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The International Journal of Advanced Manufacturing Technology
Erschienen in: The International Journal of Advanced Manufacturing Technology 1-2/2020

09.08.2020 | ORIGINAL ARTICLE

Manufacturability analysis of metal laser-based powder bed fusion additive manufacturing—a survey

verfasst von: Ying Zhang, Sheng Yang, Yaoyao Fiona Zhao

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 1-2/2020

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Abstract

The laser-based powder bed fusion (LPBF) process is able to produce complex part geometries. The fast development of the LPBF process offers new opportunities for the industries. Most research done to date has focused on the modeling of the process, which shows that both part geometries and process parameters play an essential role in the result of end-product quality. The definition of the manufacturability of the LPBF is vague. In this review, the focus is set on the manufacturability of the metal-LPBF process. What manufacturability is in the LPBF process and how it is investigated so far are discussed. All process parameters and design constraints for LPBF processes are introduced. The relationship between process parameters and design constraints and how they affect the manufacturability are discussed as well. A detailed discussion on how other researchers evaluate manufacturability analysis of LPBF is conducted. Finally, the manufacturability of LPBF is defined, and future prospects on filling the research gaps on the manufacturability analysis of the LPBF are presented.
Vorheriger Artikel Towards design of mechanical part and electronic control of multi-material/multicolor fused deposition modeling 3D printing
Nächster Artikel Multiphysics simulation of the resistance spot welding detection using electromagnetic ultrasonic transverse wave

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Literatur
1.
Leary M, Mazur M, Elambasseril J, McMillan M, Chirent T, Sun Y, Qian M, Easton M, Brandt M (2016) Selective laser melting (SLM) of AlSi12Mg lattice structures. Mater Des 98:344–357
2.
Sun S, Brandt M, Easton M (2017) 2 - Powder bed fusion processes: an overview. In: Laser additive manufacturing. Woodhead Publishing, pp 55–77
3.
4.
Bhavar, V., et al. A review on powder bed fusion technology of metal additive manufacturing. In: 4th International Conference and Exhibition on Additive Manufacturing Technologies-AM-2014, September. 2014
5.
Beaman JJ et al (1997) SLS process modeling and control. In: Solid freeform fabrication: a new direction in manufacturing: with research and applications in thermal laser processing. Springer US, Boston, MA, pp 167–243
6.
Kruth J-P, Mercelis P, van Vaerenbergh J, Froyen L, Rombouts M (2005) Binding mechanisms in selective laser sintering and selective laser melting. Rapid Prototyp J 11(1):26–36
7.
Frazier WE (2014) Metal additive manufacturing: a review. J Mater Eng Perform 23(6):1917–1928
8.
Wohlers, T., Wohlers report. Wohlers Associates Inc, 2014
9.
King W et al (2015) Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges. Appl Phys Rev 2(4):041304
10.
Mullen L et al (2009) Selective laser melting: a regular unit cell approach for the manufacture of porous, titanium, bone in-growth constructs, suitable for orthopedic applications. Journal of Biomedical Materials Research Part B: Applied Biomaterials: an Official Journal of The Society for Biomaterials, The Japanese Society for Biomaterials, and The Australian Society for Biomaterials and the Korean Society for Biomaterials 89(2):325–334
11.
Arabnejad S, Burnett Johnston R, Pura JA, Singh B, Tanzer M, Pasini D (2016) High-strength porous biomaterials for bone replacement: a strategy to assess the interplay between cell morphology, mechanical properties, bone ingrowth and manufacturing constraints. Acta Biomater 30:345–356
12.
Uriondo A, Esperon-Miguez M, Perinpanayagam S (2015) The present and future of additive manufacturing in the aerospace sector: a review of important aspects. Proceedings of the Institution of Mechanical Engineers, Part G: J Aero Engr 229 (11):2132–2147
13.
