Applying fuzzy approach to develop transient probability matrix for on-line variable quality monitoring

The characteristic of interest follows a normal distribution and changes of the distribution parameters are described by a k-state Markov chain. Items are produced independently and a single item is examined at every manufactured item similar to an on-line quality procedure to monitor variables of process. In this paper the fuzzy approach has been developed to obtain the transition matrix in vagueness environment. First calculated the mass function of each state and then the possibility of probability state transaction from each state to another state have been achieved. To validate the proposed approach the five learning set data was captured from real case to form the fuzzy transition matrix of 2-state Markov chain.