@inproceedings{ca571e348b62431eb089260eeb0c9d71,
title = "Research on BOM Prediction for Cutterhead System of TBM based on Quality Function Deployment",
abstract = "For project-based large-scale manufacturing equipment, frequent changes will lead to design changes, which will affect BOM structure changes and production progress. This paper studied the problems faced by the cutterhead system of TBM in production and manufacturing. By establishing the relationship between user demands and design requirements, we can predict the change trend of BOM structure, so as to realize the optimization of supply chain and production management. Through in-depth interviews with users and engineering experts, we established a scheme based on AHP-QFD-BP Neural Network. Moreover, the effectiveness of our method was verified by the real data of a TBM manufacturing company.",
keywords = "AHP-QFD, BOM prediction, TBM, cutterhead system",
author = "J. Shi and Zhu, {Y. C.} and Wang, {W. H.} and Y. Pan and T. Zhou and Hu, {Y. G.}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022 ; Conference date: 07-12-2022 Through 10-12-2022",
year = "2022",
doi = "10.1109/IEEM55944.2022.9989778",
language = "English",
series = "IEEE International Conference on Industrial Engineering and Engineering Management",
publisher = "IEEE Computer Society",
pages = "226--230",
booktitle = "IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022",
address = "United States",
}