Potentials of Nonlinear Dynamics Methods to Predict Customer Demands in Production Networks
Potentials of Nonlinear Dynamics Methods to Predict Customer Demands in Production Networks
复制标题
非线性动力学方法在生产网络中预测客户需求的潜力
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Mirko Kück
中科院分区：
文献类型：
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作者：
B. Scholz;Mirko Kück
如今，市场的特点是日益增加的动态性和复杂性。特别是，客户的需求往往非常不稳定。这些情况使需求预测变得复杂，并降低了预测数据的平均准确性。然而，制造企业必须准确预测客户需求，以实现有根据的生产计划和控制。本文研究了生产物流应用场景中的客户需求预测方法。首先，平稳客户需求的预测方法，特别强调非线性动力学方法。随后，一个新的算法来预测间歇性需求。在这两种情况下的需求演变，不同的方法被应用到预测的生产网络的离散事件模拟所产生的需求数据。预测结果进行解释，并就其适用性的不同方法进行评级。研究表明，应用非线性动力学方法可以提高预测精度。
Nowadays, markets are characterized by increasing dynamics and complexity. In particular, customer demands are often highly volatile. These conditions complicate demand forecasting and reduce the average accuracy of forecasting data. Nevertheless, manufacturing companies have to predict customer demands precisely, in order to achieve a well-founded production planning and control. The paper at hand deals with methods to predict customer demands in application scenarios of production logistics. Firstly, forecasting methods for smooth customer demand are described with a particular emphasis on nonlinear dynamics methods. Subsequently, a new algorithm to predict intermittent demand is introduced. In both cases of demand evolution, different methods are applied to predict demand data generated by a discrete-event simulation of a production network. Forecasting results are interpreted and the different methods are rated regarding their applicability. The research displays that an application of nonlinear dynamics methods can lead to improved forecasting accuracy.