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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Prediction of the life cycle cost using statistical and artificial neural network methods in conceptual product design
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Prediction of the life cycle cost using statistical and artificial neural network methods in conceptual product design

机译：在概念产品设计中使用统计和人工神经网络方法预测生命周期成本

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摘要

During the early design stages, over 70% of the total life cycle cost (LCC) of a product is committed and there may be competing concepts with dramatic differences. Additionally, both the lack of detailed information, and the overhead in developing parametric LCC models for a range of concepts make the application of traditional LCC models impractical. This paper describes the development of predictive models for the product LCC during conceptual design. An artificial neural network (ANN) model to predict the product LCC is developed and compared with a conventional statistical model-a regression model. The results show that the ANN model outperforms the traditional regression model used for predicting the product LCC.
机译：在设计的早期阶段，产品的总生命周期成本（LCC）超过70％已投入使用，并且可能会有竞争性概念存在巨大差异。此外，由于缺乏详细的信息，以及为一系列概念开发参数化LCC模型的开销，使得传统LCC模型的应用不切实际。本文介绍了概念设计期间产品LCC的预测模型的开发。开发了用于预测产品LCC的人工神经网络（ANN）模型，并将其与常规统计模型-回归模型进行了比较。结果表明，ANN模型优于用于预测产品LCC的传统回归模型。

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