Abstract
The poor surface quality during the laser powder bed fusion (L-PBF) process adversely impacts the mechanical properties of the final product and even can result in failure of the process. This study aims at minimizing the top surface roughness of the parts manufactured by the L-PBF process by deploying a feedforward plus feedback control system. The most common factors affecting the surface quality, namely, balling, lack of inter-track overlap, overlapping curvature of laser scan tracks, and spatters, were investigated through a monitoring system consisting of a high-speed camera, a zooming lens, and a short-pass filter. The desired melt pool width and the critical value for the level of spatters were determined using the imaging system and subsequent image processing. An experimental model was developed, and the control system was designed accordingly. The performance of the control system was evaluated by simulations and experiments. In all cases, the control system showed an excellent transient performance to reach the desired melt pool width only after printing a few layers. The results obtained from this study showed that the average arithmetic mean surface roughness value (Sa) reduced from 10.48 to 5.91 \({\mu m}\) and from 9.61 to 6.64 \({\mu m}\) at 500 mm/s and 400 mm/s scanning speed, respectively. In addition, evaluating the controller on a bridge geometry showed that controlling the geometry of the melt pool can mitigate significant defects occurring during the process and minimize the top surface roughness.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Codes are available from the corresponding author upon reasonable request.
Abbreviations
- AM:
-
Additive manufacturing
- CAD:
-
Computer-aided design
- EDM:
-
Electrical discharge machining
- FB:
-
Feedback
- FF:
-
Feedforward
- L-PBF:
-
Laser powder bed fusion
- MPC:
-
Model predictive control
- PD:
-
Proportional derivative
- PID:
-
Proportional–integral–derivative
- PM:
-
Partially melted
- SEM:
-
Scanning electron microscopy
- UM:
-
Un-melted
References
DebRoy T, Wei HL, Zuback JS, Mukherjee T, Elmer JW, Milewski JO, Beese AM, Wilson-Heid A, De A, Zhang W (2018) Additive manufacturing of metallic components – process, structure and properties. Prog Mater Sci 92:112–224. https://doi.org/10.1016/j.pmatsci.2017.10.001
Nadammal N, Mishurova T, Fritsch T, Serrano-Munoz I, Kromm A, Haberland C, Portella PD, Bruno G (2021) Critical role of scan strategies on the development of microstructure, texture, and residual stresses during laser powder bed fusion additive manufacturing. Addit Manuf 38:101792. https://doi.org/10.1016/J.ADDMA.2020.101792
Ghoncheh MH, Sanjari M, Zoeram AS, Cyr E, Amirkhiz BS, Lloyd A, Haghshenas M, Mohammadi M (2021) On the microstructure and solidification behavior of new generation additively manufactured Al-Cu-Mg-Ag-Ti-B alloys. Addit Manuf 37:101724. https://doi.org/10.1016/J.ADDMA.2020.101724
Fereiduni E, Ghasemi A, Elbestawi M (2020) Selective laser melting of aluminum and titanium matrix composites: recent progress and potential applications in the aerospace industry. Aerospace. https://doi.org/10.3390/AEROSPACE7060077
King WE, Anderson AT, Ferencz RM, Hodge NE, Kamath C, Khairallah SA, Rubenchik AM (2015) Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges. Appl Phys Rev 2:041304. https://doi.org/10.1063/1.4937809
Sanchez S, Smith P, Xu Z, Gaspard G, Hyde CJ, Wits WW, Ashcroft IA, Chen H, Clare AT (2021) Powder bed fusion of nickel-based superalloys: a review. Int J Mach Tools Manuf 165:103729. https://doi.org/10.1016/J.IJMACHTOOLS.2021.103729
