[1]
M.K. Thompson, G. Moroni, T. Vaneker, G. Fadel, R.I. Campbell, I. Gibson, A. Bernard, J. Schulz, P. Graf, B. Ahuja and F. Martina, Design for Additive Manufacturing: Trends, opportunities, considerations, and constraints, CIRP Ann. Manuf. Technol. 65(2) (2016) 737-760.
DOI: 10.1016/j.cirp.2016.05.004
Google Scholar
[2]
T. Vaneker, A. Bernard, G. Moroni, I. Gibson and Y. Zhang, Design for additive manufacturing: Framework and methodology, CIRP Annals, 69(2), CIRP Ann. Manuf. Technol. 69(2) (2020) 578-599.
DOI: 10.1016/j.cirp.2020.05.006
Google Scholar
[3]
F. Calignano, D. Manfredi, E.P. Ambrosio, S. Biamino, M. Lombardi, E. Atzeni, A. Salmi, P. Minetola, L. Iuliano, P. Fino, Overview on additive manufacturing technologies, Proc. IEEE 105(4) (2017) 593-612.
DOI: 10.1109/jproc.2016.2625098
Google Scholar
[4]
E.P. Gargiulo, Stereolithography process accuracy: user experience, Proceedings of the 1st European Conference on Rapid Prototyping (1992) 187-207.
Google Scholar
[5]
T.H.C. Childs and N.P. Juster, Linear and geometric accuracies from layer manufacturing, CIRP Ann. Manuf. Technol. 43(1) (1994) 163-166.
DOI: 10.1016/s0007-8506(07)62187-8
Google Scholar
[6]
R. Ippolito, L. Iuliano and A. Gatto, Benchmarking of rapid prototyping techniques in terms of dimensional accuracy and surface finish, CIRP Ann. Manuf. Technol. 44(1) (1995) 157-160.
DOI: 10.1016/s0007-8506(07)62296-3
Google Scholar
[7]
F. Xu, Y.S. Wong and H.T. Loh, Toward generic models for comparative evaluation and process selection in rapid prototyping and manufacturing, J. Manuf. Syst. 19(5) (2000) 283-296.
DOI: 10.1016/s0278-6125(01)89001-4
Google Scholar
[8]
M. Mahesh, Y.S. Wong, J.Y.H. Fuh and H.T. Loh, Benchmarking for comparative evaluation of RP systems and processes, Rapid Prototyping J. 10(2) (2004) 123-135.
DOI: 10.1108/13552540410526999
Google Scholar
[9]
D. Dimitrov, W. van Wijck, K. Schreve and N. de Beer, Investigating the achievable accuracy of three dimensional printing, Rapid Prototyping J. 12(1) (2006) 42-52.
DOI: 10.1108/13552540610637264
Google Scholar
[10]
E. Bassoli, A. Gatto, L. Iuliano and M.G. Violante, 3D printing technique applied to rapid casting, Rapid Prototyping J. 13(3) (2007) 148-155.
DOI: 10.1108/13552540710750898
Google Scholar
[11]
D. Scaravetti, P. Dubois and R. Duchamp, Qualification of rapid prototyping tools: proposition of a procedure and a test part, Int. J. Adv. Manuf. Tech. 38 (2008) 683-690.
DOI: 10.1007/s00170-007-1129-2
Google Scholar
[12]
R. Singh and J.P. Singh, Comparison of rapid casting solutions for lead and brass alloys using three-dimensional printing, P. I. Mech. Eng. C.-J. Mec. 223(9) 2117-2123.
DOI: 10.1243/09544062jmes1387
Google Scholar
[13]
E. Bassoli and E. Atzeni, Direct metal rapid casting: mechanical optimization and tolerance calculation, Rapid Prototyping J. 15(4) (2009) 238-243.
DOI: 10.1108/13552540910979758
Google Scholar
[14]
T. Brajlih, B. Valentan, J. Balic and I. Drstvensek, Speed and accuracy evaluation of additive manufacturing machines, Rapid Prototyping J. 17(1) (2011) 64-75.
DOI: 10.1108/13552541111098644
Google Scholar
[15]
H.K. Garg and R. Singh, Pattern development for manufacturing applications with fused deposition modelling-a case study, Int. J. Automot. Mech. Eng. 7(1) (2013) 981-992.
DOI: 10.15282/ijame.7.2012.14.0079
Google Scholar
[16]
S. Moylan, J. Slotwinski, A. Cooke, K. Jurrens and M.A. Donmez, An additive manufacturing test artifact, J. Res. Natl. Inst. Stan. 119 (2014) 429-459.
DOI: 10.6028/jres.119.017
Google Scholar
[17]
W.M. Johnson, M. Rowell, B. Deason and M. Eubanks, Comparative evaluation of an open-source FDM system, Rapid Prototyping J. 20(3) (2014) 205-214.
DOI: 10.1108/rpj-06-2012-0058
Google Scholar
[18]
R. Singh and G. Singh, Investigations for statistically controlled investment casting solution of FDM-based ABS replicas, Rapid Prototyping J. 20(3) (2014) 215-220.
