In an attempt to find a solution similar to the FDM 3D printers which would allow cost-effective and reliable additive manufacturing of metal components, this paper proposes a three-axis WAAM system capable of reliably printing small, near-net-shape metal objects. The system consists of gas metal arc (GMA) process equipment, a three-axis CNC positioning system, the interpass temperature control and forced cooling of the base plate and the deposit. The main challenge addressed is the minimisation of shape distortions caused by excessive heat accumulation when printing small objects. The interpass temperature control uses an IR pyrometer to remotely measure the last deposited layer and a control system to keep the interpass temperature below the predefined value by stopping the deposition after each layer in order to allow the deposit to cool. This results in a stable and more repeatable shape of the deposit, even when the heat transfer conditions are changing during the build-up process. The combination of adaptive interlayer dwell time and forced cooling significantly improves system productivity. Open-source NC control and path generation software is used, which enables fast and easy creation of the control code. Different control methods are evaluated through the printing of simple walls, and the printing accuracy is evaluated by printing small shell objects. As the results show, the interpass temperature control allows small objects to be printed at near-net shape with a deviation of 2%, which means that successful printing of 3D shapes can be achieved without trial and error approach.

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Contemporary 3D digitization systems employed by reverse engineering (RE) feature ever-growing scanning speeds with the ability to generate large quantity of points in a unit of time. Although advantageous for the quality and efficiency of RE modelling, the huge number of point datas can turn into a serious practical problem, later on, when the CAD model is generated. In addition, 3D digitization processes are very often plagued by measuring errors, which can be attributed to the very nature of measuring systems, various characteristics of the digitized objects and subjective errors by the operator, which also contribute to problems in the CAD model generation process. This paper presents an integral system for the pre-processing of point data, i.e., filtering, smoothing and reduction, based on a cross-sectional RE approach. In the course of the proposed system development, major emphasis was placed on the module for point data reduction, which was designed according to a novel approach with integrated deviation analysis and fuzzy logic reasoning. The developed system was verified through its application on three case studies, on point data from objects of versatile geometries obtained by contact and laser 3D digitization systems. The obtained results demonstrate the effectiveness of the system.

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