This master's thesis investigates the impact of unbalanced variability on lead time using a simulation-based optimization approach. Based on the hypothesis, variation of service time has a strong effect on lead time. It has also been hypothesized that placing the high variable station, in terms of CVp, at the end of the line will increase lead time. To evaluate these hypotheses, Fact Analyzer Simulation Software version beta7 was used to simulate and optimize two different models. First, the effect of an imbalanced line in terms of service time on total lead time in a simple production line hypothetical model was investigated. In the second part of this master thesis, a real health care model was adopted from Frandsen and Engqvist’s project at Skaraborg Hospital (SkaS). By optimizing this model, using NSGA_II Algorithms, the effect of variance and mean of service time on lead time variance and mean were evaluated and compared. As a result of both the hypothetical and health care models, the total lead time will not decrease by reducing the variance of service time, indicating that the hypothesis should be rejected.    Keywords: service time, CVp, lead time, imbalanced, variability, mean lead time, variance lead time, waiting time, variability