Narvan M, Al-Rubaie KS, Elbestawi M (2019) Process-structure-property relationships of AISI H13 tool steel processed with selective laser melting. Materials (Basel) 12:2284
Froes F, Boyer R (2019) Additive manufacturing for the aerospace industry. https://books.google.com/books?hl=en&lr=&id=IlSIDwAAQBAJ&oi=fnd&pg=PP1&dq=Additive+manufacturing+for+the+aerospace+industry&ots=BBCf9CDqXn&sig=0t8xb-yvqN1Z1NHWXcRyfNCsLxU (Accessed 14 Oct 2021)
Uriondo A, Esperon-Miguez M, Perinpanayagam S (2015) The present and future of additive manufacturing in the aerospace sector: a review of important aspects. 229:2132–2147. https://doi.org/10.1177/0954410014568797
Dowling L, Kennedy J, O’Shaughnessy S, Trimble D (2020) A review of critical repeatability and reproducibility issues in powder bed fusion. Mater Des 186:108346. https://doi.org/10.1016/J.MATDES.2019.108346
Echeta I, Feng X, Dutton B, Leach R, Piano S (2019) Review of defects in lattice structures manufactured by powder bed fusion. Int J Adv Manuf Technol 1065(106):2649–2668. https://doi.org/10.1007/S00170-019-04753-4
Balbaa MA, Ghasemi A, Fereiduni E, Elbestawi MA, Jadhav SD, Kruth J-P (2021) Role of powder particle size on laser powder bed fusion processability of AlSi10mg alloy. Addit Manuf 37:101630
Khorasani M, Ghasemi A, Awan US, Hadavi E, Leary M, Brandt M, Littlefair G, O’Neil W, Gibson I (2020) A study on surface morphology and tension in laser powder bed fusion of Ti-6Al-4V. Int J Adv Manuf Technol 1119(111):2891–2909. https://doi.org/10.1007/S00170-020-06221-W
Snyder JC, Thole KA (2020) Understanding laser powder bed fusion surface roughness. J Manuf Sci Eng 142:071003. https://asmedigitalcollection.asme.org/manufacturingscience/article-abstract/142/7/071003/1074958?casa_token=uW8Zv5PtNy4AAAAA:gW4LJ5YFU671VJryAnm2RAFbuSumFjHwIyKzkGBOTY-FbkuaydXAJk7Fi9w5bsUXlr8WSw (Accessed 27 Oct 2021)
Esmaeilizadeh R, Ali U, Keshavarzkermani A, Mahmoodkhani Y, Marzbanrad E, Toyserkani E (2019) On the effect of spatter particles distribution on the quality of Hastelloy X parts made by laser powder-bed fusion additive manufacturing. J Manuf Process 37:11–20. https://doi.org/10.1016/J.JMAPRO.2018.11.012
Tanigawa D, Abe N, Tsukamoto M, Hayashi Y, Yamazaki H, Tatsumi Y, Yoneyama M (2015) Effect of laser path overlap on surface roughness and hardness of layer in laser cladding. Sci Technol Weld Join 20:601–606
Grasso M, Colosimo BM (2017) Process defects and in situ monitoring methods in metal powder bed fusion: a review. Meas Sci Technol 28:044005. https://doi.org/10.1088/1361-6501/AA5C4F
Bourell D, Kruth JP, Leu M, Levy G, Rosen D, Beese AM, Clare A (2017) Materials for additive manufacturing. CIRP Ann 66:659–681. https://doi.org/10.1016/J.CIRP.2017.05.009
Li L, Li JQ, Fan TH (2021) Phase-field modeling of wetting and balling dynamics in powder bed fusion process. Phys Fluids 33:042116. https://doi.org/10.1063/5.0046771
Sola A, Nouri A (2019) Microstructural porosity in additive manufacturing: the formation and detection of pores in metal parts fabricated by powder bed fusion. J Adv Manuf Process. https://doi.org/10.1002/AMP2.10021
Snell R, Tammas-Williams S, Chechik L, Lyle A, Hernández-Nava E, Boig C, Panoutsos G, Todd I (2020) Methods for rapid pore classification in metal additive manufacturing. Jom 72:101–109. https://doi.org/10.1007/s11837-019-03761-9
Abdelrahman M, Reutzel EW, Nassar AR, Starr TL (2017) Flaw detection in powder bed fusion using optical imaging. Addit Manuf 15:1–11. https://doi.org/10.1016/j.addma.2017.02.001
Rezaeifar H, Elbestawi M (2022) Porosity formation mitigation in laser powder bed fusion process using a control approach. Opt Laser Technol 147:107611. https://doi.org/10.1016/J.OPTLASTEC.2021.107611
