This paper presents a new method to describe, analyse and estimate production system performances. Work-in-process (units), lead time (number of time units spent in the production system for each unit) and throughput (number of produced units per time unit) are basic performance measures, also used in this article. It is essential for industry to know about relations between system parameters and system performances in existing systems, and in not yet implemented system alternatives. Different performances are achieved by adjusting system parameters. Trade-offs between system parameters and its different performances are necessary to stay efficient and competitive in today's market. Queuing theory and simulation can help the decision makers to estimate system performances of existing and not yet implemented systems. When the complexity increases queuing theory becomes cumbersome, very difficult and eventually impossible to use. A single simulation presents limited information. Multiple simulations are necessary to ensure that the best alternative is chosen. A high number of simulations demand a lot of computer time and resources. Reduction of runs is desirable even with cheaper computer equipment. Currently, traditional two-dimensional charts are the only tools to present and analyse system performances. This article presents a new surrogate model for easier estimation and presentation of system performances, their internal relations, and relations to the system parameters. With the new surrogate model, system performances based on simulations are presented as positions in a three-dimensional environment. Parametric curves and surfaces of Bezier type are generated and adapted to these positions. System performances of other system alternatives can then be estimated without explicit simulation. The number of simulation calculations can thereby be moderated. The method is illustrated with a small production line system
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