An Optimization Model for Environmental Ergonomics Assessment in Bioproduction of Food SMEs

  • Mirwan Ushada Department of Agro-industrial Technology, Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta
  • Hani Febri Mustika Research Center for Informatics, Indonesian Institute of Sciences (LIPI), Bandung
  • Aina Musdholifah Department of Computer Sciences and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta
  • Tsuyoshi Okayama Department of Regional and Environmental Science, College of Agriculture, Ibaraki University
DOI: https://doi.org/10.4308/hjb.27.4.296

Abstract

Environmental ergonomics in bioproduction of food Small Medium-sized Enterprises (SMEs) become a concern and need to be optimized. An optimization model was developed using a Genetic Algorithm (GA). The weight of an Artificial Neural Network Model was used as a fitness function for GA. The research objectives were: 1) To design an environmental ergonomic assessment system for bioproduction of Food SMEs, 2) To develop an optimization model for environmental ergonomic assessment using a Genetic Algorithm. GA is utilized to search optimal set points of environmental ergonomics based on the predicted fitness values. Each chromosome of GA represents the environmental ergonomics value. The parameters were heart rate, bioproduction temperature, distribution of bioproduction relative humidity and light intensity. The target of the optimization model was the bioproduction temperature set points. The research result indicated the model generated optimum values of environmental ergonomics parameter in bioproduction of food SMEs. The parameters could be used to provide standard workplace environment for the sustainability of food SMEs.

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Published
2020-10-01
How to Cite
UshadaM., MustikaH. F., MusdholifahA., & OkayamaT. (2020). An Optimization Model for Environmental Ergonomics Assessment in Bioproduction of Food SMEs. HAYATI Journal of Biosciences, 27(4), 296. https://doi.org/10.4308/hjb.27.4.296
Issue
Vol. 27 No. 4 (2020): October 2020
Section
Articles

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