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Manufacturing lead time estimation using data mining
Date
2006-09-01
Author
Ozturk, Atakan
Kayaligil, Sinan
Özdemirel, Nur Evin
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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We explore use of data mining for lead time estimation in make-to-order manufacturing. The regression tree approach is chosen as the specific data mining method. Training and test data are generated from variations of a job shop simulation model. Starting with a large set of job and shop attributes, a reasonably small subset is selected based on their contribution to estimation performance. Data mining with the selected attributes is compared with linear regression and three other lead time estimation methods from the literature. Empirical results indicate that our data mining approach coupled with the attribute selection scheme outperforms these methods.
Subject Keywords
Management Science and Operations Research
,
Modelling and Simulation
,
Information Systems and Management
URI
https://hdl.handle.net/11511/48973
Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
DOI
https://doi.org/10.1016/j.ejor.2005.03.015
Collections
Department of Industrial Engineering, Article
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A. Ozturk, S. Kayaligil, and N. E. Özdemirel, “Manufacturing lead time estimation using data mining,”
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
, pp. 683–700, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48973.