journal article·2020-04-03

Optimization of digital radiography for large metallic additively manufactured components

Brant Edward Stoner, Griffin T. Jones, Sanjay Joshi, Rich Martukanitz

Rapid Prototyping Journal· Volume 26· Issue 3
Publisher page

Abstract

Purpose The continued improvement of additive manufacturing (AM) processing has led to increased part complexity and scale. Processes such as electron beam directed energy deposition (DED) are able to produce metal AM parts several meters in scale. These structures pose a challenge for current inspection techniques because of their large size and thickness. Typically, X-ray computed tomography is used to inspect AM components, but low source energies and small inspection volumes restrict the size of components that can be inspected. This paper aims to develop digital radiography (DR) as a method for inspecting multi-meter-sized AM components and a tool that optimizes the DR inspection process. Design/methodology/approach This tool, SMART DR, provides optimal orientations and the probability of detection for flaw sizes of interest. This information enables design changes to be made prior to manufacturing that improve the inspectabitity of the component and areas of interest. Findings Validation of SMART DR was performed using a 40-mm-thick stainless-steel blade produced by laser-based DED. An optimal orientation was automatically determined to allow radiographic inspection of a thickness of 40 mm with a 70% probability of detecting 0.5 mm diameter flaws. Radiography of the blade using the optimal orientation defined by SMART DR resulted in 0.5-mm diameter pores being detected and indicated good agreement between SMART DR’s predictions and the physical results. Originality/value This paper addresses the need for non-destructive inspection techniques specifically developed for AM components.
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Research context

OpenAlex topics: Additive Manufacturing Materials and Processes · Advanced X-ray and CT Imaging · Additive Manufacturing and 3D Printing Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Pennsylvania State University, University Park Department of Mechanical and Nuclear Engineering, , Pennsylvania,

Pennsylvania State University Center for Innovative Materials Processing Through Direct Digital Deposition, , State College, Pennsylvania,

Pennsylvania State University Department of Industrial and Manufacturing Engineering, , Malvern, Pennsylvania,

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