Optimal control of fault tolerant machining system with reboot and recovery in fuzzy environment using harmony search algorithm

Kumar, Pankaj; Jain, Madhu; Meena, Rakesh Kumar

doi:10.1016/j.isatra.2021.02.027

Cited by 15 publications

(7 citation statements)

References 29 publications

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“…Wang and Matthies (2019) framed epistemic uncertain parameters by taking both fuzzy and evidence variable at the same time. Most recently, Kumar et al (2022) did fuzzy modeling for a fault tolerant system with impacts of failure and recovery along reboot process and assessed the performance indices of the system.…”

Section: Review Of Literaturementioning

confidence: 99%

Load sharing repairable system with imperfect coverage in fuzzy environment

Gupta

Tasneem

2022

IJQRM

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PurposeThe purpose of this study is to develop Markovian model to obtain the transient probabilities to determine mean-time-to-failure and reliability function and further steady state availability of the repairable system. As the system parameters are uncontrollable factors; thus the life times, repair times and recovery/reboot time are assumed to be as uncertain or fuzzified distributions.Design/methodology/approachThe fuzzy approach is introduced to investigate the reliability measures of load sharing repairable system which consists of two operating units and one standby unit. On the failure of an operating component, it is instantly spotted, located and sent for recovery procedures with coverage probability. In case of imperfect recovery, reboot takes place.FindingsOn the basis of extension principle and mathematical programming approach, the authors establish membership functions for system characteristics with the help of α-cuts. To demonstrate the practical validity of the proposed fuzzified model, numerical illustrations are performed.Originality/valueThe model proposed for reliability analysis may cheer up the continuance of the work towards more applications in repairable systems. Therefore, the reader is provided with useful intuition into the nature of fuzzy computations and practical amendments while measuring ambiguous data.

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Section: Review Of Literaturementioning

confidence: 99%

Load sharing repairable system with imperfect coverage in fuzzy environment

Gupta

Tasneem

2022

IJQRM

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“…The reliability models on machine repair problem (MRP) have been broadly investigated in the literature (cf. [1][2][3][4][5][6] ) for the better design of the FMMSs. Besides active redundancy, standby redundancy can strategically enhance system reliability in machining systems.…”

Section: Introductionmentioning

confidence: 99%

“…The expert machining system is desirable to propose the prevention of unforeseen faults/failures of units and related unpleasant scenarios. The reliability models on machine repair problem (MRP) have been broadly investigated in the literature (cf 1–6 …”

Section: Introductionmentioning

confidence: 99%

Reliability analysis of standby provision multi‐unit machining systems with varied failures, degradations, imperfections, and delays

Shekhar

Devanda

Kaswan

2023

Quality & Reliability Eng

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This prospective study focuses on analyzing the reliability characteristics of multi‐unit systems with standby provisioning, accounting for failures, degradation, random delays, and probabilistic imperfections. The investigation sheds light on how these unreliable attributes hinder the performance and availability of machining systems. Given the frequent occurrence of these negative attributes within machining systems, their impact on production flow, performance, and resource utilization is significant. Moreover, these unfavorable attributes hinder the adoption of advanced technologies that rely on the continuous availability of machining systems. Thorough research on operational traits serves as a foundation for developing solutions to enhance machining system efficiency and elucidates the underlying causes of machining system failures throughout their performance lifecycle. The reliability analysis employs a state‐of‐the‐art queue‐theoretic approach. In order to model the stochastic behavior of the investigated machine repair problem in a systematic manner, we consider various statistically independent failure modes, including active/standby unit failure, degraded failure, switching failure, and common‐cause failure. The unreliable characteristics of machining systems are further compounded by factors such as imperfect fault coverage, reboot delay, and imperfect repair, necessitating a comprehensive examination to strategically implement preventive, corrective, and predictive measures. The seamless operation of multi‐unit machining systems is essential for the successful integration of advanced technologies such as cloud computing, industry 4.0, and IoT. Failures, delays, degradation, and imperfections within machining systems have detrimental effects on their efficiency and availability, demanding in‐depth investigation. To facilitate numerical experimentation and sensitivity analysis of the reliability aspects of the proposed machining system, we develop performance indices such as system reliability, mean‐time‐to‐failure, and failure frequency. These metrics provide valuable insights for decision‐makers seeking to implement measures that ensure uninterrupted availability of the machining system.

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“…One can find a review of the newest results relating to queueing models with different restriction types in the access to the service station in [ 16 ], where in all models, the supplementary variable technique is used. For example, in [ 17 ], an

-type model with Poisson arrivals and generally distributed processing times of the fault-tolerant system with server vacation policy and threshold-type waking up is developed by using the supplementary variable technique. In particular, the representation for the remaining time to repair is obtained.…”

Section: Introductionmentioning

confidence: 99%

On Transient Queue-Size Distribution in a Model of WSN Node with Threshold-Type Power-Saving Algorithm

Kempa

Kurzyk

2022

Sensors

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This article proposes a queueing model of the operation of a wireless sensor network node, in which a threshold strategy for starting the node after a period of no transmission is used. In this model, transmission of packets is resumed when the number of packets in the accumulation buffer reaches a predefined level. In the literature, most of the results for models with limited access to the service station are obtained in equilibrium. In this paper, a formula for the Laplace transform of the transient queue-size distribution is obtained and written using the key input parameters of the system. The analytical apparatus uses the concept of the embedded Markov chain, the formula for total probability, renewal theory and some supporting algebraic results. Numerical examples are attached as well.

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Optimal control of fault tolerant machining system with reboot and recovery in fuzzy environment using harmony search algorithm

Cited by 15 publications

References 29 publications

Load sharing repairable system with imperfect coverage in fuzzy environment

Load sharing repairable system with imperfect coverage in fuzzy environment

Reliability analysis of standby provision multi‐unit machining systems with varied failures, degradations, imperfections, and delays

On Transient Queue-Size Distribution in a Model of WSN Node with Threshold-Type Power-Saving Algorithm

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