Defect Characterization Through Automated Laser Track Trace Identification in SLM Processes Using Laser Profilometer Dat
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Defect Characterization Through Automated Laser Track Trace Identification in SLM Processes Using Laser Profilometer Data Brandon Baucher, Anil B. Chaudhary, Sudarsanam S. Babu, and Subhadeep Chakraborty (Submitted March 24, 2018; in revised form November 9, 2018) This paper presents recent developments in statistical image processing to demonstrate feasibility of layerby-layer nondestructive inspection for selective laser melting (SLM) of metallic parts. A matrix of 10 mm 3 10 mm stainless 316 squares was deposited with the first row consisting of just the sintered surface, Row 2 a single layer, Row 3 with 2 layers and so on. These layers were scanned to emulate the layer-by-layer collection of top surface geometry using a laser sensor. The resultant data were utilized to generate ISO 25718 roughness parameters and subsequently to perform track identification. This calculation consisted of two salient steps: (1) computing the gradients of surface roughness, which vanish at the peaks and pits, and (2) extracting the scanning direction by taking Hough transform of the geometry. This algorithm was repeated for all layers, and the alignment of the roughness with the rotating scan was observed to be persistent for all layers. Correlation between surface properties obtained along various scan directions and defect probability is explored. Keywords
Hough transform, NDE, SLM, track identification
1. Introduction The majority in-process monitoring efforts in SLM have focused on measurement of process signatures associated with the melt pool and surrounding heat-affected zone (HAZ). Measurements of these process signals including acoustic (Ref 1) and electromagnetic signatures show great promise for evaluating melt pool size (Ref 2), temperature (Ref 3) and stability. In addition to the melt pool, the process signatures from the powder bed (Ref 4) itself can provide valuable insight into process variation and final part quality. The goal of all such efforts is ultimately a near-real-time automated workflow for measurement, design, verification and control of uncertainty and defects in additive manufacturing (AM) processes. Layerby-layer nondestructive evaluation of surface profiles, before and after a deposit, may prove to be a critical tool in this endeavor. To demonstrate the feasibility and usefulness of layer-bylayer NDE, a series of builds and measurements of stainless steel 316 squares were made and scanned with a laser profilometer. Figure 1 outlines the details of the build, measurement and preprocessing steps. Each column in Fig. 1(a), This article is an invited paper selected from presentations at the symposium ÔAdditive Manufacturing: In-situ Process Monitoring and Control,Õ held during MS&TÕ17, October 8-12, 2017, in Pittsburgh, Pa., and has been expanded from the original presentation. Brandon Baucher and Anil B. Chaudhary, Applied Optimization, Fairborn, OH; Sudarsanam S. Babu and Subhadeep Chakraborty, University of Tennessee, Knoxville, TN. Contact e-mail: [email protected].
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