Design of a Decision Support System for Functional Beverage Flavoring

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Published: Apr 13, 2020
Keywords:
Functional beverage Hybrid Artificial Neural Network (ANN) with particle Swarm Optimization (ANN-PSO) Decision Support System (DSS)

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Ariya Ounsri
Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand
Pornthip Tabkosai
Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand
Athakorn Kengpol
Advanced Industrial Engineering Management Systems Research Center, Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand
Sopida Tuammee
College of Industrial Technology, Department of Information and Production Technology Management, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

Abstract

The objective of research is to design and develop a Decision Support System (DSS) software to assess customer satisfaction on functional beverage flavor notes. Questionnaire is launched to gather data of costumer preference. The taste, color and odor are the subjects of questionnaire. Data is acquired from 400 customers in six groups from North, North Eastern, Central, Southern, and Bangkok of Thailand that have different gender and age. The survey shows that there are 5 well known tastes of functional drinks which are mango, passion fruit, Thai blueberry, linhzhi and mangosteen in both level of concentration (100% and mixed). The DSS is analyzed by using ANN in comparison with hybrid Artificial Neural Network and Particle Swarm Optimization (ANN-PSO). Both models give the same results shown in structure (6-18-30). The minimum MSE is 0.0054784 at 6 epochs. As a result of comparison between two models, the result shows that minimum speed time of ANN-PSO faster than ANNs. Hence, ANN-PSO is an appropriate system for using in the DSS software.

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How to Cite
Ounsri, A., Tabkosai, P., Kengpol, A., & Tuammee, S. (2020). Design of a Decision Support System for Functional Beverage Flavoring. Applied Science and Engineering Progress, 13(2), 112–117. Retrieved from https://ph02.tci-thaijo.org/index.php/ijast/article/view/240581
Issue
Vol. 13 No. 2 (2020)
Section
Research Articles

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