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Computer-aided cost estimation of manufacturing operations

机译:生产过程的计算机辅助成本估算

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摘要

Current methods for estimating the cost and time are based on decomposing the product into elements, followed by cost estimation of each element and summing of the other costs. As element, we can consider a product component, a manufacturing process component or an activity component. To estimate the cost for each element, its features that are closely related to cost or time are used. With few exceptions, the estimation methods lead to estimation without a mathematic model describing the relation between cost or time and the element's features. Moreover, these methods have a slight adaptation capacity to different specific situations because the information that is provided in order to make estimations is general and does not adapt to a specific case.Therefore, in this paper, the cost and time will be estimated by a set of appropriate techniques which are based on, neural modeling and k-nearest neighbor regression. Each of these techniques cover a range of specific cases.
机译:当前估算成本和时间的方法是基于将产品分解为要素,然后是每个要素的成本估算和其他成本的总和。作为元素,我们可以考虑产品组件,制造过程组件或活动组件。为了估算每个元素的成本,使用了与成本或时间紧密相关的功能。除了极少数例外,估算方法无需使用描述成本或时间与要素特征之间关系的数学模型即可进行估算。此外,这些方法对不同的特定情况具有轻微的适应能力,因为为进行估计而提供的信息是通用的,并不适合特定的情况。因此,在本文中,成本和时间将由基于神经建模和k近邻回归的一组适当技术。这些技术中的每一种都涵盖了一系列特定情况。

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