Assembly Time Estimation: Assembly Mate Based Structural Complexity Metric Predictive Modeling

作者：Owen**y Joseph E^*; Summers Joshua D

来源：Journal of Computing and Information Science in Engineering, 2014, 14(1): 011004.

DOI：10.1115/1.4025808

• design for assembly
• DFA
• assembly time
• complexity
• artificial neural networks

This paper presents an automated tool for estimating assembly times of products based on a three step process: connectivity graph generation from assembly mate information, structural complexity metric analysis of the graph, and application of the complexity metric vector to predictive artificial neural network models. The tool has been evaluated against different training set cases, suggesting that partially defined assembly models and training product variety are critical characteristics. Moreover, the tool is shown to be robust and insensitive to different modeling engineers. The tool has been implemented in a commercial CAD system and shown to yield results of within +/- 25% of predicted values. Additional extensions and experiments are recommended to improve the tool.

• 出版日期2014-3