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The Optimization of Injection Molding Processes Using Design of Experiments

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The Optimization of Injection Molding Processes Using Design of Experiments

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The number of characterization experiments needed to develop reliable model-based process and quality control is a serious impediment to implementation in plastics manufacturing. This note shows how the effective use of Design of Experiments can facilitate the development of models through the use of robust approaches such as multivariate analyses. Principal Components Analysis and Projection to Latent Structure methods can employ data from oversaturated DOEs to effectively predict process faults and to characterize the variational effect of many process factors simultaneously. While such DOEs are inadequate for effective multivariate regression analysis, PCA models provide reasonable fidelity to setup the process and evaluate its robustness. The case study for plastics injection molding in this report shows how neglecting the interaction affects results in poor identification of the process boundaries and gross over estimations of the process robustness.

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