An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties
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 uncer...
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| Format: | Article |
| Language: | English |
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IDOSI Publication
2013
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/5494/ http://umpir.ump.edu.my/id/eprint/5494/1/Published.pdf |
| _version_ | 1848817600597852160 |
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| author | Amir, Azizi Amir Yazid, Ali Loh, Wei Ping |
| author_facet | Amir, Azizi Amir Yazid, Ali Loh, Wei Ping |
| author_sort | Amir, Azizi |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | 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
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| first_indexed | 2025-11-15T01:24:21Z |
| format | Article |
| id | ump-5494 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T01:24:21Z |
| publishDate | 2013 |
| publisher | IDOSI Publication |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-54942018-02-23T02:44:20Z http://umpir.ump.edu.my/id/eprint/5494/ An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties Amir, Azizi Amir Yazid, Ali Loh, Wei Ping TS Manufactures 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 IDOSI Publication 2013 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/5494/1/Published.pdf 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) http://www.idosi.org/wasj/wasj25(3)2013.htm DOI: 10.5829/idosi.wasj.2013.25.03.63 |
| spellingShingle | TS Manufactures Amir, Azizi Amir Yazid, Ali Loh, Wei Ping An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties |
| title | An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties |
| title_full | An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties |
| title_fullStr | An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties |
| title_full_unstemmed | An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties |
| title_short | An Adaptive Neuro-Fuzzy Inference System for a Dynamic Production Environment under Uncertainties |
| title_sort | adaptive neuro-fuzzy inference system for a dynamic production environment under uncertainties |
| topic | TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/5494/ http://umpir.ump.edu.my/id/eprint/5494/ http://umpir.ump.edu.my/id/eprint/5494/ http://umpir.ump.edu.my/id/eprint/5494/1/Published.pdf |