TY - JFULL AU - Myungraee Cha and Jun Seok Kim and Seung Hwan Park and Jun-Geol Baek PY - 2012/1/ TI - Nonparametric Control Chart Using Density Weighted Support Vector Data Description T2 - International Journal of Industrial and Manufacturing Engineering SP - 2759 EP - 2764 VL - 6 SN - 1307-6892 UR - https://publications.waset.org/pdf/8229 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 72, 2012 N2 - In manufacturing industries, development of measurement leads to increase the number of monitoring variables and eventually the importance of multivariate control comes to the fore. Statistical process control (SPC) is one of the most widely used as multivariate control chart. Nevertheless, SPC is restricted to apply in processes because its assumption of data as following specific distribution. Unfortunately, process data are composed by the mixture of several processes and it is hard to estimate as one certain distribution. To alternative conventional SPC, therefore, nonparametric control chart come into the picture because of the strength of nonparametric control chart, the absence of parameter estimation. SVDD based control chart is one of the nonparametric control charts having the advantage of flexible control boundary. However,basic concept of SVDD has been an oversight to the important of data characteristic, density distribution. Therefore, we proposed DW-SVDD (Density Weighted SVDD) to cover up the weakness of conventional SVDD. DW-SVDD makes a new attempt to consider dense of data as introducing the notion of density Weight. We extend as control chart using new proposed SVDD and a simulation study of various distributional data is conducted to demonstrate the improvement of performance. ER -