The aim of this study is to investigate the effect of different carbon black structures towards heat build-up measurements and its dynamic properties such as tangent delta, loss modulus and storage modulus on the industrial rubber compounds containing Natural Rubber (NR) and Styrene Butadiene Rubber (SBR). Different carbon black structures were used and characterised with respect to their rheological and physical properties. Heat Build-up test is a testing procedure which is used to measure the rate of heat generated by the rubber vulcanisates when subjected to rapidly oscillating compressive stresses or strain under controlled conditions. It was found that NR compound containing low and high carbon black structures; N375 and N339 produced lower heat generation compared to NR/SBR blends that filled with the same type of carbon black fillers. It shows that NR with low and high carbon black structures exhibits low heat build-up (surface and intrinsic) with a balance of good traction and low rolling resistance for application in tyre.

Nowadays, manufacturing industry is growing rapidly in any country over the world. Plastic industry is the one of the manufacturing industry that has high demand among consumers. Polypropylene is popular due to its characteristics such as recycle, low cost, chemical resistance, excellent impact strength, food grade availability and so on. The plastic product is normally produced by using an injection molding machine. The quality of the product depends on the injection molding parameters during the processing. Thus, the optimization of the injection molding parameters on processing polypropylene by using design of experiment is the main objective of the study. The best value of injection molding parameters such as melting temperature, injection pressure, injection speed, cooling time, holding time and holding pressure have been obtained and optimized using Taguchi method. From the results obtained, the most significant injection molding parameter on the shrinkage of polypropylene is holding time. The result has been supported by analysis of variance (ANOVA). The optimization of injection molding parameters contributes to the plastic processing such as increasing productivity as well as maintaining the dimension and quality performance of the product.