This paper describes the fundamental framework of an intelligent grinding process advisory system, which has been developed to help process engineers design new grinding processes. The system incorporates both highly complex, nonlinear analytical grinding process models and knowledge-based linguistic rules, and generates unified fuzzy rules by a novel automatic rule generation procedure. Optimal design of the parameters is performed via fuzzy logic inference. Several design principles for constructing the system are discussed as well as the over-all architecture of the system. The implementation of the system shows that the system can lead to the optimal design of a grinding process very effectively even with a large number of process parameters.
All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering
- Artificial Intelligence