Fabbro R, Hamadou M, Coste F (2004) Metallic vapor ejection effect on melt pool dynamics in deep penetration laser welding. J Laser Appl 16:16–19
Nakamura H, Kawahito Y, Nishimoto K, Katayama S (2015) Elucidation of melt flows and spatter formation mechanisms during high power laser welding of pure titanium. J Laser Appl 27:32012
Matsunawa A, Kim J-D, Seto N, Mizutani M, Katayama S (1998) Dynamics of keyhole and molten pool in laser welding. J Laser Appl 10:247–254
Fabbro R, Slimani S, Doudet I, Coste F, Briand F (2006) Experimental study of the dynamical coupling between the induced vapour plume and the melt pool for Nd–Yag CW laser welding. J Phys D Appl Phys 39:394
Hassanin H, Elshaer A, Benhadj-Djilali R, Modica F, Fassi I (2018) Surface finish improvement of additive manufactured metal parts 145–164. https://doi.org/10.1007/978-3-319-68801-5_7
Fotovvati B, Balasubramanian M, Asadi E (2020) Modeling and optimization approaches of laser-based powder-bed fusion process for Ti-6Al-4V alloy. Coatings 10(1):1104. https://doi.org/10.3390/COATINGS10111104
Deng Y, Mao Z, Yang N, Niu X, Lu X (2020) Collaborative optimization of density and surface roughness of 316L stainless steel in selective laser melting. Materials (Basel). https://doi.org/10.3390/MA13071601
Yavari R, Riensche A, Tekerek E, Jacquemetton L, Halliday H, Vandever M, Tenequer A, Perumal V, Kontsos A, Smoqi Z, Cole K, Rao P (2021) Digitally twinned additive manufacturing: detecting flaws in laser powder bed fusion by combining thermal simulations with in-situ meltpool sensor data. Mater Des 211:110167. https://doi.org/10.1016/J.MATDES.2021.110167
Gunenthiram V, Peyre P, Schneider M, Dal M, Coste F, Koutiri I, Fabbro R (2018) Experimental analysis of spatter generation and melt-pool behavior during the powder bed laser beam melting process. J Mater Process Technol 251:376–386. https://doi.org/10.1016/J.JMATPROTEC.2017.08.012
Yasa E, Kruth JP, Deckers J (2011) Manufacturing by combining selective laser melting and selective laser erosion/laser re-melting. CIRP Ann - Manuf Technol 60:263–266. https://doi.org/10.1016/j.cirp.2011.03.063
Zhou J, Han X, Li H, Liu S, Yi J (2021) Materials & Design Investigation of layer-by-layer laser remelting to improve surface quality, microstructure, and mechanical properties of laser powder bed fused AlSi10Mg alloy. Mater Des 210:110092. https://doi.org/10.1016/j.matdes.2021.110092
Stief P, Dantan J, Etienne A, Siadat A (2020) ScienceDirect ScienceDirect Improving the quality of up-facing inclined surfaces in laser powder bed Improving the quality of inclined surfaces in laser powder bed fusion of metals using a dual laser setup fusion of metals using a dual laser setup new m. Procedia CIRP 94:266–269. https://doi.org/10.1016/j.procir.2020.09.050
Demir AG, Previtali B (2017) Investigation of remelting and preheating in SLM of 18Ni300 maraging steel as corrective and preventive measures for porosity reduction. Int J Adv Manuf Technol 93:2697–2709. https://doi.org/10.1007/s00170-017-0697-z
Brodie EG, Richter J, Wegener T, Niendorf T, Molotnikov A (2020) Low-cycle fatigue performance of remelted laser powder bed fusion (L-PBF) biomedical Ti25Ta. Mater Sci Eng A 798:140228. https://doi.org/10.1016/j.msea.2020.140228
Xi Z (2022) Model predictive control of melt pool size for the laser powder bed fusion process under process uncertainty. ASCE-ASME J Risk Uncert Engrg Sys Part B Mech Engrg. https://doi.org/10.1115/1.4051746
Hussain SZ, Kausar Z, Koreshi ZU, Sheikh SR, Rehman HZU, Yaqoob H, Shah MF, Abdullah A, Sher F (2021) Feedback control of melt pool area in selective laser melting additive manufacturing process. Processes. https://doi.org/10.3390/pr9091547
