标题：Age hardening process modeling and optimization of aluminum alloy A356/Cow horn particulate composite for brake drum application using RSM, ANN and simulated annealing
摘要：Most conventional ceramic based aluminum metal matrix composites (MMCs) are either heavy, costly or
combination of both. In order to reduce cost and weight, while at the same time maintaining quality, cow
horn particles (CHp) was used with aluminum alloy A356 to produce MMC for brake drum application
and other engineering uses. The aim of this research is to model the age hardening process of the
produced composite using response surface methodology (RSM) and artificial neural network (ANN), and
to use the developed ANN as fitness function for a simulated annealing optimization algorithm (SA-NN
system) for optimization of age hardening process parameters. The results show that ANN modeled the
age hardening data excellently and better than RSM with a correlation coefficient of experimental
response with ANN predictions being 0.9921 as against 0.9583 for the RSM. The SA-NN system optimized
process parameters were in very close agreement with the experimental values with the maximum
relative error of 1.2%, minimum of 0.35% and average of 0.71%.
关键词：Artificial neural network ; Response surface methodology ; Simulated annealing ; Age hardening ; Metal matrix composite
