Real-time statistical process control of aqueous cleaning systems through in-situ monitoring

Abstract

Traditional off-line part cleanliness analysis is too slow for use as a process control tool. These tests, traditionally performed in a laboratory on a small number of representative part samples, are extremely time-consuming. Parts are already integrated into finished product before contamination data are available. Any problems identified at this point require product recall or rework to correct, inflicting a heavy toll on already thin profit margins. Optimally; contamination problems must be identified in real-time, before suspect parts reach the production floor or are built into finished goods. Liquid in-situ particle monitors (ISPMs), a method used for several years in the semiconductor industry [1], have proven themselves a reliable means of measuring general part cleanliness in real-time. When combined with current state-of-the-art monitoring and control packages, ISPMs provide statistical process control capabilities never before available for parts cleaning. With this type of process control, contaminated parts are identified and removed from manufacture before they impact product yield or reliability.