{"title":"Generalised and automated method for surface analysis of roughness and subsurface porosity using micro-computed tomography","authors":"Lukas Englert, Volker Schulze, Stefan Dietrich","doi":"10.1016/j.ndteint.2024.103166","DOIUrl":null,"url":null,"abstract":"<div><p>As additive manufacturing enables the production of intricate, high-value parts with functional integration, inspection is gaining importance to ensure safety for use. Since the surface quality of laser beam powder bed fusion parts has proven to be inherently inhomogeneous, the measured values are dependent on the measurement spot, making surface quality difficult to characterise using conventional methods. Combined with the fact that the complex shape of the parts potentially complicates measurements further, a new surface characterisation method is required to adequately capture the quality of additively manufactured parts on the entire surface. In this work, a novel method is proposed that is both capable of meeting the above requirements and additionally allows the correlation of the results with the process data and the evaluation of the near-surface porosity. At the same time, the local quality deviations can be visualised and roughness hotspots found and correlated with the process.</p></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"146 ","pages":"Article 103166"},"PeriodicalIF":4.1000,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0963869524001312/pdfft?md5=5c81d8d3bd1e256c8e194a712eb5f4fc&pid=1-s2.0-S0963869524001312-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ndt & E International","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0963869524001312","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
引用次数: 0
Abstract
As additive manufacturing enables the production of intricate, high-value parts with functional integration, inspection is gaining importance to ensure safety for use. Since the surface quality of laser beam powder bed fusion parts has proven to be inherently inhomogeneous, the measured values are dependent on the measurement spot, making surface quality difficult to characterise using conventional methods. Combined with the fact that the complex shape of the parts potentially complicates measurements further, a new surface characterisation method is required to adequately capture the quality of additively manufactured parts on the entire surface. In this work, a novel method is proposed that is both capable of meeting the above requirements and additionally allows the correlation of the results with the process data and the evaluation of the near-surface porosity. At the same time, the local quality deviations can be visualised and roughness hotspots found and correlated with the process.
期刊介绍:
NDT&E international publishes peer-reviewed results of original research and development in all categories of the fields of nondestructive testing and evaluation including ultrasonics, electromagnetics, radiography, optical and thermal methods. In addition to traditional NDE topics, the emerging technology area of inspection of civil structures and materials is also emphasized. The journal publishes original papers on research and development of new inspection techniques and methods, as well as on novel and innovative applications of established methods. Papers on NDE sensors and their applications both for inspection and process control, as well as papers describing novel NDE systems for structural health monitoring and their performance in industrial settings are also considered. Other regular features include international news, new equipment and a calendar of forthcoming worldwide meetings. This journal is listed in Current Contents.