Designing of Automotive Vacuum Pumps - Development of Mathematical Model for Critical Parameters and Optimization using Artificial Neural Networks

In this ever-changing field of automotive industry where there is high competition to seek a place in market, it is necessary to design and develop products with a minimum lead time meeting the target specifications. This is normally achieved through product variants specific to customer requirements from the repository of design base created. Design bases are created based on the previous products and by bench marking. Vacuum Pump is an engine driven part identified for this study. The main aim of this study is to create a mathematical model, and use Artificial Neural Networking (ANN) to arrive at a design base. In the process of building the mathematical model, two key design parameters namely profile and performance were identified and model was constructed. Using this mathematical model, proto samples were prepared for a range of vacuum pump capacities and were tested. These test results were used for training the ANN to create the design base for any future design. The NN predicted values had a good correlation with the actual values of tested proto samples. Thus, the design was optimized for greater accuracy, which will serve as a design base for future applications.