Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/157425 
Year of Publication: 
2015
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 11 [Publisher:] Springer [Place:] Heidelberg [Year:] 2015 [Pages:] 101-110
Publisher: 
Springer, Heidelberg
Abstract: 
In this study, the analytical probability models for an automated serial production system, bufferless that consists of n-machines in series with common transfer mechanism and control system was developed. Both time to failure and time to repair a failure are assumed to follow exponential distribution. Applying those models, the effect of system parameters on system performance in actual croissant production line was studied. The production line consists of six workstations with different numbers of reparable machines in series. Mathematical models of the croissant production line have been developed using Markov process. The strength of this study is in the classification of the whole system in states, representing failures of different machines. Failure and repair data from the actual production environment have been used to estimate reliability and maintainability for each machine, workstation, and the entire line is based on analytical models. The analysis provides a useful insight into the system's behaviour, helps to find design inherent faults and suggests optimal modifications to upgrade the system and improve its performance.
Subjects: 
Manufacturing systems
Performance evaluation
Markov chain
Croissant production line
Reparable machines
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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