A Practical Monitoring to Detect the Quality Shifts using EWMA Method  

Oleh:

Chen, Demeter ; Chang, WF

Jenis: Article from Proceeding
Dalam koleksi: 12th ANQ Congress in Singapore, 5-8 Agustus 2014, page 1-7.
Topik: Exponential Weighted Moving Average; Average Run Length; eCOA; Sequence-Disorder Effect; n-Steps-Ahead-Error
Fulltext: PS-2.6-P0397.pdf (472.5KB)

Isi artikel

In this paper, we focus on the small shift detection of raw material incoming control, such as wafer flatness and thickness, etc. Using exponentially-weighted moving average chart (EWMA) charts where possibly smooth out the “sequence-disordered effect”. The EWMA parameter optimizers are proposed to obtain realistic parameters and the average run length, ARL , is served as a performance index of the optimizers. The optimizers to minimize ARL1 and n-Steps-Ahead-Error based on baseline population, and to maximize ARL0 to approach specified upper bound of false alarm rate. The optimal parameters are to make a trade-off between above three conditions. The eCOA data illustrates our proposal and several small shifts that are detected by EMWA do reflect assigned causes in supplier production line. We demonstrate that a well-designed EWMA chart is also complementary to give a perspective of how small changes of the production line with sequence-disordered effects affect the incoming raw material control

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