Journal of Ambient Intelligence and Humanized Computing | 2021

Optimal replacement model for the physical component of safety critical smart-world CPSs

 
 
 

Abstract


Nowadays CPSs have drawn an upsurge of interests for their enormous potential towards the next generation smart systems where safety is a critical issue. In CPS, large number of IoT devices (sensors, actuators, etc.) are deployed to collect data to support safety critical smart-world CPS infrastructures such as smart city, smart health, smart manufacturing, and smart transportation. The degradation of physical components of safety critical smart-world CPSs would deteriorate the performance of the smart system and lead to loss of human life with significant damage to properties. Hence, planned preventive maintenance replacement of physical components of the system is vital to extend the lifetime of the system, to reduce maintenance cost and to avoid risks that may cause major harm to life and property. In this study, we focus on cost effective preventive replacement strategy that recovers failure of physical components of safety critical smart-world CPSs by mainly considering the deterioration state of the physical component on the availability of the system. In view of the degraded physical component of CPSs, we demonstrate the effects of involving maintenance actions during the deterioration state of physical components of CPSs on its availability. Since timely preventive replacement is crucial to support continuous and effective system operation, we compute the optimum time of the constant-interval of preventive replacement strategy for the physical components of CPSs. In this study, we use Weibull distribution as it is a generalized failure model that has been widely used for process equipment life data analyses. At last, the effects of the shape and the scale parameters on the optimal preventive replacement interval of the physical component are also demonstrated.

Volume None
Pages 1-12
DOI 10.1007/S12652-021-03137-5
Language English
Journal Journal of Ambient Intelligence and Humanized Computing

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