This paper proposes an approach to investigate the influencing factors of the brake pad on the disc brake squeal by integrating finite element simulations with statistical regression techniques. Complex eigenvalue analysis (CEA) has been widely used to predict unstable frequencies in brake systems models. The finite element model is correlated with experimental modal test. The 'input-output' relationship between the brake squeal and the brake pad geometry is constructed for possible prediction of the squeal using various geometrical configurations of the disc brake. Influences of the various factors namely; Young's modulus of back plate, back plate thickness, chamfer, distance between two slots, slot width and angle of slot are investigated using design of experiments (DOE) technique. A mathematical prediction model has been developed based on the most influencing factors and the validation simulation experiments proved its adequacy. The predicted results show that brake squeal propensity can be reduced by increasing Young's modulus of the back plate and modifying the shape of friction material by adding chamfer on both sides of friction material and by introducing slot configurations. The combined approach of modeling brake squeal using CEA and DOE is found to be statistically adequate through verification trials. This combined approach will be useful in the design stage of the disc brake.

Optimal setting up of injection molding process variables plays a very important role in controlling the quality of the injection molded products. It is all the most important to control attribute defects like sink marks. Sink marks are basically a "designed in" problem and hence it is to be attended during designs stages. Owing to certain conditions and constraints, sometimes, it is rather ignored during design stages and it is expected to be handled by molders with only instruction to 'do the best'. Handling of numerous processing variables to control defects is a mammoth task that costs time, effort and money. This paper presents a simple and efficient way to study the influence of injection molding variables on sink marks using Taguchi approach. Using the Taguchi approach, optimal parameter settings and the respective sink depth were arrived. The sink depth based on the validation trials was compared with the predicted sink depth and they are found to be in good agreement. The results demonstrate the ability of this approach to predict sink depth for various combination of processing variables with in the design space.

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