A comparison of Inconel 718 obtained with three L-PBF production systems in terms of process parameters, as-built surface quality, and fatigue performance

ndustry-grade Powder Bed Fusion (PBF) systems operated according to qualified processing parameters and procedures are expected to manufacture metal parts of highly complex geometry. However, variation of the mechanical properties of components obtained with different qualified production equipment for the same powder and production workflow has been observed. This dependence of the final L-PBF part performance on a multitude of factors is of concern for the application engineer. The present work aims to shed light on the role of process equipment on fatigue performance and focuses on Inconel 718 alloy processed by a qualified service provider using three industry-grade L-PBF systems working with different layer thicknesses. A novel method based on the use of miniature specimens is being used; this innovative approach allows to efficiently investigate fatigue behavior with less material consumption compared to standard methods and favoured by the small dimension, the coupons can be freely positioned inside the chamber to investigate different built direction and their consequent effect on mechanical properties. Sets of miniature specimens oriented along different directions with respect to build direction were fabricated with each system according to its optimized process parameters, heat-treated according to the same dual-step thermal cycle and characterized in terms of hardness, surface roughness, and finally tested in the high cycle fatigue regime with the surfaces in the as-built condition. The directional specimens exhibits degrees of anisotropic fatigue behavior in dependence of the production equip- ment. The present test results define a scatter in fatigue performance that can support the design of L-PBF Inconel 718 parts. 1. Introduction Additive manufacturing (AM) is defined according to ASTM F2792- 101 as “the process of adding materials to create objects” layer by layer from a 3D computer model as opposed to subtractive production with traditional manufacturing processes [1]. The growing interest in AM is related to the established advantages in terms of design freedom and optimization, functional integration and part consolidation, energy efficiency, reduced material waste, part customization, low volume production, and reduced manufacturing lead time [2]. Different AM technologies are available and a wide range of materials are currently processed including metals, polymers, ceramics, and concrete.[3]. The most used AM technique to produce metallic components is the Laser powder bed fusion (L-PBF) processing where laser beams are used to selectively melt, layer after layer, thin layers of metal powder spread on the built platform. The possibility to produce metal parts with no limitation in terms of geometrical complexity makes L-PBF competitive for product innovation and optimization [4,5], which is a frequent target for high performance sectors, such as aerospace, energy, motorsport [6]. From the design engineer point of view, however, it is important to be aware not only of the potential from the available production systems but also of possible limitations [7]. The L-PBF process is complex and characterized by many parameters (over 100 according to Oliveira et al. [8]), such layer thickness, scanning strategy, laser power, hatch spacing, scan time, contour, powder size, source type, part orientation in the build chamber and others. The AM technologist is expected to qualify the L-PBF process thus guaranteeing reliable part properties[9,10]. Well-established equipment manufacturers have developed optimized processing conditions for each material that result in near-theoretical material density, minimize defects, reduce surface roughness thus * Corresponding author. E-mail address: federico.uriati@unipr.it (F. Uriati). Contents lists available at ScienceDirect International Journal of Fatigue journal homepage: www.elsevier.com/locate/ijfatigue https://doi.org/10.1016/j.ijfatigue.2022.107004 Received 1 February 2022; Received in revised form 21 April 2022; Accepted 8 May 2022