Santos EC, Shiomi M, Osakada K, Laoui T (2006) Rapid manufacturing of metal components by laser forming. Int J Mach Tools Manuf 46(12–13):1459–1468
14.
Louvis E, Fox P, Sutcliffe CJ (2011) Selective laser melting of aluminium components. J Mater Process Technol 211(2):275–284
15.
Brandl E, Heckenberger U, Holzinger V, Buchbinder D (2012) Additive manufactured AlSi10Mg samples using selective laser melting (SLM): microstructure, high cycle fatigue, and fracture behavior. Mater Des 34:159–169
16.
17.
Thompson MK, Moroni G, Vaneker T, Fadel G, Campbell RI, Gibson I, Bernard A, Schulz J, Graf P, Ahuja B, Martina F (2016) Design for Additive Manufacturing: trends, opportunities, considerations, and constraints. CIRP Ann 65(2):737–760
18.
19.
Rosen, D.W., Powder bed fusion processes. 2012, Georgia Institute of Technology
20.
Ziemke MC, Spann MS (1993) Concurrent engineering’s roots in the World War II era. In: Concurrent engineering. Springer, pp 24–41
21.
Gupta SK, Nau DS (1995) Systematic approach to analysing the manufacturability of machined parts. Comput Aided Des 27(5):323–342MATH
22.
Sing SL et al (2016) Manufacturability and mechanical testing considerations of metallic scaffolds fabricated using selective laser melting: a review. Biomedical Science and Engineering:1(1)
23.
Thomas, D., The development of design rules for selective laser melting. 2009, University of Wales
24.
Adam GA, Zimmer D (2015) On design for additive manufacturing: evaluating geometrical limitations. Rapid Prototyp J 21(6):662–670
25.
Diegel, O., et al., Tools for sustainable product design: additive manufacturing. 2010
26.
Ameta G, Lipman R, Moylan S, Witherell P (2015) Investigating the role of geometric dimensioning and tolerancing in additive manufacturing. J Mech Des 137(11):111401
27.
Booth JW, Alperovich J, Chawla P, Ma J, Reid TN, Ramani K (2017) The design for additive manufacturing worksheet. J Mech Des 139(10):100904
28.
Li W, Li S, Liu J, Zhang A, Zhou Y, Wei Q, Yan C, Shi Y (2016) Effect of heat treatment on AlSi10Mg alloy fabricated by selective laser melting: microstructure evolution, mechanical properties and fracture mechanism. Mater Sci Eng A 663:116–125
29.
Sufiiarov VS, Popovich AA, Borisov EV, Polozov IA, Masaylo DV, Orlov AV (2017) The effect of layer thickness at selective laser melting. Procedia engineering 174:126–134
30.
Pegues, J., et al. Effect of specimen surface area size on fatigue strength of additively manufactured Ti-Al-4V parts. In: 28th International Solid Freeform Fabrication Symposium. 2017
31.
Pegues, J., et al. Effect of process parameter variation on microstructure and mechanical properties of additively manufactured Ti-6Al-4V. In: Solid freeform fabrication 2017: Proceedings of the 28th Annual International. 2017
32.
Hanzl P, Zetek M, Bakša T, Kroupa T (2015) The influence of processing parameters on the mechanical properties of SLM parts. Procedia Engineering 100:1405–1413
33.
Krauss H, Zaeh M (2013) Investigations on manufacturability and process reliability of selective laser melting. Phys Procedia 41:815–822
34.
Uddin, S.Z., et al. Laser powder bed fusion fabrication and characterization of crack-free aluminum alloy 6061 using in-process powder bed induction heating. In: Solid freeform fabrication 2017. 2017
35.
Campanelli SL et al (2014) Manufacturing and characterization of Ti6Al4V lattice components manufactured by selective laser melting. Materials 7(6):4803–4822
36.
Ponnusamy, P., et al. Mechanical performance of selective laser melted 17–4 PH stainless steel under compressive loading. In: Solid freeform fabrication 2017. 2017
37.
