Multi response optimization of injection moulding process parameters of polystyrene and polypropylene to minimize surface roughness and shrinkage’s using integrated approach of S/N ratio and composite desirability function

The present study is intended to optimize and develop a prediction model for horizontal injection moulding process parameters. The processing materials are polystyrene (PS) and polypropylene (PP), while the final products are cups. The mould material used is aluminum alloy 6061-T651. The process parameters investigated are injection temperature, injection pressure, injection speed and mould temperature while the response variables are surface roughness, shrinkage inflow and cross-flow directions. Taguchi orthogonal array L9 is designed for experimental runs, while the levels are defined based on screening experiments. For optimization of process parameters, an integrated approach of signal to noise (S/N) ratio and composite desirability function is applied. The results show that injection temperature has a significant effect on surface roughness, shrinkage inflow and cross-flow directions for both polystyrene and polypropylene. Injection pressure has a significant effect on surface roughness and shrinkage in parallel flow direction for PS, while for polypropylene PP it has a significant effect on surface roughness and shrinkage in cross-flow direction. The optimal process parameters identified for PS are injection temperature at 533.15 K, injection pressure at 60 MPa, injection speed at 80 mm/s and mould temperature at 313.15 K. While for PP the optimal process parameters are injection temperature at 513.15 K, injection pressure at 60 MPa, injection speed at 70 MPa, mould temperature at 313.15 K. The novelty of this paper lies by optimizing injection moulding process parameters to minimize surface roughness and shrinkages using proposed integrated approach for the said mould.