Authors:
Xiaoqing Tang
and
Zhehan Chen
Affiliation:
Beihang University, China
Keyword(s):
Process Model, Measurement Plan, Knowledge Presentation, Digital Manufacturing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Foundations of Knowledge Discovery in Databases
;
Information Extraction
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining High-Dimensional Data
;
Mining Text and Semi-Structured Data
;
Symbolic Systems
Abstract:
Digital measurement technology has been widely employed in product manufacturing process. In general, a measuring process is planned based on human knowledge in planning strategies, measuring regulations, de-vices and instruments, measuring operations and historical data. Knowledge-supported measuring planning makes the process formatted, and enables manufacturers to improve product quality and reduce manufacturing cost. Therefore, accumulating, presenting and modeling the measuring data, information and expertise knowledge from engineering sectors, which can provide a foundation for discovering and reusing knowledge of measuring process, are crucial for planning and optimizing a measurement plan. In order to improve measurement plans based on expertise knowledge, a general measurement space (GMS) model of measuring process is proposed. The model makes the attributes in three dimensions to describe and classify multi-source and heterogeneous knowledge in the measuring process. The me
thodology for integrating and expressing measuring process knowledge is then discussed, in order to support the storage, management and analysis of structured knowledge data based on programs. Finally, the GMS’s characteristics matrix is constructed, providing a feasible way to evaluate measurement plans based on measuring process knowledge.
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