Qi, T., et al. Porosity development and cracking behavior of Al-Zn-Mg-Cu alloys fabricated by selective laser melting. In: Solid freeform fabrication 2017. 2017
38.
Yadollahi, A., et al. Prediction of fatigue lives in additively manufactured alloys based on the crack-growth concept. In: Solid freeform fabrication 2017. 2017
39.
Aboulkhair NT et al (2014) Reducing porosity in AlSi10Mg parts processed by selective laser melting. Additive Manufacturing 1:77–86
40.
Tradowsky U, White J, Ward RM, Read N, Reimers W, Attallah MM (2016) Selective laser melting of AlSi10Mg: influence of post-processing on the microstructural and tensile properties development. Mater Des 105:212–222
41.
Haghshenas, M., et al. Small-scale mechanical properties of additively manufactured Ti-6Al-4V. In: Solid freeform fabrication 2017. 2017
42.
Yadroitsev I, Smurov I (2011) Surface morphology in selective laser melting of metal powders. Phys Procedia 12:264–270
43.
Ferrar B, Mullen L, Jones E, Stamp R, Sutcliffe CJ (2012) Gas flow effects on selective laser melting (SLM) manufacturing performance. J Mater Process Technol 212(2):355–364
44.
Hoefer, M., N. Chen, and M. Frank. Automated manufacturability analysis for conceptual design in new product development. In: IIE Annual Conference. Proceedings. 2017. Institute of Industrial and Systems Engineers (IISE)
45.
Kerbrat O, Mognol P, Hascoët J-Y (2011) A new DFM approach to combine machining and additive manufacturing. Comput Ind 62(7):684–692
46.
Jang D, Kim K, Jung J (2000) Voxel-based virtual multi-axis machining. Int J Adv Manuf Technol 16(10):709–713
47.
Das S, Kanchanapiboon A (2011) A multi-criteria model for evaluating design for manufacturability. Int J Prod Res 49(4):1197–1217
48.
Shukor SA, Axinte DA (2009) Manufacturability analysis system: issues and future trends. Int J Prod Res 47(5):1369–1390
49.
Han J, Pratt M, Regli WC (2000) Manufacturing feature recognition from solid models: a status report. IEEE Trans Robot Autom 16(6):782–796
50.
Li, Y. and M.C. Frank, Machinability analysis for 3-axis flat end milling. 2006
51.
Joshi S, Chang T-C (1988) Graph-based heuristics for recognition of machined features from a 3D solid model. Comput Aided Des 20(2):58–66MATH
52.
Kailash S, Zhang Y, Fuh JY (2001) A volume decomposition approach to machining feature extraction of casting and forging components. Comput Aided Des 33(8):605–617
53.
Kim, Y.S., Convex decomposition and solid geometric modeling. 1990
54.
Kim YS (1992) Recognition of form features using convex decomposition. Comput Aided Des 24(9):461–476MATH
55.
Sakurai H, Dave P (1996) Volume decomposition and feature recognition, part II: curved objects. Comput Aided Des 28(6–7):519–537
56.
Sakurai, H. and C.-W. Chin, Definition and recognition of volume features for process planning. In: Manufacturing research and technology. 1994, Elsevier. p. 65–80
57.
Regli III, W.C., Geometric algorithms for recognition of features from solid models. 1995
58.
Han J, Requicha AA (1997) Integration of feature based design and feature recognition. Comput Aided Des 29(5):393–403
59.
Brooks, S.L., et al., Using STEP to integrate design features with manufacturing features. 1995. Allied-Signal Aerospace Co., Kansas City, MO (United States). Kansas City Div
60.
Vandenbrande JH, Requicha AA (1993) Spatial reasoning for the automatic recognition of machinable features in solid models. IEEE Trans Pattern Anal Mach Intell 15(12):1269–1285
61.
