Semi-automatic Maintenance of Regression Models: an Application in the Steel Industry
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| Title | Semi-automatic Maintenance of Regression Models: an Application in the Steel Industry |
| Authors | |
| Abstract | Software applications used in the controlling and planning of production processes commonly make use of predictive statistical models. Changes in the process involve a more or less regular need for updating the prediction models on which the operational software applications are based. The objective of this article is- to provide information which helps to design semiautomatic systems for the maintenance of statistical prediction models and- to describe a proof-of-concept implementation in an industrial application.The system developed processes the production data and provides an easy-to-use interface to construct updated models and introduce them into a software application. The article presents the architecture of the maintenance system, with a description of the algorithms that cause the system’s functionality. The system developed was implemented for keeping up-to-date prediction models which are in everyday use in a steel plate mill in the planning of the mechanical properties of steel products. The conclusion of the results is that the semi-automatic approach proposed is competitive with fully automatic and manual approaches. The benefits include good prediction accuracy and decreased workload of the deployment of updated model versions. |
| Publisher | University of Zagreb, University Computing Centre - SRCE |
| Date | 2011-12-13 |
| Source | Journal of Computing and Information Technology Vol 19, No 3 (2011) |
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