Abstract This paper describes a special purpose simulation tool, SCSIM, developed for analysing supply chain (SC) behaviour and performance in the presence of uncertainty. SCSIM treats a SC which includes a raw material inventory, a number of in-process inventories, an end-product inventory and production facilities between them, linked in a series. Main sources of uncertainty inherent in the serial SC and its environment are identified, including customer demand, external supply of raw material and lead times to the facilities. Uncertainties perceived in these SC data are described by imprecise natural language expressions and they are modelled in SCSIM by fuzzy sets. Two types of models are combined in SCSIM: (1) SC fuzzy analytical models to determine the optimal order-up-to levels for all inventories in a fuzzy environment and (2) a SC simulation model to evaluate SC performance achieved over time by applying the order-up-to levels recommended by the fuzzy models. SCSIM can be used for various SCs analyses to gain a better understanding of SC behaviour and performance in the presence of uncertainty and to enhance decision making on operational SC control parameters. The application of SCSIM in analysing and quantifying the effects of changing uncertainty in customer demand is discussed and illustrated by a numerical example.