Paper Info
Title
Flow-time estimation by synergistically modeling real and simulation data
Abstract
The ability to quote a competitive and reliable lead time for a new order is a key competitive advantage for manufacturers and plays a significant role in customer acquisition and satisfaction. Quoting a precise and reliable lead time requires a good prediction for the flow time of a new order. This research focuses on quantifying the dependence of the flow time upon observed job shop status variables, the size of a new order, and the arrival rate of future orders. An iterative fitting procedure based on stochastic kriging with qualitative factors, is developed to synergistically model simulation and real manufacturing data, for the prediction of a new order's flow time.
Year
DOI
Venue
2017
10.5555/3242181.3242461
WSC '17: Winter Simulation Conference Las Vegas Nevada December, 2017
Field
DocType
ISSN
Customer acquisition,Kriging,Data modeling,Industrial engineering,Simulation,Computer science,Job shop,Server,Competitive advantage,Flow time,Lead time
Conference
0891-7736
ISBN
Citations 
PageRank 
978-1-5386-3427-1
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Hoda Sabeti100.34
Feng Yang2477.21