Abstract:

In many industrial situations, process stability has to be determined with the help of two or more quality characteristics simultaneously. Many researchers in the past used fuzzy set theory to model linguistic data and construct control charts. In many such charts, the assumption of fuzziness is not retained through all the steps. The current paper considers the case when quality experts subjectively estimate correlated multiple-attribute quality characteristics. These estimates are used to find the aggregate fuzzy values of the samples, using interactive fuzzy addition. Two fuzzy control charts are developed, one based on possibility measure and the other on the necessity measure. The paper proposes a novel approach that uses the concept of the a-level and ?-level set to identify the specific quality characteristic(s) that are responsible for an out-of-control condition of the process.