DOI: 10.1108/rpj-03-2013-0036
Google Scholar
[19]
F.A. Cruz Sanchez, H. Boudaoud, L. Muller and M. Camargo, Towards a standard experimental protocol for open source additive manufacturing, Virtual Phys. Prototyp. 9(3) (2014) 151-167.
DOI: 10.1080/17452759.2014.919553
Google Scholar
[20]
P. Minetola, L. Iuliano and G. Marchiandi, Benchmarking of FDM machines through part quality using IT grades, Proc. CIRP 41 (2016) 1027-1032.
DOI: 10.1016/j.procir.2015.12.075
Google Scholar
[21]
K. Kitsakis, J. Kechagias, N. Vaxevanidis and D. Giagkopoulos, Tolerance Analysis of 3d-MJM parts according to IT grade, IOP Conf. Ser. Mater. Sci. Eng. 161(1) (2016) 012024.
DOI: 10.1088/1757-899x/161/1/012024
Google Scholar
[22]
L. Rebaioli and I. Fassi, A review on benchmark artifacts for evaluating the geometrical performance of additive manufacturing processes, Int. J. Adv. Manuf. Technol. 93(5) (2017) 2571–2598.
DOI: 10.1007/s00170-017-0570-0
Google Scholar
[23]
P. Minetola, M. Galati, L. Iuliano, E. Atzeni and A. Salmi, The Use of Self-replicated Parts for Improving the Design and the Accuracy of a Low-cost 3D Printer, Proc. CIRP 67 (2018) 203-208.
DOI: 10.1016/j.procir.2017.12.200
Google Scholar
[24]
J. Gulanová, I. Kister, N. Káčer and L. Gulan, A comparative study of various AM technologies based on their accuracy, Proc. CIRP 67 (2018) 238–243.
DOI: 10.1016/j.procir.2017.12.206
Google Scholar
[25]
G. Papazetis and G.C. Vosniakos, Feature-based process parameter variation in continuous paths to improve dimensional accuracy in three-dimensional printing via material extrusion, Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 233(12) (2019) 2241-2250.
DOI: 10.1177/0954405419838361
Google Scholar
[26]
S.J. Jin, D.Y. Kim, J.H. Kim and W.C. Kim, Accuracy of Dental Replica Models Using Photopolymer Materials in Additive Manufacturing: In Vitro Three-Dimensional Evaluation, 2019 J. Prosthodont. 28(2) (2019) e557–e562.
DOI: 10.1111/jopr.12928
Google Scholar
[27]
P. Minetola, M. Galati, F. Calignano, L. Iuliano, G. Rizza and L. Fontana, Comparison of dimensional tolerance grades for metal AM processes, Proc. CIRP 88 (2020) 399-404.
DOI: 10.1016/j.procir.2020.05.069
Google Scholar
[28]
P. Minetola, F. Calignano and M. Galati, Comparing geometric tolerance capabilities of additive manufacturing systems for polymers, Addit. Manuf. 32 (2020) 101103.
DOI: 10.1016/j.addma.2020.101103
Google Scholar
[29]
V.M.R. Santos, A. Thompson, D. Sims-Waterhouse, I. Maskery, P. Woolliams and R. Leach, Design and characterisation of an additive manufacturing benchmarking artefact following a design-for-metrology approach, Addit. Manuf. 32 (2020) 100964.
DOI: 10.1016/j.addma.2019.100964
Google Scholar
[30]
M.A. de Pastre, S.C.T. Tagne and N. Anwer, Test artefacts for additive manufacturing: A design methodology review, CIRP J. Manuf. Sci. Technol. 31 (2020) 14-24.
DOI: 10.1016/j.cirpj.2020.09.008
Google Scholar
[31]
ISO 286-1:1988, ISO system of limits and fits - Part 1: Basis of tolerances, deviations and fit, International Organization for Standardization (1988).
DOI: 10.3403/00373808
Google Scholar
[32]
ISO 286-2:2010, Geometrical product specifications (GPS) - ISO code system for tolerances on linear sizes - Part 2: Tables of standard tolerance classes and limit deviations for holes and shafts, International Organization for Standardization (2010).
DOI: 10.3403/30163095u
Google Scholar
[33]
ISO 1101:2017, Geometrical product specifications (GPS) - Geometrical tolerancing - Tolerances of form, orientation, location and run-out, International Organization for Standardization (2017).
DOI: 10.3403/30303642
Google Scholar
[34]
ISO 17450-1:2011, Geometrical product specifications (GPS) - General concepts - Part 1: Model for geometrical specification and verification, International Organization for Standardization (2011).
DOI: 10.3403/30198177
Google Scholar
[35]
ISO 17450-3:2016, Geometrical product specifications (GPS) – General concepts - Part 3: Toleranced features, International Organization for Standardization (2016).
DOI: 10.3403/30272937
Google Scholar