systems on the basis of model driven approach. Smart Structures and Systems, 26(4), 495\u2013506.","journal-title":"Smart Structures and Systems"},{"key":"1902_CR9","volume-title":"Advances in materials and manufacturing engineering","author":"H Cherkia","year":"2020","unstructured":"Cherkia, H., Kar, S., Singh, S. S., & Satpathy, A. (2020). Fused deposition modelling and parametric optimization of abs-m30. Lecture Notes in Mechanical Engineering. In L. Li, D. K. Pratihar, S. Chakrabarty, & P. C. Mishra (Eds.), Advances in materials and manufacturing engineering. Singapore: Springer."},{"key":"1902_CR10","unstructured":"Cioppa, T.M. (September 2002). Efficient nearly orthogonal and space-filling experimental designs for high-dimensional complex models. Technical report, NAVAL POSTGRADUATE SCHOOL MONTEREY CA. https:\/\/apps.dtic.mil\/sti\/citations\/ADA406957 Accessed 2021-12-19"},{"key":"1902_CR11","unstructured":"Courter, B., Savane, V., Bi, J., Dev, S., & Hansen, C.J. (2017). Finite element simulation of the fused deposition modelling process. In: Proceedings of the NAFEMS World Congress, pp. 11\u201314."},{"key":"1902_CR12","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1016\/j.commatsci.2013.06.041","volume":"79","author":"D Croccolo","year":"2013","unstructured":"Croccolo, D., De Agostinis, M., & Olmi, G. (2013). Experimental characterization and analytical modelling of the mechanical behaviour of fused deposition processed parts made of ABS-M30. Computational Materials Science, 79, 506\u2013518. https:\/\/doi.org\/10.1016\/j.commatsci.2013.06.041.","journal-title":"Computational Materials Science"},{"key":"1902_CR13","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.addma.2018.02.004","volume":"21","author":"JS Cuellar","year":"2018","unstructured":"Cuellar, J. S., Smit, G., Plettenburg, D., & Zadpoor, A. (2018). Additive manufacturing of non-assembly mechanisms. Additive Manufacturing, 21, 150\u2013158. https:\/\/doi.org\/10.1016\/j.addma.2018.02.004.","journal-title":"Additive Manufacturing"},{"issue":"11\u201312","key":"1902_CR14","doi-asserted-by":"publisher","first-page":"4517","DOI":"10.1007\/s00170-020-05340-8","volume":"107","author":"I Daniyan","year":"2020","unstructured":"Daniyan, I., Mpofu, K., Daniyan, L., Fameso, F., & Oyesola, M. (2020). Computer aided simulation and performance evaluation of additive manufacturing technology for component parts manufacturing. The International Journal of Advanced Manufacturing Technology, 107(11\u201312), 4517\u20134530. https:\/\/doi.org\/10.1007\/s00170-020-05340-8.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"1902_CR15","doi-asserted-by":"publisher","DOI":"10.1115\/1.4049089","author":"N Decker","year":"2021","unstructured":"Decker, N., Lyu, M., Wang, Y., & Huang, Q. (2021). Geometric accuracy prediction and improvement for additive manufacturing using triangular mesh shape data. Journal of Manufacturing Science and Engineering. https:\/\/doi.org\/10.1115\/1.4049089.","journal-title":"Journal of Manufacturing Science and Engineering"},{"issue":"7","key":"1902_CR16","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1007\/s10845-020-01532-x","volume":"32","author":"W Derigent","year":"2021","unstructured":"Derigent, W., Cardin, O., & Trentesaux, D. (2021). Industry 4.0: contributions of holonic manufacturing control architectures and future challenges. Journal of Intelligent Manufacturing, 32(7), 1797\u20131818. https:\/\/doi.org\/10.1007\/s10845-020-01532-x.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1902_CR17","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1016\/j.procir.2016.02.313","volume":"42","author":"M Faes","year":"2016","unstructured":"Faes, M., Ferraris, E., & Moens, D. (2016). Influence of inter-layer cooling time on the quasi-static properties of abs components produced via fused deposition modelling. Procedia CIRP, 42, 748\u2013753. https:\/\/doi.org\/10.1016\/j.procir.2016.02.313.","journal-title":"Procedia CIRP"},{"key":"1902_CR18","doi-asserted-by":"publisher","unstructured":"Favaloro, A. (2019). Simple, example use of UEPActivationVol in Abaqus for additive manufacturing simulation. figshare. Software. https:\/\/doi.org\/10.6084\/m9.figshare.8279621.v1.","DOI":"10.6084\/m9.figshare.8279621.v1"},{"key":"1902_CR19","unstructured":"Feih, S., Sun, C., Zhang, B., Lo, Q.L., Chin, C., & Wei, J. (2017). Influence of surrounding powder bed and build platform on thermal cooling characteristics in 3 d printed parts via selective laser melting. https:\/\/www.semanticscholar.org\/paper\/Influence-of-Surrounding-Powder-Bed-and-Build-on-in-Feih-Sun\/dbe7702af748ea5b62f638cef769231e5fa4598b Accessed 2021-12-19."