Production of components through microcellular processing
The manufacture of light weight plastic components is gaining relevance within the polymer industry as component weight savings of up to 15% can be achieved. Foam Injection Moulding (FIM) is one technology solution that delivers weight saving through the introduction of microcellular structures within components. FIM differs from conventional injection moulding whereby blowing agents are added to the polymer during processing to create a cellular structure. The first part of this research aims to benchmark Unfilled and Talc-filled Copolymer Polypropylene (PP) samples through low-pressure FIM. The research analyses the process response when utilising a chemical blowing agent, a physical blowing agent and a novel hybrid foaming (combination of said chemical and physical foaming agents). The experimental results concluded that Unfilled PP foams produced through chemical blowing agent exhibited superior mechanical characteristics due to larger skin wall thicknesses. However, the hybrid foaming produced superior microcellular foams for both PP variations due to calcium carbonate (CaCO3) enhancing the nucleation phase. The next section of research initially varied then subsequently optimised the main processing parameters to determine their effect on Surface Roughness, Young’s Modulus and Tensile Strength. The experimental results show that the mechanical performance can be improved when processing with higher Mould Temperatures and longer Holding Times. Also, when utilising the CBA, surface roughness is comparable to conventionally processed components. The final stage of the research investigated the ability of an industry standard simulation package to accurately predict the process response when processing with a variety of blowing agents. Initial simulations results failed to accurately replicate physical mouldings which can be attributed to microcellular structure overestimations within the simulation. Through an iterative process, simulation settings have been identified that provide clear correlations to improve the simulation accuracy of FIM.