Meisel N, Williams C (2015) An investigation of key design for additive manufacturing constraints in multimaterial three-dimensional printing. J Mech Des 137(11):111406
62.
Mani, M., P. Witherell, and H. Jee, Design rules for additive manufacturing: a categorization. 2017 (58110): p. V001T02A035
63.
Grasso M, Colosimo BM (2017) Process defects and in situ monitoring methods in metal powder bed fusion: a review. Meas Sci Technol 28(4):044005
64.
Tapia G, Elwany A (2014) A review on process monitoring and control in metal-based additive manufacturing. J Manuf Sci Eng 136(6):060801
65.
Mani, M., et al., Measurement science needs for real-time control of additive manufacturing powder bed fusion processes. 2015: US Department of Commerce, National Institute of Standards and Technology
66.
Everton SK, Hirsch M, Stravroulakis P, Leach RK, Clare AT (2016) Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing. Mater Des 95:431–445
67.
Sames WJ, List FA, Pannala S, Dehoff RR, Babu SS (2016) The metallurgy and processing science of metal additive manufacturing. Int Mater Rev 61(5):315–360
68.
Spears TG, Gold SA (2016) In-process sensing in selective laser melting (SLM) additive manufacturing. Integrating Materials and Manufacturing Innovation 5(1):2
69.
70.
Okaro IA, Jayasinghe S, Sutcliffe C, Black K, Paoletti P, Green PL (2019) Automatic fault detection for laser powder-bed fusion using semi-supervised machine learning. Additive Manufacturing 27:42–53
71.
Yuan, B., et al. Semi-supervised convolutional neural networks for in-situ video monitoring of selective laser melting. In: Proceedings - 2019 IEEE winter conference on applications of computer vision, WACV 2019. 2019
72.
Yuan B et al (2018) Machine-learning-based monitoring of laser powder bed fusion. Advanced Materials Technologies 3(12)
73.
Wasmer K, le-Quang T, Meylan B, Shevchik SA (2019) In situ quality monitoring in AM using acoustic emission: a reinforcement learning approach. J Mater Eng Perform 28(2):666–672
74.
Scime L, Beuth J (2018) A multi-scale convolutional neural network for autonomous anomaly detection and classification in a laser powder bed fusion additive manufacturing process. Additive Manufacturing 24:273–286
75.
Scime L, Beuth J (2019) Using machine learning to identify in-situ melt pool signatures indicative of flaw formation in a laser powder bed fusion additive manufacturing process. Additive Manufacturing 25:151–165
76.
Imani F et al (2018) Process mapping and in-process monitoring of porosity in laser powder bed fusion using layerwise optical imaging. Journal of Manufacturing Science and Engineering, Transactions of the ASME 140(10)
77.
Gobert C, Reutzel EW, Petrich J, Nassar AR, Phoha S (2018) Application of supervised machine learning for defect detection during metallic powder bed fusion additive manufacturing using high resolution imaging. Additive Manufacturing 21:517–528
78.
Zhang, Y. and A. Bernard. AM feature and knowledge based process planning for additive manufacturing in multiple parts production context. In: Proceedings of 25th Annual International Solid Freeform Fabrication Symposium. 2014
79.
Shi Y, Zhang Y, Baek S, de Backer W, Harik R (2018) Manufacturability analysis for additive manufacturing using a novel feature recognition technique. Computer-Aided Design and Applications 15(6):941–952
80.
Kerbrat O, Mognol P, Hascoet JY (2010) Manufacturability analysis to combine additive and subtractive processes. Rapid Prototyp J 16(1):63–72
81.
Tedia, S. and C.B. Williams. Manufacturability analysis tool for additive manufacturing using voxel-based geometric modeling. In: 27th Annual International Solid Freeform Fabrication (SFF) Symposium. 2016
82.
Telea, A. and A. Jalba. Voxel-based assessment of printability of 3D shapes. In: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing. 2011. Springer
83.
