The main focus of the research presented in this paper is to propose new methods for filtering and cleaning large-scale production log data by applying statistical learning models. Successful application of the methods in consideration of a production optimization and a simulation-based prediction framework for decision support is presented through an industrial case study. Key parameters analysed in the computational experiments are fluctuating reject rates that make capacity estimations on a

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... hift basis difficult to cope with. The most relevant features of simulation-based workload estimation are extracted from the products' final test log, which process has the greatest impact on the variance of workload parameters.