Estimation of Lead Time in the RFID-Enabled Real-Time Shopfloor Production with a Data Mining Model

Ray Y. Zhong (), George Q. Huang, Qing-yun Dai and Tao Zhang
Additional contact information
Ray Y. Zhong: The University of Hong Kong
George Q. Huang: The University of Hong Kong
Qing-yun Dai: Guangdong University of Technology
Tao Zhang: Huaiji Dengyun Auto Parts (Holding) Co., Ltd.

Chapter Chapter 33 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 321-331 from Springer

Abstract: Abstract Lead time estimation (LTE) is difficult to carry out, especially within the RFID-enabled real-time manufacturing shopfloor environment since large number of factors may greatly affect its precision. This paper proposes a data mining approach with four steps each of which is equipped with suitable mathematical models to analysis the LTE from a real-life case and then to quantitatively examine its key impact factors such as processing routine, batching strategy, scheduling rules and critical parameters of specification. Experiments are carried out for this purpose and results imply that batching strategy, scheduling rules and two specification parameters largely influence the LTE, while, processing routine has less impact in this case.

Keywords: Data mining; Lead time; Radio frequency identification (RFID); Real-time; Shopfloor production (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-3-642-38391-5_33

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