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Common defects and contributing parameters in powder bed fusion AM process and their classification for online monitoring and control: a review

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Abstract

The powder bed fusion additive manufacturing process enables fabrication of metal parts with complex geometry and elaborate internal features, the simplification of the assembly process, and the reduction of development time; however, its tremendous potential for widespread application in industry is hampered by the lack of consistent quality. This limits its ability as a viable manufacturing process particularly in the aerospace and medical industries where high quality and repeatability are critical. A variety of defects, which may be initiated during powder bed fusion additive manufacturing, compromise the repeatability, precision, and resulting mechanical properties of the final part. One approach that has been more recently proposed to try to control the process by detecting, avoiding, and/or eliminating defects is online monitoring. In order to support the design and implementation of effective monitoring and control strategies, this paper identifies, analyzes, and classifies the common defects and their contributing parameters reported in the literature, and defines the relationship between the two. Next, both defects and contributing parameters are categorized under an umbrella of manufacturing features for monitoring and control purposes. The quintuple set of manufacturing features presented here is meant to be employed for online monitoring and control in order to ultimately achieve a defect-free part. This categorization is established based on three criteria: (1) covering all the defects generated during the process, (2) including the essential contributing parameters for the majority of defects, and (3) the defects need to be detectable by existing monitoring approaches as well as controllable through standard process parameters. Finally, the monitoring of signatures instead of actual defects is presented as an alternative approach to controlling the process “indirectly.”

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  1. Center for Additive Manufacturing Research at IUPUI (CAMRI), Purdue School of Engineering and Technology, Indianapolis, IN, USA

    Ehsan Malekipour & Hazim El-Mounayri

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Malekipour, E., El-Mounayri, H. Common defects and contributing parameters in powder bed fusion AM process and their classification for online monitoring and control: a review. Int J Adv Manuf Technol 95, 527–550 (2018). https://doi.org/10.1007/s00170-017-1172-6

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