Nelaturi S, Kim W, Kurtoglu T (2015) Manufacturability feedback and model correction for additive manufacturing. J Manuf Sci Eng 137(2):021015
84.
Schmitt, W., et al. A 3D shape descriptor based on depth complexity and thickness histograms. In: 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images. 2015. IEEE
85.
Ulu, E., et al., Manufacturability oriented model correction and build direction optimization for additive manufacturing. Journal of Mehanical Design, 2019(in process)
86.
Lu, T. Towards a fully automated 3D printability checker. In: 2016 IEEE International Conference on Industrial Technology (ICIT). 2016. IEEE
87.
Kim S et al (2019) A design for additive manufacturing ontology to support manufacturability. Analysis. 1
88.
Chen, Y. and X. Xu. Manufactruability analysis of infeasible features in polygonal models for web-based rapid prototyping. In: 2010 International Conference on Manufacturing Automation. 2010. IEEE
89.
Cabiddu, D. and M. Attene, Epsilon-shapes: characterizing, detecting and thickening thin features in geometric models. 2017
90.
Wang Y, Blache R, Zheng P, Xu X (2018) A knowledge management system to support design for additive manufacturing using Bayesian networks. J Mech Des 140(5):051701
91.
Mokhtarian H et al (2018) A conceptual design and modeling framework for integrated additive manufacturing. J Mech Des:140(8)
92.
Manfredi D, Calignano F, Krishnan M, Canali R, Ambrosio E, Atzeni E (2013) From powders to dense metal parts: characterization of a commercial AlSiMg alloy processed through direct metal laser sintering. Materials 6(3):856–869
93.
Hauser, J.R. and D. Clausing, The house of quality. 1988
94.
Park T, Kim K-J (1998) Determination of an optimal set of design requirements using house of quality. J Oper Manag 16(5):569–581
95.
Akao, Y., Quality function deployment. 2004
96.
Sing SL, Wiria FE, Yeong WY (2018) Selective laser melting of lattice structures: a statistical approach to manufacturability and mechanical behavior. Robot Comput Integr Manuf 49:170–180
97.
Norton RL (2009) Cam design and manufacturing handbook. Industrial Press Inc
98.
Yang S, Zhao YF (2015) Additive manufacturing-enabled design theory and methodology: a critical review. Int J Adv Manuf Technol 80(1–4):327–342
99.
Sutton AT, Kriewall CS, Leu MC, Newkirk JW (2017) Powder characterisation techniques and effects of powder characteristics on part properties in powder-bed fusion processes. Virtual and Physical Prototyping 12(1):3–29
100.
Yan C, Hao L, Hussein A, Bubb SL, Young P, Raymont D (2014) Evaluation of light-weight AlSi10Mg periodic cellular lattice structures fabricated via direct metal laser sintering. J Mater Process Technol 214(4):856–864
101.
Brown B, Everhart W, Dinardo J (2016) Characterization of bulk to thin wall mechanical response transition in powder bed AM. Rapid Prototyp J 22(5):801–809
102.
Kruth J et al (2005) Benchmarking of different SLS/SLM processes as rapid manufacturing techniques. Laser 1:3D
103.
Zeng, K., Optimization of support structures for selective laser melting. 2015
104.
Gibson I, Rosen D, Stucker B (2014) Additive manufacturing technologies, vol 17. Springer, New York
105.
Calignano F (2014) Design optimization of supports for overhanging structures in aluminum and titanium alloys by selective laser melting. Mater Des 64:203–213
106.
Adam GA, Zimmer D (2014) Design for additive manufacturing—element transitions and aggregated structures. CIRP J Manuf Sci Technol 7(1):20–28
107.
Hague R, Campbell I, Dickens P (2003) Implications on design of rapid manufacturing. Proc Inst Mech Eng C J Mech Eng Sci 217(1):25–30
108.
Prüß H, Vietor T (2015) Design for fiber-reinforced additive manufacturing. J Mech Des 137(11):111409
109.
