Investigation into Adaptive Control of a Slip-Cast, Reaction-Bonded Silicon-Nitride Process via Adaptive Learning Network Modeling
Final technical rept. 31 Jan-30 Sep 1979
ADAPTRONICS INC MCLEAN VA
Pagination or Media Count:
A program was conducted to model the modulus of rupture MOR strength using Adaptive Learning Networks ALNs for aircraft engine components produced by a slip-cast, reaction-bonded, silicon-nitride production process. The primary objectives of the work were to identify key process variables and to predict optimum values for those variables as a guide for further experimentation. Nonlinear models have been synthesized that predict MOR with an average error of about 4 ksi over a range from 18.6 to 47.8. The manufacturing and analysis work done to date has demonstrated the feasibility of modeling the slip-cast RBSN process with the Adaptive Learning Network methodology and is viewed as the first iteration in the optimization procedure which is ultimately aimed at finding those manufacturing conditions which will produce the strongest, most consistent material strengths.
- Industrial Chemistry and Chemical Processing
- Manufacturing and Industrial Engineering and Control of Production Systems