As customer awareness of product sound grows, the need exists to ensure that product sound quality is maintained in the manufacturing process. To this end in-process controls that employ a variety of traditional acoustical and alternate sound quality metrics are utilized, usually partly or wholly housed in a test enclosure. Often times these test cells are required to attenuate the background noise in the manufacturing facility so that the device under test can be accurately assessed. While design guidelines exist the mere size and cost of such booths make an iterative build and test approach costly in terms of materials as well as engineering and testing time. In order to expedite the design process and minimize the number of confirmation prototypes, SEA can be utilized to predict the transmission loss based upon material selection and booth construction techniques. Additionally, SEA can be used to identify those components of the booth that are likely to be problematic from either a transmission loss or a leakage perspective.
Two approaches are possible in terms of booth design and execution. The first of these is the ‘brute force’ approach whereby a target transmission loss is achieved almost without regard to cost or complexity. However, while this approach is effective from a noise control perspective, it is often overkill for the environment into which the booth must be placed. The second approach is one of optimization with some measure of conservatism in its design. That is to say, booths are designed to offer adequate transmission loss to ensure that the device under test is not affected by external environmental factors. From an economic standpoint this is the more rational choice when one considers the cost sensitive nature of the automotive industry.
In order to determine the required transmission loss prototypes are tested in laboratory conditions to determine their overall noise and sound quality performance. These data are typically utilized with data from the manufacturing facility which describe the ambient noise levels. This paper considers the entire process whereby laboratory, plant, and modeling data are utilized to optimize the booth design, thereby ensuring that reliable process control may be generated by the systems as employed in the manufacturing facility.