Production of components through microcellular processing

Abstract

The manufacture of light weight plastic components is gaining relevance within thepolymer industry as component weight savings of up to 15% can be achieved. FoamInjection Moulding (FIM) is one technology solution that delivers weight savingthrough the introduction of microcellular structures within components. FIM differsfrom conventional injection moulding whereby blowing agents are added to thepolymer during processing to create a cellular structure.The first part of this research aims to benchmark Unfilled and Talc-filled CopolymerPolypropylene (PP) samples through low-pressure FIM. The research analyses theprocess response when utilising a chemical blowing agent, a physical blowing agentand a novel hybrid foaming (combination of said chemical and physical foamingagents). The experimental results concluded that Unfilled PP foams produced throughchemical blowing agent exhibited superior mechanical characteristics due to largerskin wall thicknesses. However, the hybrid foaming produced superior microcellularfoams for both PP variations due to calcium carbonate (CaCO3) enhancing thenucleation phase.The next section of research initially varied then subsequently optimised the mainprocessing parameters to determine their effect on Surface Roughness, Young’sModulus and Tensile Strength. The experimental results show that the mechanicalperformance can be improved when processing with higher Mould Temperatures andlonger Holding Times. Also, when utilising the CBA, surface roughness is comparableto conventionally processed components.The final stage of the research investigated the ability of an industry standardsimulation package to accurately predict the process response when processing with avariety of blowing agents. Initial simulations results failed to accurately replicatephysical mouldings which can be attributed to microcellular structure overestimationswithin the simulation. Through an iterative process, simulation settings have beenidentified that provide clear correlations to improve the simulation accuracy of FIM