A neural information retrieval system
| Autor: | Scott D. G. Smith, R. Escobedo, Thomas P. Caudell |
|---|---|
| Rok vydání: | 1993 |
| Předmět: |
Media management
Artificial neural network Computer science business.industry Mechanical Engineering Reuse Machine learning computer.software_genre Industrial and Manufacturing Engineering Purchasing Computer Science Applications Group technology Control and Systems Engineering Human–computer information retrieval Artificial intelligence Industrial and production engineering business computer Software |
| Zdroj: | The International Journal of Advanced Manufacturing Technology. 8:269-273 |
| ISSN: | 1433-3015 0268-3768 |
| DOI: | 10.1007/bf01748637 |
| Popis: | Group technology is an approach to manufacturing that attempts to enhance production efficiency by grouping similar activities and tasks together. The results of this process are then used in the execution of similar tasks and activities. This concept can be applied to a variety of activities such as design retrieval, purchasing, sales, and process planning [1]. Traditionally, classification and coding has been used to implement group technology. In this paper, however, we discuss a novel approach using neural networks, a technology noted for its powerful pattern-matching capability. Although this approach can be applied to the entire spectrum of group technology applications, we focus on an application to the retrieval and reuse of engineering part designs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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