Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

TOWARDS KNOWLEDGE MANAGEMENT FOR SMART MANUFACTURING

Published

Author(s)

Shaw C. Feng, William Z. Bernstein, Thomas D. Hedberg Jr., Allison Barnard Feeney

Abstract

The need for capturing knowledge in the digital form in design, process planning, production, and inspection has increasingly become an issue in manufacturing industries as the variety and complexity of product lifecycle applications increase. Both knowledge and data need to be well managed for quality assurance, lifecycle-impact assessment, and design improvement. Some technical barriers exist today that inhibit industry from fully utilizing design, planning, processing, and inspection knowledge. The primary barrier is a lack of a well-accepted mechanism that enables users to integrate data and knowledge. This paper prescribes knowledge management to address a lack of mechanism for integrating, sharing, and updating domain-specific knowledge in smart manufacturing. Aspects of the knowledge constructs include conceptual design, detail design, process planning, material property, production, and inspection. The main contribution of this paper is to provide a view on what knowledge that manufacturing organizations access, update, and archive in the context of smart manufacturing. The case study in this paper provides some example knowledge objects to enable smart manufacturing.
Citation
ASME Journal of Computing and Information Science in Engineering
Volume
17
Issue
3

Keywords

Framework, Knowledge Engineering, Knowledge Management, Smart Manufacturing.

Citation

Feng, S. , Bernstein, W. , Hedberg, T. and Barnard, A. (2017), TOWARDS KNOWLEDGE MANAGEMENT FOR SMART MANUFACTURING, ASME Journal of Computing and Information Science in Engineering, [online], https://doi.org/10.1115/1.4037178 (Accessed December 10, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created July 3, 2017, Updated September 30, 2020