A new neural network-based control scheme for fault detection and fault diagnosis in fuzzy multivariate multinomial data Online publication date: Thu, 28-May-2015
by Mohammad Reza Maleki; Seyed Meysam Mousavi; Amirhossein Amiri
International Journal of Applied Decision Sciences (IJADS), Vol. 8, No. 2, 2015
Abstract: In some multivariate statistical control applications, the data of the process cannot be precise and defined linguistically in practice. Using multivariate control charts in such situations with non-precise data leads to misleading results. In this paper, a new neural network-based monitoring scheme is presented by considering fuzzy multivariate multinomial data. The proposed approach is also able to identify the attribute(s) that cause an out-of-control signal. An application example is provided to evaluate the performance of the proposed approach in detecting different shifts as well as diagnosing the out-of-control attribute quality characteristic(s). The results of applying the proposed approach in both fault detection and the fault diagnosis are satisfactory.
Online publication date: Thu, 28-May-2015
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