},{"key":"1902_CR20","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1016\/j.ijfatigue.2016.07.005","volume":"94","author":"M Gorelik","year":"2017","unstructured":"Gorelik, M. (2017). Additive manufacturing in the context of structural integrity. International Journal of Fatigue, 94, 168\u2013177. https:\/\/doi.org\/10.1016\/j.ijfatigue.2016.07.005.","journal-title":"International Journal of Fatigue"},{"key":"1902_CR21","doi-asserted-by":"publisher","unstructured":"Hitoshi, I. (2009). Hybrid genetic programming and gmdh system: stroganoff. In: Onwubolu, G.C. (ed.) Hybrid Self-organizing modeling systems. Studies in Computational Intelligence, pp. 27\u201398. Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-01530-4_2. https:\/\/doi.org\/10.1007\/978-3-642-01530-4_2 Accessed 2021-12-19","DOI":"10.1007\/978-3-642-01530-4_2"},{"key":"1902_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2020.101594","author":"R Hong","year":"2021","unstructured":"Hong, R., Zhang, L., Lifton, J., Daynes, S., Wei, J., Feih, S., & Lu, W. F. (2021). Artificial neural network-based geometry compensation to improve the printing accuracy of selective laser melting fabricated sub-millimetre overhang trusses. Additive Manufacturing. https:\/\/doi.org\/10.1016\/j.addma.2020.101594.","journal-title":"Additive Manufacturing"},{"key":"1902_CR23","doi-asserted-by":"publisher","DOI":"10.1115\/1.4028510","author":"Q Huang","year":"2014","unstructured":"Huang, Q., Nouri, H., Xu, K., Chen, Y., Sosina, S., & Dasgupta, T. (2014). Statistical predictive modeling and compensation of geometric deviations of three-dimensional printed products. Journal of Manufacturing Science and Engineering. https:\/\/doi.org\/10.1115\/1.4028510.","journal-title":"Journal of Manufacturing Science and Engineering"},{"key":"1902_CR24","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2019.2959211","author":"Q Huang","year":"2020","unstructured":"Huang, Q., Wang, Y., Lyu, M., & Lin, W. (2020). Shape deviation generator-a convolution framework for learning and predicting 3-d printing shape accuracy. IEEE Transactions on Automation Science and Engineering. https:\/\/doi.org\/10.1109\/TASE.2019.2959211.","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"key":"1902_CR25","doi-asserted-by":"publisher","unstructured":"Ivakhnenko, A.G. (1988). Self-organizing methods in modelling and clustering: gmdh type algorithms. In: Sydow, A., Tzafestas, S.G., Vichnevetsky, R. (eds.) Systems Analysis and Simulation I. Advances in Simulation, pp. 86\u201388. Springer, New York, NY. https:\/\/doi.org\/10.1007\/978-1-4684-6389-7_15","DOI":"10.1007\/978-1-4684-6389-7_15"},{"key":"1902_CR26","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-020-01715-6","author":"J Jiang","year":"2020","unstructured":"Jiang, J., Xiong, Y., Zhang, Z., & Rosen, D. W. (2020). Machine learning integrated design for additive manufacturing. Journal of Intelligent Manufacturing. https:\/\/doi.org\/10.1007\/s10845-020-01715-6.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"5","key":"1902_CR27","doi-asserted-by":"publisher","first-page":"1541","DOI":"10.1016\/j.matt.2020.08.023","volume":"3","author":"Z Jin","year":"2020","unstructured":"Jin, Z., Zhang, Z., Demir, K., & Gu, G. X. (2020). Machine learning for advanced additive manufacturing. Matter, 3(5), 1541\u20131556. https:\/\/doi.org\/10.1016\/j.matt.2020.08.023.","journal-title":"Matter"},{"issue":"1","key":"1902_CR28","doi-asserted-by":"publisher","first-page":"1900130","DOI":"10.1002\/aisy.201900130","volume":"2","author":"Z Jin","year":"2020","unstructured":"Jin, Z., Zhang, Z., & Gu, G. X. (2020). Automated real-time detection and prediction of interlayer imperfections in additive manufacturing