CAPABILITIES IN SOFTWARE SYSTEMS for METAL ADDITIVE MANUFACTURING – A REVIEW
Shaw C. Feng, Paul Witherell, Albert T. Jones, Tesfaye Moges, Hyunseop Park, Mostafa Yakout, Hyunwoong Ko
Additive manufacturing (AM) is rapidly transitioning to an accepted production technology. This transition has led to increasing demands on data analysis and software tools. Advances in data acquisition and analysis are being propelled by an increase in new types of in-situ sensors and ex-situ measurement devices. Measurements taken with these sensors and devices rapidly increasing the volume, variety, and value of AM data but decreasing the veracity of that data simultaneously. The number of new, data-driven software tools capable of analyzing, modeling, simulating, integrating, and managing that data is also increasing; however, the capabilities and accessibility of these tools vary greatly. Issues associated with these software tools are impacting the ability to manage and control AM processes and qualify the resulting parts. This paper investigates and summarizes the available software tools and their capabilities. Findings are then used to help derive a set of functional requirements for tools that are mapped to AM lifecycle activities. The activities include product design, design analysis, process planning, process monitoring, process modeling, process simulation, and production management. AM users can benefit from tools implementing these functional requirements implemented by (1) shortening the lead time of developing these capabilities, (2) adopting emerging, state-of-the-art, AM data and data analytics methods, and (3) enhancing the previously mentioned AM-product-lifecycle activities.
ASME Journal of Computing and Information Science in Engineering
, Witherell, P.
, Jones, A.
, Moges, T.
, Park, H.
, Yakout, M.
and Ko, H.
CAPABILITIES IN SOFTWARE SYSTEMS for METAL ADDITIVE MANUFACTURING – A REVIEW, ASME Journal of Computing and Information Science in Engineering, [online], https://doi.org/10.1115/1.4054933, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933378
(Accessed September 25, 2023)