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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kabadurmus, O. Pathak, O. Smith, J.S. Smith, A.E. Yapicioglu, H. |
| Copyright Year | 2010 |
| Description | Author affiliation: Auburn University, Department of Industrial and Systems Engineering, Alabama 36849, USA (Kabadurmus, O.; Pathak, O.; Smith, J.S.; Smith, A.E.) || Anadolu University, Department of Industrial Engineering, Eskisehir, 26480, TURKEY (Yapicioglu, H.) |
| Abstract | The quality of hot mix asphalt (HMA) is directly related to the quality of the input aggregates and the control of the production process. Many factors such as aggregate gradation and moisture level affect the quality of hot mix asphalt. As state agencies dictate certain standards on quality of the product, some quality assurance techniques have been used in HMA plants. In the current practice, a production sample is taken and analyzed in the lab. The lab analysis takes approximately two hours, making it difficult to quickly correct production mix problems. In this paper, a new online process control of asphalt production system designed to overcome this problem is described. In the proposed system, an image processing system continuously analyzes images of the samples and the required corrective action is taken instantly by a computerized optimization system. In this paper, the simulation model of the proposed online process control system is presented and the results are discussed. |
| Starting Page | 1522 |
| Ending Page | 1533 |
| File Size | 448017 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781424498666 |
| ISSN | 15584305 |
| e-ISBN | 9781424498659 |
| DOI | 10.1109/WSC.2010.5679042 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Aggregates Asphalt Production Process control Roads Image analysis |
| Content Type | Text |
| Resource Type | Article |
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