Statistical Design of Experiment (SDE): A part of virtual manufacturing

Abstract

Of late, much has been discussed on virtual manufacturing. Essentially, virtual manufacturing comprises of the development of prototypes using computer simulation. In this paper, it is proposed that Statistical Design of Experiments (SDE) is, in actual fact, a technique that gives rise to effects that are similar to that of virtual manufacturing. Instead of running many combinations of parameters in real life, SDE enables only a few combinations to be run before optimum process set-up can be determined. As a result, the time taken to determine optimum process set-up is greatly reduced. This also allows experimenters to get much more and much better data per experimental run. Furthermore, SDE hails as remedy for the competitive challenges that modern manufacturing is encountering through rising quality standards, shortened product life cycle, and greater demand for product variety. Possession of new flexible technologies such as virtual manufacturing would result in a strategic response to competitive pressure. The success of the virtual manufacturing is tied to the ability to response rapidly to time–based market opportunities. However, SDE provides a feasible and useful tool for the companies to speed up their product development and optimization of manufacturing process with a small number of cost effective set of experiments. Set of experiments holds great potentials to identify factors and levels that have the most and least impact on manufacturing system. It is often carried out by virtual manufacturing system.