TY - GEN
T1 - Estimation of lead time in the RFID-enabled real-time shopfloor production with a data mining model
AU - Zhong, Ray Y.
AU - Huang, George Q.
AU - Dai, Qing Yun
AU - Zhang, Tao
N1 - Publisher Copyright:
© 2013 Springer-Verlag Berlin Heidelberg
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Data mining
KW - Lead time
KW - Radio frequency identification (RFID)
KW - Real-time
KW - Shopfloor production
UR - https://www.scopus.com/pages/publications/84891554242
U2 - 10.1007/978-3-642-38391-5_33
DO - 10.1007/978-3-642-38391-5_33
M3 - Conference article published in proceeding or book
AN - SCOPUS:84891554242
SN - 9783642383908
T3 - 19th International Conference on Industrial Engineering and Engineering Management: Assistive Technology of Industrial Engineering
SP - 321
EP - 331
BT - 19th International Conference on Industrial Engineering and Engineering Management
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th International Conference on Industrial Engineering and Engineering Management: Assistive Technology of Industrial Engineering
Y2 - 27 October 2012 through 29 October 2012
ER -