Application of frequency domain experiments in the factor screening of production systems
The purpose of this study was to demonstrate that the Application of Frequency Domain Experiments (AFDE) method is effective in screening for discrete variable factors within production systems, plus requires fewer computer simulations than conventional factorial design. To help clarify this, an ass...
Saved in:
Main Author: | |
---|---|
Format: | Article |
Published: |
Chiang Mai University
2015
|
Subjects: | |
Online Access: | http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84860736764&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/38628 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
id |
th-cmuir.6653943832-38628 |
---|---|
record_format |
dspace |
spelling |
th-cmuir.6653943832-386282015-06-16T07:53:40Z Application of frequency domain experiments in the factor screening of production systems Minsan,W. Physics and Astronomy (all) Chemistry (all) Materials Science (all) Mathematics (all) Biochemistry, Genetics and Molecular Biology (all) The purpose of this study was to demonstrate that the Application of Frequency Domain Experiments (AFDE) method is effective in screening for discrete variable factors within production systems, plus requires fewer computer simulations than conventional factorial design. To help clarify this, an assembly line production system was designed in order to have factor screening experiments carried out using the AFDE method. The study assembly line produces one type of product and there were ten workstations assigned to be the study's discrete variable factors. Each factor had one to five machines for the workers to control. In the experiment, there were three main study aims in terms of the assembly line production process, these being to carry out: 1) A Major Factor Study, 2) Impact Ranking Major Factors Study, and 3) Sensitivity Impact of the Factors Study. The study results show that AFDE had the ability to detect bottleneck workstations in the production system for all the types of study undertaken. When assigning the system to have one, two or three bottleneck stations in a respective order, AFDE was able to detect these bottleneck stations and order the importance of the stations with 100% accuracy. In addition, AFDE requires fewer computer runs than conventional factorial design. 2015-06-16T07:53:40Z 2015-06-16T07:53:40Z 2012-05-14 Article 01252526 2-s2.0-84860736764 http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84860736764&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/38628 Chiang Mai University |
institution |
Chiang Mai University |
building |
Chiang Mai University Library |
country |
Thailand |
collection |
CMU Intellectual Repository |
topic |
Physics and Astronomy (all) Chemistry (all) Materials Science (all) Mathematics (all) Biochemistry, Genetics and Molecular Biology (all) |
spellingShingle |
Physics and Astronomy (all) Chemistry (all) Materials Science (all) Mathematics (all) Biochemistry, Genetics and Molecular Biology (all) Minsan,W. Application of frequency domain experiments in the factor screening of production systems |
description |
The purpose of this study was to demonstrate that the Application of Frequency Domain Experiments (AFDE) method is effective in screening for discrete variable factors within production systems, plus requires fewer computer simulations than conventional factorial design. To help clarify this, an assembly line production system was designed in order to have factor screening experiments carried out using the AFDE method. The study assembly line produces one type of product and there were ten workstations assigned to be the study's discrete variable factors. Each factor had one to five machines for the workers to control. In the experiment, there were three main study aims in terms of the assembly line production process, these being to carry out: 1) A Major Factor Study, 2) Impact Ranking Major Factors Study, and 3) Sensitivity Impact of the Factors Study. The study results show that AFDE had the ability to detect bottleneck workstations in the production system for all the types of study undertaken. When assigning the system to have one, two or three bottleneck stations in a respective order, AFDE was able to detect these bottleneck stations and order the importance of the stations with 100% accuracy. In addition, AFDE requires fewer computer runs than conventional factorial design. |
format |
Article |
author |
Minsan,W. |
author_facet |
Minsan,W. |
author_sort |
Minsan,W. |
title |
Application of frequency domain experiments in the factor screening of production systems |
title_short |
Application of frequency domain experiments in the factor screening of production systems |
title_full |
Application of frequency domain experiments in the factor screening of production systems |
title_fullStr |
Application of frequency domain experiments in the factor screening of production systems |
title_full_unstemmed |
Application of frequency domain experiments in the factor screening of production systems |
title_sort |
application of frequency domain experiments in the factor screening of production systems |
publisher |
Chiang Mai University |
publishDate |
2015 |
url |
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84860736764&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/38628 |
_version_ |
1681421508096819200 |