This Small Business Innovation Research (SBIR) Phase I project aims to apply advanced signal processing methodologies such as Principal Component Analysis (PCA) to forging processes. This project will address the need of the forging industry with PCA-based control charts for in-line applications. The goal is to demonstrate the ability to detect signatures of faults that are as weak as 1% of the total signal magnitude. The Phase I research will include the evaluation of available data analysis methodologies, such as the PCA. The selected methods will be tested with real forging press data for the fault of colder than-normal die temperature. If successful, the developed control charts will be implemented on a test site to verify the detection performance for 30 days.
The need of advanced process monitoring is well documented by the industry. The Forging Industry Association identified forging process/equipment monitoring and control with advanced sensor systems as one of the 5 needed technical programs by the US forging industry. A success of this proposed project will have an immediate impact to the forging industry, particularly in the time the raw material is at a record high value and the demand for improved productivity is unprecedented. The ATA system, once commercialized, can help the target industry with better equipment efficiency and less scrap. The ATA system, if successfully developed, is expected to reduce the amount of scrap drastically and in turn, improve energy preservation and environmental protection. The potential commercial value associated with this technological development is high. The estimated market size is $15 million the US and $100 million globally.
