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A model driven development approach based on a reference model for predicting disruptive events in a supply process

机译:基于参考模型的模型驱动开发方法,用于预测供应过程中的破坏性事件

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Due to the impossibility of predicting with certainty the occurrence of disruptive events, buffers defined to obtain a robust schedule could not absorb all the changes. Then, local modifications of the schedule are usually performed to avoid a new planning task. For this task, obtaining disruptive event information in advance can help to make better decisions. As a result, ability to predict disruptive events that affect the execution of the supply process an order represents is required. With the objective of satisfying this requirement, this work proposes a model driven development approach based on a reference model to automate the generation of the monitoring model of a supply process able to anticipate the occurrence of a disruptive event by monitoring variables that can explain it. The approach proposes both a reference model to represent the monitoring model independently of the implementation platform, and a specific model to represent the monitoring model with the particular language of the implementation platform. An engine based on transformation rules allows automating the generation of a platform dependent monitoring model from an instance of a platform independent metamodel. The monitoring component of a SCEM system has been developed, which implements the transformation engine as a Bayesian Network model, and uses an appropriate tool to execute it. For an empirical validation of the model three case studies are presented.
机译:由于不可能确定性地预测破坏性事件的发生,因此为获得可靠的调度而定义的缓冲区无法吸收所有更改。然后,通常对进度表进行本地修改以避免新的计划任务。对于此任务,提前获取破坏性事件信息可以帮助做出更好的决策。结果,需要能够预测影响订单所代表的供应过程执行的破坏性事件的能力。为了满足这一要求,这项工作提出了一种基于参考模型的模型驱动开发方法,该方法可以自动生成供应过程的监视模型,该监视过程可以通过监视可以解释破坏性事件的变量来预测破坏性事件的发生。该方法既提出了一个参考模型来代表独立于实现平台的监视模型,又提出了一个特定模型来代表具有实现平台的特定语言的监视模型。基于转换规则的引擎允许从独立于平台的元模型的实例自动生成依赖于平台的监视模型。已经开发了SCEM系统的监视组件,该组件将转换引擎实现为贝叶斯网络模型,并使用适当的工具来执行它。为了对模型进行实证验证,提出了三个案例研究。

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