Amir, Azizi and Amir Yazid, Ali and Loh, Wei Ping (2013) An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties. World Applied Sciences Journal, 25 (3). pp. 428-433. ISSN 1818-4952. (Published)
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Abstract
Throughput modelling evaluates the performance and behaviour of the production systems. This study examined the potential application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for modelling throughput under production uncertainties. Five significant factors were considered as the main uncertainties of production: scrap, setup time, break time, demand and lead time of manufacturing. Observations on the production uncertainties had been performed for 104 weeks in a tile manufacturing industry. The results of ANFIS model had been compared with Multiple Linear Regression (MLR) model. The results showed that ANFIS model was capable of providing adjusted R-squared of 98%, which was higher than the MLR mode
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > TS Manufactures |
| Faculty/Division: | Faculty of Manufacturing Engineering |
| Depositing User: | Dr. Amir Azizi |
| Date Deposited: | 09 Apr 2014 02:11 |
| Last Modified: | 23 Feb 2018 02:44 |
| URI: | http://umpir.ump.edu.my/id/eprint/5494 |
| Download Statistic: | View Download Statistics |
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