Accuracy and Precision Analysis of the Graph Complexity Connectivity Method

被引:13
|
作者
Sridhar, Sudarshan [1 ]
Fazelpour, Mohammad [1 ]
Gill, Amaninder S. [1 ]
Summers, Joshua D. [1 ]
机构
[1] Clemson Univ, Dept Mech Engn, Clemson, SC 29634 USA
关键词
Assembly models; Function structures; Assembly time; Market value; Artificial neural network; ENGINEERING DESIGN COMPLEXITY;
D O I
10.1016/j.procir.2016.02.029
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
For a given electro-mechanical product, represented using assembly models and function structures, the assembly time (AT) and market value (MV) are influenced by complexity of the product. Given the AT and MV of a set of known products, complexity values can he used to predicted AT and MV for a set of unknown products using an Artificial Neural Network. This paper presents a precision analysis of four prediction models that are a combination of the aforementioned design representations and AT and MV. A sensitivity analysis of the complexity metrics was done using Multiple Linear Regression, and a set of significant metrics was identified. Lastly, a comparison of accuracy and precision for the four prediction models obtained using this set of sensitivity analysis is presented. (C) 2016 The Authors. Published by Elsevier B.V.
引用
收藏
页码:163 / 168
页数:6
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