The process of Selective Laser Melting (SLM) is an innovative technology for rapid prototyping that can be included among the SFF (Solid Freeform Fabrication) techniques, which are characterized by "free-form" manufacturing of solid parts. SLM is an additive technology that operates starting from the data encoded in the three-dimensional computer aided design (CAD) file of the component to be built. After the slicing operation made on the 3D model of the component, the consequent data file is sent to a computer-controlled laser device that fuses successive layers of metal powder to create the three-dimensional product. The SLM is a technological process which involves optical, thermal and solidification phenomena; thus the analysis of the process is rather complex. This work aims to study the molten/solidified zone in SLM samples through the experimental analysis of the shape and the size of laser tracks. The functional relationships between dimensional parameter of the molten/solidified track and the main parameters used to control the process was identified. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Friction Stir Welding (FSW) is a solid-state joining process; i.e., no melting occurs. The welding process is promoted by the rotation and translation of an axis-symmetric non-consumable tool along the weld centerline. Thus, the FSW process is performed at much lower temperatures than conventional fusion welding, nevertheless it has some disadvantages. The laser Assisted Friction Stir Welding (LAFSW) combines a Friction Stir Welding machine and a laser system. Laser power is used to preheat and to plasticize the volume of the workpiece ahead of the rotating tool; the workpiece is then joined in the same way as in the conventional FSW process. In this work an Ytterbium fiber laser with maximum power of 4 kW and a commercial FSW machine were coupled. Both FSW and LAFSW tests were conducted on 3 mm thick 5754H111 aluminum alloy plates in lap joint configuration with a constant tool rotation rate and with different feed rates. The two processes were compared and evaluated in terms of differences in the microstructure and in the micro-hardness profile.

Friction Stir Welding (FSW) has demonstrated a significant potential for joining low melting point non-ferrous metals in several joint configurations. During FSW metals are joined in the solid state due to the heat generated by the friction and flow of metal by the stirring action of a pinned tool. This paper reports an experimental investigation on the effects of geometry and surface coating of the tool shoulder on the defectiveness, the microstructure and the microhardness of a 3 mm thick 5754H11 aluminium alloy butt weld. During the experiments the diameter and slope of the shoulder varied. Moreover a tungsten carbide coated was tested. The pin geometry and dimensions were kept constant. Four different tools for shoulder geometry and coating condition were tested. The weld was characterized in terms of the bead morphology and the grain size. The weld microhardness profile was measured for all the microstructural zones of the friction stir welding process. The obtained results provide a deeper knowledge of the effect of the tool shoulder geometry and surface condition on the aluminium alloy weldability

Laser milling (LM) can be classified as a layer manufacturing process in which the material is removed by a laser beam by means of the ablation mechanism. It is a laser machining process which uses a laser beam to produce 3D shapes into a wide variety ofmaterials. It is also known as laser ablation. It shows clear advantages versus the traditional milling such as the unlimited choice of materials, the direct use of computer-aided design structure data, the high geometric flexibility, and the touchless tool. LM requires the selection of optimal machining parameters for the job. Unlike the mechanical milling and themechanical incision, the depth of the single removed layer is chosen at the beginning as input parameter of the process. In LM, the ablated depth depends from the process parameters such as laser power, scan speed, pulse duration, and pulse frequency. This work aims to develop an algorithm that can predict the parameters necessary to execute the material removal with a preset ablation depth. Using the results of an experimental campaign, the laser milling process was modeled by means of a back-propagation artificial neural network. Then, an iterative algorithm, based on the previous trained neural network, permitted to calculate the scanning velocity and pulse frequency that approached for the best the preset ablation depth. The developed approach represents a mean for the rational selection of laser ablation process parameters. It can be performed in an intuitive manner since it uses simple artificial intelligence like the artificial neural network.

Selective Laser Melting (SLM) is actually the most attractive technique in an Additive Manufacturing (AM) technology because of the possibility to build layer by layer up nearly full density metallic components without needing for post-processing. One of the main problems in SLM processes is represented by the thermal distortion of the model during forming; the part tends to be deformed and cracked due to the thermal stress. Therefore, it is important to know the effect of the process parameters on the molten zone and consequently on the density of the consolidated material. Great advantage can be obtained from the prediction of temperature evolution and distribution. The aim of this study is to evaluate the influence of the process parameters on the temperature evolution in a 3D model. The developed code evaluates the distribution and evolution of the temperatures in the SLM process and simulates the powder-liquid-solid change by means of a check of the nodes temperature.

The paper investigates the fabrication of Selective Laser Melting (SLM) titanium alloy Ti6Al4V micro-lattice structures for the production of lightweight components. Specifically, the pillar textile unit cell is used as base lattice structure and alternative lattice topologies including reinforcing vertical bars are also considered. Detailed characterizations of dimensional accuracy, surface roughness, and micro-hardness are performed. In addition, compression tests are carried out in order to evaluate the mechanical strength and the energy absorbed per unit mass of the lattice truss specimens made by SLM. The built structures have a relative density ranging between 0.2234 and 0.5822. An optimization procedure is implemented via the method of Taguchi to identify the optimal geometric configuration which maximizes peak strength and energy absorbed per unit mass.