Optimising process conditions for multiple quality criteria in micro-injection moulding

This paper presents a statistical technique to optimise process conditions for multiple quality criteria in micro-injection moulding. A sample hierarchical component with micro-features was replicated where it was required to improve the process conditions for both complete mould filling and variability in mass. A design-of-experiments approach was used to investigate the effect of five processing parameters on both criteria. It was found that holding pressure, melt temperature and injection velocity were statistically significant for part mass, whereas injection velocity alone was significant for mass variation. Desirability functions were used to predict processing conditions that improved both requirements within pre-set conditions. The technique was validated by experiment and it was shown to be applicable for process parameters for multiple criteria.