Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2019 , Vol. 53 >Issue 7: 838 - 843

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2019.07.010

Identification of Product Redesign Modules Based on Neural Network of Sparse Auto-Encoder

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  • 1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; 2. School of Mines, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China

Online published: 2019-08-02

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Abstract

This paper presents a redesign-module identification method based on time-varying product usage data. The method is conducted in three steps：Building a model based on sparse auto-encoder (SAE) neural network using performance feature data from the product health state; Assessing functional performance degradation by using the data during the actual operation; Identifying the redesign module by comparing the difference in functional degradation. Then, a case study of horizontal directional drilling redesign module identification is presented to illustrate feasibility of the proposed method. The result shows the effectiveness of proposed method so that it can identify the weak function modules, while the identified result can provide support for redesign decision-making.

Key words： This paper presents a redesign-module identification method based on time-varying product usage data. The method is conducted in three steps：Building a model based on sparse auto-encoder (SAE) neural network using performance feature data from the product health state; Assessing functional performance degradation by using the data during the actual operation; Identifying the redesign module by comparing the difference in functional degradation. Then, a case study of horizontal directional drilling redesign module identification is presented to illustrate feasibility of the proposed method. The result shows the effectiveness of proposed method so that it can identify the weak function modules, while the identified result can provide support for redesign decision-making.

Cite this article

MA Binbin,MA Hongzhan,CHU Xuening,LI Yupeng . Identification of Product Redesign Modules Based on Neural Network of Sparse Auto-Encoder[J]. Journal of Shanghai Jiaotong University, 2019 , 53(7) : 838 -843 . DOI: 10.16183/j.cnki.jsjtu.2019.07.010

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