Research Papers

Design and Implementation of a Multisensor Coaxial Monitoring System With Correction Strategies for Selective Laser Melting of a Maraging Steel

[+] Author and Article Information
Ali Gökhan Demir

Department of Mechanical Engineering,
Politecnico di Milano Via La Masa 1,
Milan 20156, Italy
e-mail: aligokhan.demir@polimi.it

Chiara De Giorgi

Department of Mechanical Engineering,
Politecnico di Milano Via La Masa 1,
Milan 20156, Italy
e-mail: chiara.degiorgi@polimi.it

Barbara Previtali

Department of Mechanical Engineering,
Politecnico di Milano Via La Masa 1,
Milan 20156, Italy
e-mail: barbara.previtali@polimi.it

1Corresponding author.

Manuscript received February 23, 2017; final manuscript received November 14, 2017; published online February 5, 2018. Assoc. Editor: Hongqiang Chen.

J. Manuf. Sci. Eng 140(4), 041003 (Feb 05, 2018) (14 pages) Paper No: MANU-17-1113; doi: 10.1115/1.4038568 History: Received February 23, 2017; Revised November 14, 2017

Development of monitoring devices becomes crucially important in selective laser melting (SLM) due to the high process complexity and the high value of the products obtained. This work discusses the design of a coaxial monitoring system for SLM using multiple sensors. In particular, an optical model is developed for the propagation of the process emission from the workpiece to the monitoring module. The model is used to determine the field of view (FOV) around the monitored zone. The lens arrangements and the optical filters are chosen according to the model results. They were implemented to construct a monitoring module consisting of two cameras viewing visible and near-infrared wavelength bands, as well as a photodiode viewing the back-reflected laser emission, all integrated in a coaxial configuration. The system functionality is tested with a prototype SLM machine during the processing of 18Ni300 maraging steel, a material known to be prone to porosity. In particular, different remelting strategies were employed as possible correction strategies to reduce porosity. The signals were interpreted as being indicators of the change in absorptivity of the laser light by the powder bed, of the plasma and molten pool, as well as of the evolution of the temperature field.

Copyright © 2018 by ASME
Your Session has timed out. Please sign back in to continue.


