Production process control focuses on monitoring and improving processes over time by identifying, investigating, and eliminating problems responsible for inefficiencies in manufacturing operations. Although statistical process control tools such as control charts are available for process monitoring, these methods have certain limitations. One limitation with traditional control charts is that they typically monitor only a single variable. Although multivariate process control techniques allow for simultaneous monitoring of several variables, they require assumptions of independence and multivariate normality of data. It is also difficult to interpret out-of-control signals in a multivariate chart. To overcome these problems, this paper proposes an individual control chart that monitors an integrated performance index generated from a nonparametric method, which effectively considers multiple performance measures and relationships between them. The primary advantages of this control chart are that a single integrated measure can be monitored, does not require assumptions of independence and multivariate normality of data, and allows for the integration of decision-maker's input when the variables being monitored have unequal importance.