Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4508374 | Engineering in Agriculture, Environment and Food | 2015 | 5 Pages |
Abstract
Fusing various Kansei Engineering parameters of worker capacity requires a robust modeling tool. Artificial Neural Network (ANN) was used to develop a Kansei Engineering-based watchdog model. The model is defined as a black box relationship between worker capacity and workplace environmental parameters. Its function for assessing worker capacity can be defined as dynamic variation of mood and heart rate in a given workplace environment. Thus, these relationships were modeled using a three layered ANN. The model was demonstrated via a case study of Tempe Industry. The trained ANN model generated satisfied accuracy and minimum error. The research results concluded the possibility to assess the worker capacity in Indonesian SMFI by combining Kansei Engineering and ANN.
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Authors
Mirwan Ushada, Tsuyoshi Okayama, Haruhiko Murase,