Contextualizing Manufacturing Data for Lifecycle Decision Making
William Z. Bernstein, Thomas D. Hedberg, Moneer M. Helu, Allison Barnard Feeney
Product Lifecycle Management (PLM) systems manage the flow of data about the product and the processes that are used throughout the product's lifecycle so that the right information is delivered at the right time to the right systems. Manufacturing in the aerospace and other industries provides a rich source of data about the product and processes, but there is a lack of standardized infrastructure to richly represent this data and place it into the appropriate context to generate useful knowledge. Recent advances enable data from manufacturing systems to be captured and contextualized relative to other phases of the product lifecycle, a necessary step toward understanding system behavior and satisfying traceability requirements. Significant challenges remain for integrating information across the lifecycle and enabling efficient and effective decision making. In this paper, we describe a reference implementation that leverages existing data standards such as the Standard for the Exchange of Product Data (STEP), MTConnect, and the Quality Information Framework (QIF) to integrate the information silos that exist across the product lifecycle. This reference implementation is prototyped with a contract manufacturer in the NIST Smart Manufacturing Systems Test Bed. In this implementation, we fuse data from design, planning, manufacturing and inspection and explore how knowledge generated from manufacturing data can be used to support lifecycle decision making in the aerospace industry. We then classify, by lifecycle viewpoint, the types of questions that can be addressed through this implementation.
International Journal of Product Lifecycle Management
, Hedberg, T.
, Helu, M.
and Barnard, A.
Contextualizing Manufacturing Data for Lifecycle Decision Making, International Journal of Product Lifecycle Management, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=922833
(Accessed June 6, 2023)