Kawahito, Y. , Mizutani, M. , and Katayama, S. , 2007, “ Elucidation of High-Power Fibre Laser Welding Phenomena of Stainless Steel and Effect of Factors on Weld Geometry,” J. Phys. D Appl. Phys., 40(19), pp. 5854–5859. [CrossRef]
Gong, H. , Rafi, K. , Gu, H. , Starr, T. , and Stucker, B. , 2014, “ Analysis of Defect Generation in Ti-6Al-4V Parts Made Using Powder Bed Fusion Additive Manufacturing Processes,” Addit. Manuf., 1(1–4), pp. 87–98. [CrossRef]
Qiu, C. , Panwisawas, C. , Ward, M. , Basoalto, H. C. , Brooks, J. W. , and Attallah, M. M. , 2015, “ On the Role of Melt Flow Into the Surface Structure and Porosity Development During Selective Laser Melting,” Acta Mater., 96, pp. 72–79. [CrossRef]
Song, B. , Zhao, X. , Li, S. , Han, C. , Wei, Q. , Wen, S. , Liu, J. , and Shi, Y. , 2015, “ Differences in Microstructure and Properties Between Selective Laser Melting and Traditional Manufacturing for Fabrication of Metal Parts: A Review,” Front. Mech. Eng., 10(2), pp. 111–125. [CrossRef]
Harrison, N. J. , Todd, I. , and Mumtaz, K. , 2015, “ Reduction of Micro-Cracking in Nickel Superalloys Processed by Selective Laser Melting: A Fundamental Alloy Design Approach,” Acta Mater., 94, pp. 59–68. [CrossRef]
Kruth, J. P. , Froyen, L. , Van Vaerenbergh, J. , Mercelis, P. , Rombouts, M. , and Lauwers, B. , 2004, “ Selective Laser Melting of Iron-Based Powder,” J. Mater. Process. Technol., 149(1–3), pp. 616–622. [CrossRef]
Weller, C. , Kleer, R. , and Piller, F. T. , 2015, “ Economic Implications of 3D Printing: Market Structure Models in Light of Additive Manufacturing Revisited,” Int. J. Prod. Econ., 164, pp. 43–56. [CrossRef]
Hole, C. , 2016, “ Cost and Practicality of in-Process Monitoring for Metal Additive Manufacturing,” Met Addit. Manuf., 2(4), pp. 63–69.
Tapia, G. , and Elwany, A. , 2014, “ A Review on Process Monitoring and Control in Metal-Based Additive Manufacturing,” ASME J. Manuf. Sci. Eng., 136(6), p. 060801. [CrossRef]
Everton, S. K. , Hirsch, M. , Stravroulakis, P. , Leach, R. K. , and Clare, A. T. , 2016, “ Review of In-Situ Process Monitoring and in-Situ Metrology for Metal Additive Manufacturing,” Mater. Des., 95, pp. 431–445. [CrossRef]
Craeghs, T. , Clijsters, S. , Yasa, E. , Bechmann, F. , Berumen, S. , and Kruth, J. P. , 2011, “ Determination of Geometrical Factors in Layerwise Laser Melting Using Optical Process Monitoring,” Opt. Lasers Eng., 49(12), pp. 1440–1446. [CrossRef]
Clijsters, S. , Craeghs, T. , Buls, S. , Kempen, K. , and Kruth, J. P. , 2014, “ In Situ Quality Control of the Selective Laser Melting Process Using a High-Speed, Real-Time Melt pool Monitoring System,” Int. J. Adv. Manuf. Technol., 75(5–8), pp. 1089–1101. [CrossRef]
Berumen, S. , Bechmann, F. , Lindner, S. , Kruth, J.-P. , and Craeghs, T. , 2010, “ Quality Control of Laser- and Powder Bed-Based Additive Manufacturing (AM) Technologies,” Phys. Proc., 5(Pt. B), pp. 617–622. [CrossRef]
Craeghs, T. , Clijsters, S. , Kruth, J.-P. , Bechmann, F. , and Ebert, M.-C. , 2012, “ Detection of Process Failures in Layerwise Laser Melting With Optical Process Monitoring,” Phys Procedia, 39, pp. 753–759. [CrossRef]
Craeghs, T. , Clijsters, S. , Yasa, E. , and Kruth, J.-P. , 2011, “ Online Quality Control of Selective Laser Melting,” 22nd Annual International Solid Freeform Fabrication (SFF), Austin, TX, Aug. 8–10, pp. 212–226.
Craeghs, T. , Bechmann, F. , Berumen, S. , and Kruth, J. P. , 2010, “ Feedback Control of Layerwise Laser Melting Using Optical Sensors,” Phys Procedia, 5(Pt. b), pp. 505–514. [CrossRef]
Kanko, J. A. , Sibley, A. P. , and Fraser, J. M. , 2016, “ In Situ Morphology-Based Defect Detection of Selective Laser Melting Through Inline Coherent Imaging,” J. Mater. Process. Technol., 231, pp. 488–500. [CrossRef]
Neef, A. , Seyda, V. , Herzog, D. , Emmelmann, C. , Schönleber, M. , and Kogel-Hollacher, M. , 2014, “ Low Coherence Interferometry in Selective Laser Melting,” Phys Procedia, 56, pp. 82–89. [CrossRef]
Thombansen, U. , Gatej, A. , and Pereira, M. , 2014, “ Process Observation in Fiber Laser–Based Selective Laser Melting,” Opt. Eng., 54(1), p. 011008. [CrossRef]
Kleszczynski, S. , Jocobsmuhlen, J. Z. , and Sehrt, J. T. , 2012, “ Error Detection in Laser Beam Melting Systems by High Resolution Imaging,” 23rd Annual International Solid Freeform Fabrication Symposium (SFF), Austin, TX, Aug. 6–8, pp. 1–13.
Krauss, H. , Eschey, C. , and Zaeh, M. F. , 2012, “ Thermography for Monitoring the Selective Laser Melting Process,” 23rd Annual International Solid Freeform Fabrication Symposium (SFF), Austin, TX, Aug. 6–8, pp. 999–1014.
Furumoto, T. , Ueda, T. , Alkahari, M. R. , and Hosokawa, A. , 2013, “ Investigation of Laser Consolidation Process for Metal Powder by Two-Color Pyrometer and High-Speed Video Camera,” CIRP Ann. Manuf. Technol., 62(1), pp. 223–226. [CrossRef]
Yadroitsev, I. , Krakhmalev, P. , and Yadroitsava, I. , 2014, “ Selective Laser Melting of Ti6Al4V Alloy for Biomedical Applications: Temperature Monitoring and Microstructural Evolution,” J. Alloys Compd., 583, pp. 404–409. [CrossRef]
Grasso, M. , Laguzza, V. , Semeraro, Q. , and Colosimo, B. M. , 2016, “ In-Process Monitoring of Selective Laser Melting: Spatial Detection of Defects Via Image Data Analysis,” ASME J. Manuf. Sci. Eng., 139(5), p. 051001. [CrossRef]