processes using artificial intelligence. Advanced Intelligent Systems, 2(1), 1900130. https:\/\/doi.org\/10.1002\/aisy.201900130.","journal-title":"Advanced Intelligent Systems"},{"key":"1902_CR29","doi-asserted-by":"publisher","first-page":"2907","DOI":"10.1016\/j.matpr.2020.02.600","volume":"26","author":"S Khabia","year":"2020","unstructured":"Khabia, S., & Jain, K. K. (2020). Comparison of mechanical properties of components 3D printed from different brand ABS filament on different FDM printers. Materials Today: Proceedings, 26, 2907\u20132914. https:\/\/doi.org\/10.1016\/j.matpr.2020.02.600.","journal-title":"Materials Today: Proceedings"},{"key":"1902_CR30","doi-asserted-by":"publisher","DOI":"10.1063\/1.5016790","volume-title":"Quality improvement of FDM parts by parameter optimization","author":"F Knoop","year":"2017","unstructured":"Knoop, F., Kloke, A., & Schoeppner, V. (2017). Quality improvement of FDM parts by parameter optimization. France: Lyon."},{"issue":"1","key":"1902_CR31","doi-asserted-by":"publisher","first-page":"1568","DOI":"10.4249\/scholarpedia.1568","volume":"2","author":"T Kohonen","year":"2007","unstructured":"Kohonen, T., & Honkela, T. (2007). Kohonen network. Scholarpedia, 2(1), 1568. https:\/\/doi.org\/10.4249\/scholarpedia.1568.","journal-title":"Scholarpedia"},{"issue":"6","key":"1902_CR32","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.1162\/neco.1997.9.6.1321","volume":"9","author":"T Kohonen","year":"1997","unstructured":"Kohonen, T., Kaski, S., & Lappalainen, H. (1997). Self-organized formation of various invariant-feature filters in the adaptive-subspace som. Neural Computation, 9(6), 1321\u20131344. https:\/\/doi.org\/10.1162\/neco.1997.9.6.1321.","journal-title":"Neural Computation"},{"key":"1902_CR33","unstructured":"Kordik, P. (2006). Fully automated knowledge extraction using group of adaptive models evolution\/\/phd thesis.-prague, 2006.-136 p"},{"issue":"138","key":"1902_CR34","doi-asserted-by":"publisher","first-page":"20170844","DOI":"10.1098\/rsif.2017.0844","volume":"15","author":"L Liang","year":"2018","unstructured":"Liang, L., Liu, M., Martin, C., & Sun, W. (2018). A deep learning approach to estimate stress distribution: A fast and accurate surrogate of finite-element analysis. Journal of The Royal Society Interface, 15(138), 20170844. https:\/\/doi.org\/10.1098\/rsif.2017.0844.","journal-title":"Journal of The Royal Society Interface"},{"key":"1902_CR35","unstructured":"Materials calibration essentials. https:\/\/www.3ds.com\/products-services\/simulia\/training\/course-descriptions\/materials-calibration-essentials\/ Accessed 2021-12-19."},{"issue":"4","key":"1902_CR36","doi-asserted-by":"publisher","first-page":"1571","DOI":"10.3390\/app11041571","volume":"11","author":"D Moreno Nieto","year":"2021","unstructured":"Moreno Nieto, D., & Moreno S\u00e1nchez, D. (2021). Design for additive manufacturing: Tool review and a case study. Applied Sciences, 11(4), 1571. https:\/\/doi.org\/10.3390\/app11041571.","journal-title":"Applied Sciences"},{"key":"1902_CR37","unstructured":"Mosavi, A. (2010). Multiobjective optimization using indirect optimization on the basis of self-organization. In: Proceedings of International Conference on Computational Intelligence"},{"key":"1902_CR38","unstructured":"Onwubolu, G.C. (ed.) (2016). GMDH-methodology and Implementation in MATLAB. Imperial College Press, London ; Hackensack, NJ"},{"key":"1902_CR39","doi-asserted-by":"publisher","unstructured":"Onwubolu, G.C., & Kacprzyk, J. (eds.) (2009). Hybrid self-organizing modeling systems. Studies in computational intelligence, vol. 211. Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-01530-4. http:\/\/link.springer.com\/10.1007\/978-3-642-01530-4 Accessed 2021-12-19","DOI":"10.1007\/978-3-642-01530-4"},{"issue":"1","key":"1902_CR40","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1080\/19942060.2019.1691054","volume":"14","author":"D Park","year":"2020","unstructured":"Park, D., Cha, J., Kim, M., & Go, J. S. (2020). Multi-objective optimization and comparison of surrogate models for separation performances of cyclone separator based on CFD, RSM, GMDH-neural network, back propagation-ANN and genetic algorithm. Engineering Applications of Computational Fluid Mechanics, 14(1), 180\u2013201. https:\/\/doi.org\/10.1080\/19942060.2019.1691054.","journal-title":"Engineering Applications of Computational Fluid Mechanics"},{"issue":"1","key":"1902_CR41","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/s12289-018-01462-3","volume":"13","author":"G Quaranta","year":"2020","unstructured":"Quaranta, G., Haug, E., Duval, J. L., & Chinesta, F. (2020). Parametric evaluation of part distortion in additive manufacturing processes. International Journal of Material Forming, 13(1), 29\u201341. https:\/\/doi.org\/10.1007\/s12289-018-01462-3.","journal-title":"International Journal of Material Forming"},{"issue":"6","key":"1902_CR42","doi-asserted-by":"publisher","first-page":"985","DOI":"10.1016\/j.ijmachtools.2006.07.001","volume":"47","author":"N Raghunath","year":"2007","unstructured":"Raghunath, N., & Pandey, P. M. (2007). Improving accuracy through shrinkage modelling by using Taguchi method in selective laser sintering. International Journal of Machine Tools and Manufacture, 47(6), 985\u2013995. https:\/\/doi.org\/10.1016\/j.ijmachtools.2006.07.001.","journal-title":"International Journal of Machine Tools and Manufacture"},{"issue":"2","key":"1902_CR43","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1016\/j.inpa.2020.07.002","volume":"8","author":"D Ruiz Hidalgo","year":"2021","unstructured":"Ruiz Hidalgo, D., Bacca Cort\u00e9s, B., & Caicedo Bravo, E. (2021). Dimensionality reduction of hyperspectral images of vegetation and crops based on self-organized maps. Information Processing in Agriculture, 8(2), 310\u2013327. https:\/\/doi.org\/10.1016\/j.inpa.2020.07.002.","journal-title":"Information Processing in Agriculture"},{"issue":"3\/4","key":"1902_CR44","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1504\/IJEDPO.2015.072803","volume":"4","author":"M Shamsuzzaman","year":"2015","unstructured":"Shamsuzzaman, M., Satish, M. G., & Pint\u00e9r, J. D. (2015). Distance correlation-based nearly orthogonal space-filling experimental designs. International Journal of Experimental Design and Process Optimisation, 4(3\/4), 216. https:\/\/doi.org\/10.1504\/IJEDPO.2015.072803.","journal-title":"International Journal of Experimental Design and Process Optimisation"},{"issue":"1","key":"1902_CR45","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/s40759-019-0043-2","volume":"5","author":"OY Smetannikov","year":"2019","unstructured":"Smetannikov, O. Y., Maksimov, P. V., Trushnikov, D. N., Permyakov, G. L., Belenkiy, V. Y., & Farberov, A. S. (2019). Numerical 3D simulation of wire deposition process to predict distortion of parts. Mechanics of Advanced Materials and Modern Processes, 5(1), 3. https:\/\/doi.org\/10.1186\/s40759-019-0043-2.","journal-title":"Mechanics of Advanced Materials and Modern Processes"},{"key":"1902_CR46","doi-asserted-by":"publisher","unstructured":"Srivatsan, T.S., Sudarshan, T.S. (eds.): Additive Manufacturing: Innovations, Advances, and Applications, 0 edn. CRC Press, ??? (2015). https:\/\/doi.org\/10.1201\/b19360. https:\/\/www.taylorfrancis.com\/books\/9781498714785 Accessed 2021-12-19.","DOI":"10.1201\/b19360"},{"issue":"3","key":"1902_CR47","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1108\/13552549910278955","volume":"5","author":"X Wang","year":"1999","unstructured":"Wang, X. (1999). Calibration of shrinkage and beam offset in SLS process. Rapid Prototyping Journal, 5(3), 129\u2013133. https:\/\/doi.org\/10.1108\/13552549910278955.","journal-title":"Rapid Prototyping Journal"},{"key":"1902_CR48","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-021-01833-9","author":"J-Q Wang","year":"2021","unstructured":"Wang, J.-Q., Song, Y.-L., Cui, P.-H., & Li, Y. (2021). Correction to: A data-driven method for performance analysis and improvement in production systems with quality inspection. Journal of Intelligent Manufacturing. https:\/\/doi.org\/10.1007\/s10845-021-01833-9.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"11\u201312","key":"1902_CR49","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.1007\/s00170-006-0878-7","volume":"33","author":"T-M Wang","year":"2007","unstructured":"Wang, T.