The paper presents results of studies on Selective Laser Melting. SLM is an additive manufacturing technology
which may be used to process almost all metallic materials in the form of powder. Types of energy emission
sources, mainly fiber lasers and/or Nd:YAG laser with similar characteristics and the wavelength of 1,06 - 1,08
microns, are provided primarily for processing metallic powder materials with high absorption of laser radiation.
The paper presents results of selected variable parameters (laser power, scanning time, scanning strategy) and fixed
parameters such as the protective atmosphere (argon, nitrogen, helium), temperature, type and shape of the powder
material. The thematic scope is very broad, so the work was focused on optimizing the process of selective laser
micrometallurgy for producing fully dense parts. The density is closely linked with other two conditions:
discontinuity of the microstructure (microcracks) and stability (repeatability) of the process. Materials used for the
research were stainless steel 316L (AISI), tool steel H13 (AISI), and titanium alloy Ti6Al7Nb (ISO 5832-11).
Studies were performed with a scanning electron microscope, a light microscopes, a confocal microscope and a
Laser triangulation method is not applicable in all possible areas, due to the presence of numerous disturbances.
The method of predictive segmentation of laser line resistant to interference, which allows use in industrial
quality control of the glossy elements, has been proposed. It requires precise synchronization with the CAD
model of the scanned item. Very high accuracy of positioning is required to enable predictive segmentation of
laser prole. -The worse positioning, the widest condential intervals, and worse algorithm's ability to reject
The most universal way to synchronize the model of a part under laser scanning, with its virtual model,
is to use an extra camera and some 3D matching software. This solution, however, is rather of poor accuracy
-even if a high quality optics is used. Kalman ltering is used to reduce the deviation of results. To avoid
problems in description of such complicated system, a coherent and homogeneous mathematical description has
been proposed. It uses so-called Denavit-Hartenberg notation, widely used in robotics.
Several tests has been carried out to verify the 3D matching algorithm for object-model synchronization during
laser scanning. The results show clearly that the accuracy of matching can be improved by using Kalman ltering
-even up to 10 times. Thanks to it, its accuracy increases to face the requirements of predictive segmentation
Accuracy and robustness of 3D inspection methods, which are based on structural lightening, strongly depend on surface
reflectance and its geometry. If the intensity of light profile undergoes disturbances or the image is interfered with
reflection artefacts, then the algorithms for height determination fail.
The paper presents a method for predictive light profile line segmentation which employs information from 3D model of
inspected object. Besides calculation of profile position, based on confidence intervals, the advantage of surface normal
pitch and surface scattering are utilized. The necessary information is calculated based on STL object model and surface
description extension. The developed algorithm includes error model of camera and laser optics, what corrects distortion
The developed solution increases accuracy and robustness of machine vision quality inspection systems especially based
on laser triangulation.
Machine Vision systems for manufacturing quality inspection are interdisciplinary solutions including lighting, optics,
cameras, image processing, segmentation, feature analysis, classification as well as integration with manufacturing
process. The design and optimization of the above systems, especially image acquisition setup is mainly driven by experiment. This requires deep know-how and well equipped laboratory, which does not guarantee the optimal development process and results. This paper proposes novel usage of rendering, originating from 3D computer graphics, for machine vision prototyping and optimization. The invented technique and physically-based rendering aids selection or optimization of luminaires, tolerancing of mechanical construction and object handling, robustness predetermination or surface flaw simulation. The
rendering setup utilizes mesh modeling, bump and normal mapping and light distribution sharpening with IES data files. The performed light simulation experiments for metal surfaces (face surface of bearing rollers) are validated.