Abstract In the design of expert systems, management of uncertainty is related to a computational analysis of uncertainty from the premises to the conclusion. Although several ad hoc models have been developed to deal with vagueness, there has been a strong need for a globally applicable method of dealing with vagueness in expert systems. In this paper we propose an inference mechanism in a General Purpose Fuzzy Expert System (GPFES) as a knowledge engineering tool which is an attempt to model uncertainty in the general domain of expert systems. We use a new reasoning method utilizing the equivalence operator instead of the implication operator in modus ponens, in which we demonstrate a fuzzy-logic-based computational framework using the concept of coimplication in the inference process. Through this concept of coimplication a knowledge representation scheme has been developed.