I. I., Azmi and S. N. A. M., Zaini and Mohd Yazid, Abu (2019) Application of Mahalanobis-Taguchi system in palm oil plantation. Journal of Modern Manufacturing Systems and Technology (JMMST), 3. pp. 1-8. ISSN 2636-9575. (Published)
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Abstract
This work deals with the palm oil plantation which is not utilizing the available data to be used as reference to measure the degree of abnormal observation. There are no assessment tools to quantify the degree of seriousness of abnormal observation. When a palm oil plantation is ignoring the optimization of the factors contributing to the problem, they might produce lots of waste. The objective of this work is to measure the degree of abnormality using Mahalanobis Taguchi System (MTS) and to diagnose the parameters that influence the system. MTS is a method used for identifying or to see the pattern in decision making. The main principle MTS is to choose a group of variables and achieve optimization of the factors that contributes to the problem by embodying with Mahalanobis Distance. From the results, the degree of abnormality was successfully measured using the MTS method. There are 5 sample blocks that belong in the abnormality group; PR16 B3, PR17 C5, PR15 A5, PR16 B5 and PR17 C4. The acquired result indicates that interrow weeding is the parameters that most influence the process flow in plantation. This variable contributes to 25% of the abnormal data. It can be concluded here is this parameter need to be diagnosed by increasing the dosage of interrow weeding so that the harvesting output performance can be improve.
Item Type: | Article |
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Uncontrolled Keywords: | Mahalanobis-Taguchi system; palm oil plantation; Mahalanobis Distance |
Subjects: | T Technology > T Technology (General) T Technology > TS Manufactures |
Faculty/Division: | Faculty of Manufacturing Engineering |
Depositing User: | Dr. Mohd Yazid Abu |
Date Deposited: | 10 Oct 2019 04:23 |
Last Modified: | 21 Nov 2019 07:17 |
URI: | http://umpir.ump.edu.my/id/eprint/25975 |
Download Statistic: | View Download Statistics |
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