Daily Worker Evaluation Model for SME-Scale Food Production System using Kansei Engineering and Artificial Neural Network

Pencarian berdasarkan :

SEMUA Pengarang Subjek ISBN/ISSN Pencarian Spesifik

Pencarian terakhir:

e-journal

Daily Worker Evaluation Model for SME-Scale Food Production System using Kansei Engineering and Artificial Neural Network

Mirwan Ushada [et al.] - Nama Orang;

This paper highlighted a daily worker evaluation model for small medium-scale food production system. The model consist of worker capacity assessment and worker performance evaluation sub-models. The model measures the relationship between Total Mood Disturbance (TMD), heart rate of worker and workplace parameters using Kansei Engineering approach. However, the rapid measurement of TMD is difficult and full of bias since using the paper-based questionnaire of Profile of Mood States (POMS). Therefore, a rapid measurement method was developed using Artificial Neural Network to support the application of daily evaluation model. The inputs of the model were heart rate, workplace temperature, relative humidity, light intensity and noise level, which were measured before and after working. The output was TMD score.The training and inspection data for ANN was collected from workers of food production system as Tempe, Bakpia, Fish Chips and Crackers industries in Yogyakarta Special Region. ANN model were tested successfully predicted TMD score using back-propagation supervised learning method. The trained ANN model generated satisfied root mean square error value. ANN model is possible to substitute conventional data acquisition of POMS. The daily evaluation model is applicable to assist industrial management for providing the appropriate worker assignment for shift schedulling and environmental set point for the workplace comfortability.

Keywords: artificial neural network; daily evaluation; profile of mood states; rapid measurement; total mood disturbance

Ketersediaan

Tidak ada salinan data

Informasi Detail

Judul Seri: Agriculture and Agricultural Science Procedia
No. Panggil: -
Penerbit: : Elsevier., 2015
Deskripsi Fisik: Agriculture and Agricultural Science Procedia 3 ( 2015 ) 84 – 88
Bahasa: English
ISBN/ISSN: doi: 10.1016/j.aaspr
Klasifikasi: NONE
Tipe Isi: -
Tipe Media: -
Tipe Pembawa: -
Edisi: 3 ( 2015 )
Subjek: Pertanian
Info Detail Spesifik: -
Pernyataan Tanggungjawab: Wati/Agus

Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas

FULL TEXT:Daily Worker Evaluation Model for SME-Scale Food Production System using Kansei Engineering and Artificial Neural Network

Komentar

Anda harus masuk sebelum memberikan komentar