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 a...

in this research, a new control policy for the acceptance sampling problem is introduced. decision is made based on the number of defectives items in an inspected batch. the objective of the model is to find a constant control level that minimizes the total costs, including the cost of rejecting the batch, the cost of inspection and the cost of defective items. the optimization is performed by ...

In test cost-sensitive decision systems, it is difficulty for us to find an optimal attribute set and construct a quality classifier with limited cost. The minimal test cost-sensitive attribute reduction is proposed to address the former problem. However, it is inevitable to remove some good even better attributes in the minimal test cost-sensitive attribute reduction. As a result, the classifi...

Abstract Various uncertain influencing factors and incomprehensible mechanisms have posed daunting challenges to the management treatment of regional surface water environment quality. The unified measures “one-size-fits-all” approach limit effectiveness. Therefore, considering natural human activities which are major affecting quality, present study proposed a set zoning control schemes for ni...

In a distributed manufacturing shop (DMS), factories of various levels of manufacturing capabilities are equipped with diverse types of machines and tools and are scattered around many geographically different locations. Because of such geographical diversity, the quality control of sub-assemble products (SAP) is of great importance to ensure a high level of production quality. To address the c...