Investigation of the dimensional accuracy using image processing techniques in powder bed fusion

Abstract

In this study, a sample part is manufactured by using the Powder Bed Fusion (PBF) method with maraging steel metal powder, and the manufactured part is examined in terms of dimensional accuracy by image processing techniques. The sample =art is drawn with various geometric shapes so that dimensional and areal controlling with the image processing techniques can be performed accurately. The purpose of dimensional control is to choose the most suitable manufacturing parameters to ensure the closest production of the real dimensions of the part. With the detection of significant deviations in dimensional values by image processing techniques, the designs of the part should be changed according to these deviations. In this study, each layer of the manufactured sample part image is captured by a camera. Afterward, dimensional and areal percent error rates are determined by three different methods based on image processing techniques.

Distributed System Design Based on Image Processing Technology and Resource State Synchronization Method

“…Image processing technology often includes image clipping, image enhancement, filtering, gray-scale processing, etc. [6][7]. Because this technology is based on the input and output of computer experimental images, it has the advantages of simple method, time-saving, labor-saving, small error, and intuitive results.…”

Image Processing Approach to Investigate the Correlation between Machining Parameters and Burr Formation in Micro-Milling Processes of Selective-Laser-Melted AISI 316L

“…Image processing is a technique that transforms the obtained image signals into a form that can be interpreted electronically (with the help of computers and software) with certain algorithms or a method used to extract some useful information from images [ 34 , 35 , 36 , 37 ]. Various measurement methods such as screen calipers, three-dimensional optical profilometers, image processing software, and machine learning algorithms are used to predict and measure slit and burr measurements [ 23 , 38 , 39 ].…”

Characterization of 3D metal printed cutting tool with transpiration cooling channels

“…Here, this work examines the printed geometries and suggest suitable orientation for cooling through TC method. Traditional methods like optical microscopy, CMM, and 3D scanning are used to verify dimensions of the 3D printed component [12][13][14][15]. The surface profilometers (contact and non-contact) measure external features and the conventional methods have limitations, unable to measure interior features with higher accuracy.…”