Vasileska E, Demir AG, Colosimo BM, Previtali B (2020) Layer-wise control of selective laser melting by means of inline melt pool area measurements. J Laser Appl 32:022057. https://doi.org/10.2351/7.0000108
Rezaeifar H, Elbestawi MA (2021) On-line melt pool temperature control in L-PBF additive manufacturing. Int J Adv Manuf Technol 112:2789–2804. https://doi.org/10.1007/s00170-020-06441-0
Brown DC (1971) Close- range camera calibration. Photogramm Eng 37:855–866
Li X, Du X, Li Y (2015) The technology research of camera calibration based on LabVIEW. Int J Res Eng Sci ISSN 3:8–17. www.ijres.org (Accessed 11 Nov 2021)
Relf C (2003) Image acquisition and processing with LabVIEW. https://books.google.com/books?hl=en&lr=&id=w38eAPw8FBcC&oi=fnd&pg=PP1&dq=image+acquisition+and+processing+&ots=vxJWQfWUSk&sig=LPzaDfxJthKU3xQuzxq5BmfiIps (Accessed 11 Nov 2021)
Jankowski M (2006) Erosion, dilation and related operators. Dep Electr Eng South Maine Portland, Maine, USA
Attarzadeh F, Fotovvati B, Fitzmire M, Asadi E (2020) Surface roughness and densification correlation for direct metal laser sintering. Int J Adv Manuf Technol 107:2833–2842. https://doi.org/10.1007/S00170-020-05194-0/FIGURES/6
Balbaa M, Mekhiel S, Elbestawi M, McIsaac J (2020) On selective laser melting of Inconel 718: densification, surface roughness, and residual stresses. Mater Des 193:108818. https://doi.org/10.1016/J.MATDES.2020.108818
Fathi A, Khajepour A, Toyserkani E, Durali M (2007) Clad height control in laser solid freeform fabrication using a feedforward PID controller. Int J Adv Manuf Technol 35:280–292
Xiong J, Yin Z, Zhang W (2016) Closed-loop control of variable layer width for thin-walled parts in wire and arc additive manufacturing. J Mater Process Technol 233:100–106
Craeghs T, Bechmann F, Berumen S, Kruth JP (2010) Feedback control of layerwise laser melting using optical sensors. Phys Procedia. https://doi.org/10.1016/j.phpro.2010.08.078
Metelkova J, Kinds Y, Kempen K, de Formanoir C, Witvrouw A, Van Hooreweder B (2018) On the influence of laser defocusing in selective laser melting of 316L. Addit Manuf 23:161–169. https://doi.org/10.1016/j.addma.2018.08.006
Chaurasia JK, Jinoop AN, Parthasarathy P, Paul CP, Bindra KS, Bontha S (2021) Study of melt pool geometry and solidification microstructure during laser surface melting of Inconel 625 alloy. Optik (Stuttg) 246:167766. https://doi.org/10.1016/j.ijleo.2021.167766
Sainte-Catherine C, Jeandin M, Kechemair D, Ricaud J-P, Sabatier L (1991) Sabatier, Study of dynamic absorptivity at 10.6 µm (CO2) and 1.06 µm (Nd-YAG) wavelengths as a function of temperature. Le J Phys IV 1:C7-151
Tu Q, Rong Y, Chen J (2020) Parameter identification of ARX models based on modified momentum gradient descent algorithm. Complexity
Guzmán JL, Hägglund T, Visioli A (2012) Feedforward compensation for PID control loops. In PID Control Third Millenn, Springer, pp. 207–234
Jin D, Lin S (2012) Advances in electronic commerce, web application and communication. Springer
Marlin TE (2000) Process control, designing processes and control systems for dynamic performance
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Hossein Rezaeifar, investigation, methodology, conceptualization, and writing—original draft. Mohamed Elbestawi, review and editing and supervision.
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Rezaeifar, H., Elbestawi, M. Minimizing the surface roughness in L-PBF additive manufacturing process using a combined feedforward plus feedback control system. Int J Adv Manuf Technol 121, 7811–7831 (2022). https://doi.org/10.1007/s00170-022-09902-w
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DOI: https://doi.org/10.1007/s00170-022-09902-w