Dynamic Production Planning using Bayesian Network for Management Operation Skills

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Given the poor state of the economies all over the world, almost every manufacturing site has been supported by a lot of part-time, temporary, or mid-career personnel. And expert managers of front-line workers must design more complex production planning that take into consideration the workers' skills. Therefore, the purpose of our study is to develop a model with a Bayesian network using the operation histories of expert managers, and to verify some factors that would make it easier for nonexperts to assign human resources. First, the operation histories are collected. Next, some differences of production planning procedures for expert managers and nonexperts are discussed by dividing into the purposes of either minimizing makespan or workload. Finally, the effectiveness of the expert managers' operations is verified by constructing a Bayesian network model based on the operation records, and is this discussed by way of probabilistic inference.