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https://doi.org/10.5552/drvind.2019.1840

Estimating Modulus of Elasticity (MOE) of Particleboards Using Artificial Neural Networks to Reduce Quality Measurements and Costs

Rıfat Kurt ; Bartin University, Faculty of Forestry, Department of Forest Industrial Engineering, Bartin, Turkey
Selman Karayilmazlar ; Bartin University, Faculty of Forestry, Department of Forest Industrial Engineering, Bartin, Turkey

Puni tekst: engleski, pdf (555 KB) str. 257-263 preuzimanja: 272* citiraj
APA 6th Edition
Kurt, R. i Karayilmazlar, S. (2019). Estimating Modulus of Elasticity (MOE) of Particleboards Using Artificial Neural Networks to Reduce Quality Measurements and Costs. Drvna industrija, 70 (3), 257-263. https://doi.org/10.5552/drvind.2019.1840
MLA 8th Edition
Kurt, Rıfat i Selman Karayilmazlar. "Estimating Modulus of Elasticity (MOE) of Particleboards Using Artificial Neural Networks to Reduce Quality Measurements and Costs." Drvna industrija, vol. 70, br. 3, 2019, str. 257-263. https://doi.org/10.5552/drvind.2019.1840. Citirano 22.06.2021.
Chicago 17th Edition
Kurt, Rıfat i Selman Karayilmazlar. "Estimating Modulus of Elasticity (MOE) of Particleboards Using Artificial Neural Networks to Reduce Quality Measurements and Costs." Drvna industrija 70, br. 3 (2019): 257-263. https://doi.org/10.5552/drvind.2019.1840
Harvard
Kurt, R., i Karayilmazlar, S. (2019). 'Estimating Modulus of Elasticity (MOE) of Particleboards Using Artificial Neural Networks to Reduce Quality Measurements and Costs', Drvna industrija, 70(3), str. 257-263. https://doi.org/10.5552/drvind.2019.1840
Vancouver
Kurt R, Karayilmazlar S. Estimating Modulus of Elasticity (MOE) of Particleboards Using Artificial Neural Networks to Reduce Quality Measurements and Costs. Drvna industrija [Internet]. 2019 [pristupljeno 22.06.2021.];70(3):257-263. https://doi.org/10.5552/drvind.2019.1840
IEEE
R. Kurt i S. Karayilmazlar, "Estimating Modulus of Elasticity (MOE) of Particleboards Using Artificial Neural Networks to Reduce Quality Measurements and Costs", Drvna industrija, vol.70, br. 3, str. 257-263, 2019. [Online]. https://doi.org/10.5552/drvind.2019.1840

Sažetak
There are a large number of costs that enterprises need to bear in order to produce the same product at the same quality for a more affordable price. For this reason, enterprises have to minimize their expenses through a couple of measures in order to offer the same product for a lower price by minimizing these costs. Today, quality control and measurements constitute one of the major cost items of enterprises. In this study, the modulus of elasticity values of particleboards were estimated by using Artificial Neural Networks (ANN) and other mechanical properties of particleboards in order to reduce the measurement costs in particleboard enterprises. In addition to that, the future values of modulus of elasticity were also estimated using the same variables with the purpose of monitoring the state of the process. For this purpose, data regarding the mechanical properties of the boards were randomly collected from the enterprise for three months. The sample size (n) was: 6 and the number of samples (m): 65 and a total of 65 average measurement values were obtained for each mechanical property. As a result of the implementation, the low Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD) and Mean Squared Error (MSE) performance measures of the model clearly showed that some quality characteristics could easily be estimated by the enterprises without having to make any measurements by ANN.

Ključne riječi
estimate; modulus of elasticity; particleboard; ANN

Hrčak ID: 225632

URI
https://hrcak.srce.hr/225632

[hrvatski]

Posjeta: 518 *