Open AccessOptimization of Brushing, Bubble, and Microbubble Techniques Using Taguchi Method for Raw Edible Bird Nest Cleaning Purpose
Author(s) -
Divean Seenivasan,
Tan Chan Sin
Publication year - 2022
Publication title -
pertanika journal of science and technology
Language(s) - English
Resource type - Journals
eISSN - 2231-8526
pISSN - 0128-7680
DOI - 10.47836/pjst.30.2.23
Subject(s) - taguchi methods , raw material , bubble , process (computing) , process engineering , environmental science , computer science , pulp and paper industry , engineering , biology , machine learning , ecology , parallel computing , operating system
The paper presents the parameter setting and optimizing the brushing, bubble, and microbubble techniques to clean the raw edible bird nest (EBN). EBN is nourishment created entirely from the secretions of swiftlets, with no added ingredients. Because of its medical benefits, cleaned EBN is in high demand. In general, the raw EBN has been cleaned using human manual cleaning with the help of tweezers. However, this method is lengthy as it took about one hour to clean 1 EBN fully. Hence, some mechanical cleaning techniques are needed to clean the raw EBN to improve the cleaning time and cleanliness. This paper aims to optimize the three mechanical cleaning techniques: brushing, bubble, and microbubble. Taguchi Method is used to design and optimize the combination setting of all parameters. The chosen optimized parameter set will then be tested to find the optimal parameter sets for the cleaning process. The time setting for each parameter is set at 30, 45, and 60 seconds. Each of these parameters is tested to obtain the best-optimized parameter. Once the best-fit parameters are identified, the experiment is conducted using the three selected parameters with three different sequences to find the most effective and efficient sequence to clean the raw EBN. With the experiment being carried out, the output of the best sequence of the cleaning process is Sequence 1, which contributes to the cleanliness of 66.18% and cleaning time of 7 minutes.