Manufacturing lead time estimation using data mining

Ozturk, Atakan
Kayaligil, Sinan
Özdemirel, Nur Evin
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.

Citation Formats
A. Ozturk, S. Kayaligil, and N. E. Özdemirel, “Manufacturing lead time estimation using data mining,” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 173, no. 2, pp. 683–700, 2006, Accessed: 00, 2020. [Online]. Available: