@inproceedings{fb365650ae954019914de62000041145,
title = "A Big Data based Cost Prediction Method for Remanufacturing End-of-Life Products",
abstract = "Remanufacturing is considered as an important industrial process to restore the performance and function of End-of-Life (EOL) products to a like-new state. In order to help enterprises effectively and precisely predict the cost of remanufacturing processes, a remanufacturing cost prediction model based on big data is developed. In this paper, a cost analysis framework is established by applying big data technologies to interpret the obtained data, identify the intricate relationship of obtained sensor data and its corresponding remanufacturing processes and associated costs. Then big data mining and particle swarm optimization Back Propagation (BP) neural network algorithm are utilized to implement the cost prediction. The application of presented model is verified by a case study, and the results demonstrates that the developed model can predict the cost of the remanufacturing accurately allowing early decision making for remanufacturability of the EOL products.",
keywords = "Big Data, BP Neural Network, Cost Prediction, End-of-Life Products, Remanufacturing",
author = "Zhouyang Ding and Zhigang Jiang and Ying Liu and Yan Wang and Congbo Li",
year = "2018",
month = jun,
day = "27",
doi = "10.1016/j.procir.2018.03.129",
language = "English",
series = "Procedia CIRP",
publisher = "Elsevier",
pages = "1362--1367",
booktitle = "51st CIRP Conference on Manufacturing Systems, CIRP CMS 2018",
note = "51st CIRP Conference on Manufacturing Systems, CIRP CMS 2018 ; Conference date: 16-05-2018 Through 18-05-2018",
}