Liu, Y. , Yang, Y. , Mai, S. , Wang, D. , and Song, C. , 2015, “ Investigation Into Spatter Behavior During Selective Laser Melting of AISI 316 L Stainless Steel Powder,” Mater. Des., 87, pp. 797–806. [CrossRef]
Matthews, M. J. , Guss, G. , Khairallah, S. A. , Rubenchik, A. M. , Depond, P. J. , and King, W. E. , 2016, “ Denudation of Metal Powder Layers in Laser Powder Bed Fusion Processes,” Acta Mater., 114, pp. 33–42. [CrossRef]
Lane, B. , Whitenton, E. , and Moylan, S. , 2016, “ Multiple Sensor Detection of Process Phenomena in Laser Powder Bed Fusion,” Proc. SPIE, 9861, p. 986104.
Hirvimäki, M. , Manninen, M. , Lehti, A. , Happonen, A. , Salminen, A. , and Nyrhilä, S. , 2013, “ Evaluation of Different Monitoring Methods of Laser Additive Manufacturing of Stainless Steel,” Adv. Mater. Res., 651, pp. 812–819. [CrossRef]
Furumoto, T. , Ueda, T. , Kobayashi, N. , Yassin, A. , Hosokawa, A. , and Abe, S. , 2009, “ Study on Laser Consolidation of Metal Powder With Yb:fiber Laser-Evaluation of Line Consolidation Structure,” J. Mater. Process. Technol., 209(18–19), pp. 5973–5980. [CrossRef]
Demir, A. G. , and 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(5–8), pp. 2697–2709. [CrossRef]
Demir, A. G. , Colombo, P. , and Previtali, B. , 2017, “ From Pulsed to Continuous Wave Emission in SLM with Contemporary Fiber Laser Sources: Effect of Temporal and Spatial Pulse Overlap in Part Quality,” Int. J. Adv. Manuf. Technol., 91(5–8), pp. 2701–2714. [CrossRef]
Kaierle, S. , Abels, P. , and Kratzsch, C. , 2005, “ Process Monitoring and Control for Laser Materials Processing—An Overview,” Third International WLT-Conference Lasers in Manufacturing (LIM), Munich, Germany, June 13–16, pp. 101–105.
Colombo, D. , Colosimo, B. M. , and Previtali, B. , 2013, “ Comparison of Methods for Data Analysis in the Remote Monitoring of Remote Laser Welding,” Opt. Lasers Eng., 51(1), pp. 34–46. [CrossRef]
Spears, T. G. , and Gold, S. A. , 2016, “ In-Process Sensing in Selective Laser Melting (SLM) Additive Manufacturing,” Integr. Mater. Manuf. Innov., 5(2), pp. 1–25.
Mumtaz, K. A. , and Hopkinson, N. , 2010, “ Selective Laser Melting of Thin Wall Parts Using Pulse Shaping,” J. Mater. Process. Technol., 210(2), pp. 279–287. [CrossRef]
Oiwa, S. , Kawahito, Y. , and Katayama, S. , 2009, “ Optical Properties of Laser Induced Plasma During High Power Laser Welding,” 28th International Congress on Applications of Lasers & Electro-Optics (ICALEO), Orlando, FL, Nov. 2–5, pp. 359–365.
Wang, C.-M. , Meng, X.-X. , Huang, W. , Hu, X.-Y. , and Duan, A.-Q. , 2011, “ Role of Side Assisting Gas on Plasma and Energy Transmission During CO2 Laser Welding,” J. Mater. Process. Technol., 211(4), pp. 668–674. [CrossRef]
Miyamoto, J. T. , and Inoue, T. , 2002, “ Characterizing Keyhole Plasma Light Emission and Plasma Plume Scattering for Monitoring 20 kW Class Laser Welding Processes Characterizing Keyhole Plasma Light Emission and Plasma Plume Scattering for Monitoring 20 kW Class CO 2 Laser Welding Processes,” J. Laser Appl., 14(3), pp. 146–153. [CrossRef]
Colombo, D. , and Previtali, B. , 2010, “ Through Optical Combiner Monitoring of Fiber Laser Processes,” Int. J. Mater. Form., 3(Suppl. 1), pp. 1123–1126. [CrossRef]
Pedrotti, L. , 2008, “Basic Geometrical Optics,” Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, accessed Dec. 5, 2017, https://spie.org/Documents/Publications/00%20STEP%20Module%2003.pdf
Yasa, E. , Kempen, K. , and Kruth, J. , 2010, “ Microstructure and Mechanical Properties of Maraging Steel 300 After Selective Laser Melting,” 21st International Solid Freeform Fabrication Symposium (SFF), Austin, TX, Aug. 9–11, pp. 383–396.
Demir, A. G. , Monguzzi, L. , and Previtali, B. , 2017, “ Selective Laser Melting of Pure Zn With High Density for Biodegradable Implant Manufacturing,” Addit. Manuf., 15, pp. 20–28. [CrossRef]
Demir, A. G. , Pangovski, K. , O'Neill, W. , and Previtali, B. , 2015, “ Investigation of Pulse Shape Characteristics on the Laser Ablation Dynamics of TiN Coatings in the Ns Regime,” J. Phys. D Appl. Phys., 48, p. 235202. [CrossRef]
Spierings, A. B. , and Levy, G. , 2009, “ Comparison of Density of Stainless Steel 316 L Parts Produced With Selective Laser Melting Using Different Powder Grades,” 20th Annual International Solid Freeform Fabrication Symposium (SFF), Austin, TX, Aug. 3–5, pp. 342–353.
Mcvey, R. W. , Melnychuk, R. M. , Todd, J. A. , and Martukanitz, R. P. , 2007, “ Absorption of Laser Irradiation in a Porous Powder Layer,” J. Laser Appl., 19(4), pp. 214–224. [CrossRef]
Bi, G. , Gasser, A. , Wissenbach, K. , Drenker, A. , and Poprawe, R. , 2006, “ Characterization of the Process Control for the Direct Laser Metallic Powder Deposition,” Surf. Coat. Technol., 201(6), pp. 2676–2683. [CrossRef]
Ferrar, B. , Mullen, L. , Jones, E. , Stamp, R. , and Sutcliffe, C. J. , 2012, “ Gas Flow Effects on Selective Laser Melting (SLM) Manufacturing Performance,” J. Mater. Process. Technol., 212(2), pp. 355–364. [CrossRef]
Yasa, E. , and Kruth, J. P. , 2010, “ Investigation of Laser and Process Parameters for Selective Laser Erosion,” Precis. Eng., 34(1), pp. 101–112. [CrossRef]


