e-journal

Prediction of Hot Glue Content for Sealing Toothpaste Carton

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This research compared 2 types of model (regression model and artificial neural network) for prediction of glue content for sealing toothpaste carton from 4 sealing process factors, i.e., production line, diameter of toothpaste tube, pressure in glue nozzle during applying glue onto a toothpaste carton and glue temperature in a glue tank. Models under study included 3 regression models, i.e., multiple regression, polynomial regression and stepwise regression, and backpropagation neural network (BPN). The results indicated that the BPN model possessed higher prediction accuracy and generalization capability and lower bias. The best BPN model had a structure of 4-10-1 with the mean absolute error (MAE) of validating data set of 0.04 gram. In addition,the BPN model identified that the most influential sealing process factors affecting the prediction of glue content were pressure in glue nozzle and glue temperature in the glue tank. The packing department should concentrate on monitoring the value of both factors to control the consistency of glue usage.

Keywords: Regression; backpropagation neural network, toothpaste carton, glue content prediction

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Ketersediaan

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Informasi Detail

Judul Seri

Agriculture and Agricultural Science Procedia

No. Panggil

-

Penerbit

: Elsevier., 2015

Deskripsi Fisik

Agriculture and Agricultural Science Procedia 3 ( 2015 ) 14 – 19

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

3 ( 2015 )

Subjek

KIMIA

Info Detail Spesifik

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Pernyataan Tanggungjawab

Wati/Agus

Versi lain/terkait

Lampiran Berkas

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