TITLE:
A Monte Carlo Based Robustness Optimization Method in New Product Design Process: A Case Study
AUTHORS:
Jianguo Che, Jing Wang, Kai Li
KEYWORDS:
Monte Carlo Simulation, Robustness Optimization, New Product Design, Process Improvement
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.4 No.7,
July
24,
2014
ABSTRACT: Monte Carlo
method can analyze, solve and optimize many mathematical or physical problems through
generating a large number of statistical random samples to simulating stochastic
events. It also can be used to remarkably improve design quality of new product.
In new product design process, setting distribution characteristics of the design
variables is vital to product quality and production robustness. Firstly, response
surface model between output characteristics and design variables in new product
design is proposed, and the distribution characteristics of design variables and
response output are analyzed; then position error model of response output and standard
value and allowed error maximum is presented; and then the differences of position
error model and allowed error maximum are counted, and reliability ratio is built
and calculated, and design robustness of the new product is increased by adjusting
the precision value of random design variables in Monte Carlo experiments. Finally,
a case is brought forward to verify the validity of the method.