Relational-database model for improving quality assurance and process control in a composite manufacturing environment

Jeffery D. Gentry

doi:10.1117/12.385497

13 May 2000 Relational-database model for improving quality assurance and process control in a composite manufacturing environment

Jeffery D. Gentry

Author Affiliations +

Proceedings Volume 3993, Nondestructive Evaluation of Aging Materials and Composites IV; (2000) https://doi.org/10.1117/12.385497
Event: SPIE's 5th Annual International Symposium on Nondestructive Evaluation and Health Monitoring of Aging Infrastructure, 2000, Newport Beach, CA, United States

Abstract

A relational database is a powerful tool for collecting and analyzing the vast amounts of inner-related data associated with the manufacture of composite materials. A relational database contains many individual database tables that store data that are related in some fashion. Manufacturing process variables as well as quality assurance measurements can be collected and stored in database tables indexed according to lot numbers, part type or individual serial numbers. Relationships between manufacturing process and product quality can then be correlated over a wide range of product types and process variations. This paper presents details on how relational databases are used to collect, store, and analyze process variables and quality assurance data associated with the manufacture of advanced composite materials. Important considerations are covered including how the various types of data are organized and how relationships between the data are defined. Employing relational database techniques to establish correlative relationships between process variables and quality assurance measurements is then explored. Finally, the benefits of database techniques such as data warehousing, data mining and web based client/server architectures are discussed in the context of composite material manufacturing.

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Jeffery D. Gentry "Relational-database model for improving quality assurance and process control in a composite manufacturing environment", Proc. SPIE 3993, Nondestructive Evaluation of Aging Materials and Composites IV, (13 May 2000); https://doi.org/10.1117/12.385497

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KEYWORDS

Databases

Composites

Manufacturing

Process modeling

Data mining

Data modeling

Quality measurement

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