The main application of fuzzy logic in manufacturing has been through type-1 fuzzy sets leaving type-2 fuzzy sets behind. It is felt that type-2 fuzzy sets have the potential of being exploited on a similar scale to type-1 fuzzy sets, because of the additional advantages of containing more information about uncertainty.

The essence of type-2 is in capturing uncertainty in rule-bases by making the degrees of membership to fuzzy sets, fuzzy themselves. Type-2 fuzzy sets are used when (1) linguistic labels of fuzzy sets are uncertain, (2) there is more then one expert, (3) input data into the fuzzy model is uncertain, and (4) training data is uncertain for adaptive modelling. In this research (1) and (2) lead to the use of type-2 fuzzy sets for evaluating a New Product Introduction process. In particular the New Product Introduction Process is explored and documented in a high technology goods manufacturer. The work uses soft systems methodology, cause and effect diagrams, and process maps to document the use of and sharing of information and also to identify the causes of extended time to market.

Initially qualitative data is used to capture model structure by identifying linguistic variables and relationships between them. It is found that the variables can be arranged in a hierarchy to effectively reduce the potential number of rules. A questionnaire is prepared in order to capture further data to identify fuzzy set parameters and lead to type-2 fuzzy sets.  The remainder of the paper finds some initial results and further illuminates the methodology of using type-2 fuzzy sets.