Grahic Jump Location
Fig. 1

(a) Generic description of object, image and lens distances in a three-lens configuration and (b) schematic disposition of the implemented optical arrangement in the monitoring module

Grahic Jump Location
Fig. 2

(a) Schematic representation of the monitoring module and (b) the implemented system

Grahic Jump Location
Fig. 3

Photograph of the realized specimens

Grahic Jump Location
Fig. 4

Effect of process parameters on the part porosity. Error bars represent standard deviation.

Grahic Jump Location
Fig. 5

Example of signal acquired with the laser channel depicting (a) volume and remelting passes and (b) zoomed signal showing back-reflected laser pulses

Grahic Jump Location
Fig. 6

Examples of images and signal acquired with the visible channel depicting (a) melt pool collapse (ton = 70 μs, Nl = 32, volume pass), (b) signal intensity showing instances of melt pool separation and spark generation (ton = 80 μs, Nl = 32, volume pass). Images show an area of 1 × 1 mm2.

Grahic Jump Location
Fig. 7

Example of signal dynamics acquired with the NIR channel depicting change in thermal emission at the remelting pass (Nl = 32, SR)

Grahic Jump Location
Fig. 8

Mean value of back-reflected laser intensity as a function of process parameters

Grahic Jump Location
Fig. 9

Mean value of image intensity in the visible bandwidth as a function of process parameters

Grahic Jump Location
Fig. 10

Mean value of image intensity in the NIR bandwidth as a function of process parameters

Grahic Jump Location
Fig. 11

(a) Change in mean intensity of visible channel at volume pass over different layer as a function of total energy and (b) relationship between visible mean intensity and porosity. The dashed lines are for visualizing the trend only. Error bars represent standard deviation.



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In