-M., Xi, J.-T., & Jin, Y. (2007). A model research for prototype warp deformation in the FDM process. The International Journal of Advanced Manufacturing Technology, 33(11\u201312), 1097\u20131097. https:\/\/doi.org\/10.1007\/s00170-006-0878-7.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"1902_CR50","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1016\/j.procir.2020.02.209021-12-19","volume":"91","author":"S Weber","year":"2020","unstructured":"Weber, S., Montero, J., Bleckmann, M., & Paetzold, K. (2020). A comparison of layered tetrahedral and cartesian meshing in additive manufacturing simulation. Procedia CIRP, 91, 522\u2013527. https:\/\/doi.org\/10.1016\/j.procir.2020.02.209021-12-19.","journal-title":"Procedia CIRP"},{"key":"1902_CR51","doi-asserted-by":"publisher","DOI":"10.5705\/ss.2010.021","author":"J Yang","year":"2012","unstructured":"Yang, J., & Liu, M.-Q. (2012). Construction of orthogonal and nearly orthogonal latin hypercube designs from orthogonal designs. Statistica Sinica. https:\/\/doi.org\/10.5705\/ss.2010.021.","journal-title":"Statistica Sinica"},{"issue":"10","key":"1902_CR52","doi-asserted-by":"publisher","first-page":"1663","DOI":"10.1243\/09544054JEM572","volume":"220","author":"Y Zhang","year":"2006","unstructured":"Zhang, Y., & Chou, Y. K. (2006). Three-dimensional finite element analysis simulations of the fused deposition modelling process. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 220(10), 1663\u20131671. https:\/\/doi.org\/10.1243\/09544054JEM572.","journal-title":"Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture"},{"issue":"7","key":"1902_CR53","doi-asserted-by":"publisher","first-page":"2000031","DOI":"10.1002\/adts.202000031","volume":"3","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., & Gu, G. X. (2020). Finite-element-based deep-learning model for deformation behavior of digital materials. Advanced Theory and Simulations, 3(7), 2000031. https:\/\/doi.org\/10.1002\/adts.202000031.","journal-title":"Advanced Theory and Simulations"},{"key":"1902_CR54","doi-asserted-by":"publisher","DOI":"10.1115\/1.4039556","author":"Y Zhang","year":"2018","unstructured":"Zhang, Y., & Shapiro, V. (2018). Linear-time thermal simulation of as-manufactured fused deposition modeling components. Journal of Manufacturing Science and Engineering. https:\/\/doi.org\/10.1115\/1.4039556.","journal-title":"Journal of Manufacturing Science and Engineering"},{"key":"1902_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.matdes.2019.107678","author":"Q Zhang","year":"2019","unstructured":"Zhang, Q., Xie, J., London, T., Griffiths, D., Bhamji, I., & Oancea, V. (2019). Estimates of the mechanical properties of laser powder bed fusion Ti-6Al-4V parts using finite element models. Materials & Design. https:\/\/doi.org\/10.1016\/j.matdes.2019.107678.","journal-title":"Materials & Design"},{"key":"1902_CR56","doi-asserted-by":"publisher","DOI":"10.1115\/1.4044837","author":"Z Zhu","year":"2019","unstructured":"Zhu, Z., Anwer, N., & Mathieu, L. (2019). Statistical modal analysis for out-of-plane deviation prediction in additive manufacturing based on finite element simulation. Journal of Manufacturing Science and Engineering. https:\/\/doi.org\/10.1115\/1.4044837.","journal-title":"Journal of Manufacturing Science and Engineering"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-021-01902-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10845-021-01902-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-021-01902-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T13:14:05Z","timestamp":1678886045000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10845-021-01902-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,22]]},"references-count":56,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["1902"],"URL":"https:\/\/doi.org\/10.1007\/s10845-021-01902-z","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"value":"0956-5515","type":"print"},{"value":"1572-8145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,22]]},"assertion":[{"value":"21 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 December 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}