Mostly the semiconductor industry is using Yield of wafers for the quality management. However, Yield can not show what kind of the failure patterns because it is indicated the rate of Good or Bad chips only. In particular, wafer bin maps(WBM) that present specific failure patterns provide crucial information which is the process problems in semiconductor manufacturing. This paper proposes the map pattern index(MPI) for indicating quality level with the feature of map patterns effectively. The zonal analysis and the principal component analysis are applied to classification of map patterns and to compute the MPI. The zonal analysis is that all chips on a wafer are separated to be defined zones and calculate bad rates of separated zones, and then the principal component analysis is used to get the features values of the map patterns. The MPI is able to show the trend of the feature of the map patterns better than yield effectively. And it can be applied to analysis systems easily such as Automatic process controllers, WBM data analysis systems, Real-time monitoring systems of Testers or Equipments, Process engineering simulators and so on.