TY - JOUR
T1 - Simulation-based experimental design and statistical modeling for lead time quotation
AU - Li, Minqi
AU - Yang, Feng
AU - Wan, Hong
AU - Fowler, John
N1 - Funding Information:
This research was supported by National Science Foundation Grant CMMI-1068131 .
Publisher Copyright:
© 2014 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
PY - 2015/10/1
Y1 - 2015/10/1
N2 - In a produce-to-order environment, it is of substantial interest to be able to quote a tight and reliable lead time for a new job (or order) upon its arrival to a manufacturing system. This work developed a simulation-based statistical approach to provide responsive and high-quality prediction of a new job's flow time through the system, which renders the capability of accurately quoting lead times in real time. The approach integrates analytical queueing analysis, design of experiments, and statistical modeling to quantify the dependence of a new job's flow time distribution upon the shop status "seen" by that job. To the best of our knowledge, this is the first attempt to design simulation experiments in the space spanned by a complete set of shop status factors for the thorough investigation of the possible impacts those factors may have on the distribution of a new job's flow time. The method has been applied on a scaled-down semiconductor manufacturing system, and the quality of the quoted lead time has been evaluated based on a large and well-designed validation data set in terms of the six commonly used performance criteria.
AB - In a produce-to-order environment, it is of substantial interest to be able to quote a tight and reliable lead time for a new job (or order) upon its arrival to a manufacturing system. This work developed a simulation-based statistical approach to provide responsive and high-quality prediction of a new job's flow time through the system, which renders the capability of accurately quoting lead times in real time. The approach integrates analytical queueing analysis, design of experiments, and statistical modeling to quantify the dependence of a new job's flow time distribution upon the shop status "seen" by that job. To the best of our knowledge, this is the first attempt to design simulation experiments in the space spanned by a complete set of shop status factors for the thorough investigation of the possible impacts those factors may have on the distribution of a new job's flow time. The method has been applied on a scaled-down semiconductor manufacturing system, and the quality of the quoted lead time has been evaluated based on a large and well-designed validation data set in terms of the six commonly used performance criteria.
KW - Design of experiments
KW - Flow time estimation
KW - Lead time/due date quoting
KW - Regression
KW - Simulation
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U2 - 10.1016/j.jmsy.2014.07.012
DO - 10.1016/j.jmsy.2014.07.012
M3 - Article
AN - SCOPUS:84953358669
SN - 0278-6125
VL - 37
SP - 362
EP - 374
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
ER -