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PUBLICATIONS

SELF-IMPROVING ADDITIVE MANUFACTURING KNOWLEDGE MANAGEMENT

Published

Author(s)

Yan Lu, Zhuo Yang, Douglas Eddy, Sundar Krishnamurty

Abstract

The current AM development environment is far from being mature. Both software applications and workflow management tools are very limited due to the lack of knowledge to support engineering decision makings. AM knowledge includes design rules, operation guidance, and predictive models, etc., which play a critical role in the development of AM products, from the selection of a process and material, lattice and support structure design, process parameter optimization to in-situ process control, part qualification and even material development. At the same time, massive AM simulation and experimental data sets are being accumulated, stored, and processed by the AM community. This paper proposes a four-tier framework for self-improving additive manufacturing knowledge management which defines two processes: bottom-up data-driven knowledge engineering and top-down goal-oriented active data generation. The parallel processes are connected by users, therefore form a closed loop, through which AM knowledge can evolve continuously and in an automated way.
Proceedings Title
Proceedings of the ASME 2018 International Design Engineering Technical Conferences &
Computers & Information in Engineering Conference
Conference Dates
August 26-28, 2018
Conference Location
Quebec City, CA
Conference Title
ASME 2018 International Design Engineering Technical Conferences &
Computers & Information in Engineering Conference
Pub Type
Conferences

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Keywords

additive manufacturing, knowledge management
Information retrieval, Artificial intelligence and Additive manufacturing

Citation

Lu, Y. , Yang, Z. , Eddy, D. and Krishnamurty, S. (2018), SELF-IMPROVING ADDITIVE MANUFACTURING KNOWLEDGE MANAGEMENT, Proceedings of the ASME 2018 International Design Engineering Technical Conferences & Computers & Information in Engineering Conference, Quebec City, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=925545 (Accessed April 24, 2024)

Created August 26, 2018, Updated April 13, 2022