Das P et al (2017) Selection of build orientation for optimal support structures and minimum part errors in additive manufacturing. Computer-Aided Design and Applications 14(sup1):1–13MathSciNet
110.
Zhang Y, Bernard A, Harik R, Karunakaran KP (2017) Build orientation optimization for multi-part production in additive manufacturing. J Intell Manuf 28(6):1393–1407
111.
Panesar A, Brackett D, Ashcroft I, Wildman R, Hague R (2015) Design framework for multifunctional additive manufacturing: placement and routing of three-dimensional printed circuit volumes. J Mech Des 137(11):111414
112.
Alharbi N, Osman R, Wismeijer D (2016) Effects of build direction on the mechanical properties of 3D-printed complete coverage interim dental restorations. J Prosthet Dent 115(6):760–767
113.
Gorguluarslan RM, Park SI, Rosen DW, Choi SK (2015) A multilevel upscaling method for material characterization of additively manufactured part under uncertainties. J Mech Des 137(11):111408
114.
Zhao, D., M. Li, and Y. Liu, Self-supporting topology optimization for additive manufacturing. arXiv preprint arXiv:1708.07364, 2017
115.
Gaynor, A.T., Topology optimization algorithms for additive manufacturing. 2015
116.
Gaynor AT, Guest JK (2016) Topology optimization considering overhang constraints: eliminating sacrificial support material in additive manufacturing through design. Struct Multidiscip Optim 54(5):1157–1172MathSciNet
117.
Patterson AE, Messimer SL, Farrington PA (2017) Overhanging features and the SLM/DMLS residual stresses problem: review and future research need. Technologies 5(2):15
118.
Suri R (1988) A new perspective on manufacturing systems analysis. Design and Analysis of Integrated Manufacturing Systems:118–133
119.
Chua CK, Wong CH, Yeong WY (2017) Chapter eight. Benchmarking for additive manufacturing. In: Chua CK, Wong CH, Yeong WY (eds) Standards, quality control, and measurement sciences in 3D printing and additive manufacturing. Academic Press, pp 181–212
120.
Hudson J, Liu E, Crampin S (1996) The mechanical properties of materials with interconnected cracks and pores. Geophys J Int 124(1):105–112
121.
Chawla N, Deng X (2005) Microstructure and mechanical behavior of porous sintered steels. Mater Sci Eng A 390(1):98–112
122.
Gupta SK, Regli WC, Das D, Nau DS (1997) Automated manufacturability analysis: a survey. Res Eng Des 9(3):168–190
123.
Dong G, Marleau-Finley J, Zhao YF (2019) Investigation of electrochemical post-processing procedure for Ti-6Al-4V lattice structure manufactured by direct metal laser sintering (DMLS). Int J Adv Manuf Technol 104(9):3401–3417
124.
Aboulkhair NT, Simonelli M, Parry L, Ashcroft I, Tuck C, Hague R (2019) 3D printing of Aluminium alloys: additive manufacturing of Aluminium alloys using selective laser melting. Prog Mater Sci 106:100578
125.
126.
127.
128.
Rehme, O. and C. Emmelmann, Reproducibilty for properties of selective laser melting. In: Third International WLT-Conference in Laser Manufacturing. 2005. Munich
129.
Averyanova M, Bertrand P, Verquin B (2011) Studying the influence of initial powder characteristics on the properties of final parts manufactured by the selective laser melting technology: a detailed study on the influence of the initial properties of various martensitic stainless steel powders on the final microstructures and mechanical properties of parts manufactured using an optimized SLM process is reported in this paper. Virtual and Physical Prototyping 6(4):215–223
Metadaten
Titel
Manufacturability analysis of metal laser-based powder bed fusion additive manufacturing—a survey
verfasst von
Ying Zhang
Sheng Yang
Yaoyao Fiona Zhao
Publikationsdatum
09.08.2020
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 1-2/2020
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-020-05825-6

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