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ESRA PhD Highlights

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Tian Zhang, Arts et Métiers Institute of Technology, France

06/19/2023 PhD Highlights

Reliability Performance Modeling For Reconfigurable Manufacturing System (2023)

Reliability Performance Modeling For Reconfigurable Manufacturing System (2023)

 

Supervisors: Ali SIADAT, Lazhar HOMRI, Jean-Yves DANTAN

Keywords: Reconfiguration Manufacturing System, Reliability Performance Analysis, Exponential Distribution, Weibull Distribution, Probabilistic Models, Reconfigurable Manufacturing Tools.

The assessment of reconfigurable manufacturing system reliability is critical due to the complexity of the system and the potential consequences of failures in critical applications.
During re-configurations, the quantity of interactions and interfaces can be substantial, the configuration orders and the causalities between configurations can have non-negligible effects on the reliability of the system. Therefore, the main research in this thesis is how the decisions made for reconfigurable manufacturing system impact the different aspects of reliability performance throughout the entire processing procedure, despite the increasing complexity of these systems.
A proposed framework for reliability performance analysis for reconfigurable manufacturing system helps to verify whether the interactions and interfaces have impact on the reliability performance of an RMS, through analyzing the system, evaluating potential impacts, and assessing their significance. In the framework, models based on Markov chain managed to present the configuration orders and causalities between configurations.
Two probabilistic models to describe the reliability performance include one based on the Exponential distribution and the other based on the Weibull distribution. For the Exponential distribution based model, results have proved that configuration orders have no impact on reliability. While for the Weibull distribution based model, the impact is significant.
Besides, a model based on optimistic or pessimistic evaluation can set limits and measure the significance of the impact based on various situations.
In the end, Monte Carlo simulation, sensitivity analysis and usage examples validate and verify the framework proposed.

More information on Thian's work:
https://www.researchgate.net/profile/Zhang-Tian-12
https://orcid.org/my-orcid?orcid=0000-0001-7621-4812

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