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Using modelling and simulations in enterprises assists decision-making and allows for transparent and effective judgements. Although contemporary enterprise models make integrated and complex process controlling possible, further strategic aspects in attaining optimal processes are conceivable. Instead of optimising individual targets (e.g., resource optimisation, capacity utilisation, etc.), an approach from the point of view of process quality will be presented here. A promising field offers the inclusion of dynamic resources in enterprise planning and controlling.

In a real business process, the parameters for probability distributions are unknown or ambiguous. Therefore, conventional modeling of these systems using deterministic parameters is questionable. Fuzzy simulation enables modeling uncertainties in such systems. The objective of this study is to model and improve concurrently the performance of integrated information, business, and production process of a manufacturing system using fuzzy simulation. Here, performance is defined as customer satisfaction. The superiority of the fuzzy simulation approach over conventional models used in prior studies is discussed. The integrated fuzzy approach in this study enables evaluating customer lead times in six dimensions with uncertainties considerations. Major effects of business process reengineering and information technology are evaluated before the actual implementation. The comparison results indicate that the fuzzy model is closer to the actual system. This is the first study that presents an integrated fuzzy model for improvement of customer satisfaction in integrated information, business, and production processes with ambiguity.

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