Transactions of Nanjing University of Aeronautics & Astronautics
An Assembly Man-Hour Estimation Model Based on GA-SVM for Multi-specification and Small-Batch Production
- Article
- Figures
- Metrics
- Preview PDF
- Reference
- Related
- Cited by
- Materials
Abstract:
It is necessary to evaluate man-hour （MH） before receiving the order to guide the quotation and forecast the delivery date for a manufacturing contractor. As an important part of assembled MH， it has important practical significance. Aiming at the characteristics of multi-specification and small-batch production， an assembly MH estimation model based on support vector machine （SVM） is proposed. Apart from single component attributes， assembly process， and historical MH data， we also consider the average of shortest path length （ASPL）， which quantifies the complexity of an assembly， as influencing factors of assembly MH. Furthermore， the auto calculating methods of these factors based on 3D models with Creo JLink are proposed. Through the comparison of several algorithms， SVM is chosen as the optimal algorithm for assembly MH modeling. Genetic algorithm （GA） is used to avoid the local solution and accelerate convergence when searching for the optimal parameters of SVM （c and g）. Finally， the proposed GA-SVM model is trained and applied to predict the assembly MH of the bionic leg for the radar device. Experimental results show that GA-SVM has higher prediction accuracy than other methods in this paper and the whole predicting process only takes about 3 min.
Keywords:
Project Supported:
This work was supported in part by the Special Fund of Jiangsu Province for the Transformation of Scientific and Technological Achievements （Nos.BA2018110， BA2021036）， and the Natural Science Foundation of Jiangsu Province （No.BK20211061）. The authors would like to acknowledge the following people for their assistance： Mr. YU Ke， Mr. ZHOU Guoping， Mr. HE Yafeng， all with Changzhou Wujin GUANGYU Embossing Roller Machinery Co.， Ltd.
Clc Number:
TH162
Mobile website
