click on star to go back to Joseph Sarkis' HomepageProduction process control deals with monitoring and improving processes over time by identifying, investigating, and eliminating problems that are responsible for inefficiencies in manufacturing operations. Although statistical process control tools such as control charts are currently available for process monitoring, these methods have certain limitations in their applicability. One such limitation with traditional control charts is that they typically monitor only one 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 the performance variables. The primary advantage of this control chart is that a single integrated measure is to be monitored. It also allows for the integration of decision-maker's input when the variables being monitored have unequal importance.
click on star to go back to Joseph Sarkis' Homepage