Simulating Fuzzy Manufacturing System: Case Study
This paper presents an approach by considering fuzzy parameters in simulation model to obtain fuzzy throughputs in manufacturing systems. The basic subject of simulation is the probabilistic approach to describing real world uncertainty. However, in many cases we do not have information that would b...
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          | Published in | 2009 International Conference on Computer Engineering and Technology Vol. 1; pp. 505 - 509 | 
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| Main Authors | , , | 
| Format | Conference Proceeding | 
| Language | English | 
| Published | 
            IEEE
    
        01.01.2009
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| Subjects | |
| Online Access | Get full text | 
| ISBN | 1424433347 9781424433346 9780769535210 0769535216  | 
| DOI | 10.1109/ICCET.2009.216 | 
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| Abstract | This paper presents an approach by considering fuzzy parameters in simulation model to obtain fuzzy throughputs in manufacturing systems. The basic subject of simulation is the probabilistic approach to describing real world uncertainty. However, in many cases we do not have information that would be precise enough to build the corresponding probabilistic model or there are some human factors that prevent doing so. In such conditions the statistical and mathematical tools of fuzzy set theory may be successfully used. This paper applies t-test for validating the results obtained from conventional simulation and fuzzy simulation in comparison with the actual data of manufacturing system. Then, we use fuzzy simulation to improve the performance of manufacturing system by considering production constraints, system limitations and desired targets. The design of fuzzy simulation is discussed for an actual and large multi product assembly shop. | 
    
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| AbstractList | This paper presents an approach by considering fuzzy parameters in simulation model to obtain fuzzy throughputs in manufacturing systems. The basic subject of simulation is the probabilistic approach to describing real world uncertainty. However, in many cases we do not have information that would be precise enough to build the corresponding probabilistic model or there are some human factors that prevent doing so. In such conditions the statistical and mathematical tools of fuzzy set theory may be successfully used. This paper applies t-test for validating the results obtained from conventional simulation and fuzzy simulation in comparison with the actual data of manufacturing system. Then, we use fuzzy simulation to improve the performance of manufacturing system by considering production constraints, system limitations and desired targets. The design of fuzzy simulation is discussed for an actual and large multi product assembly shop. | 
    
| Author | Kor, H. Hatefi, S.M. Azadeh, A.  | 
    
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| SubjectTerms | Analytical models Assembly Computational modeling Computer simulation Fuzzy set theory Fuzzy systems Human factors Manufacturing systems Production systems Uncertainty  | 
    
| Title | Simulating Fuzzy Manufacturing System: Case Study | 
    
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