Binary State Reliability Computation for a Complex System Based on Extended Bernoulli Trials: Multiple Autonomous Robots

Fazlollahtabar, Hamed; Niaki, Seyed Taghi Akhavan

doi:10.1002/qre.2137

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…In the present study, that three basic factors play an important role in the final decision, we must use the multi-objective optimization method. Fazlollahtabar and Niaki [ 32 ] described a comprehensive fault tree analysis based on the critical components of industrial robots [33]. Karimi, Niaki [34] presented A complete classification of the subject literature in this field.…”

Section: 1multi-objective Optimizationmentioning

confidence: 99%

Concurrent Optimization of Reliability, Maintainability and Total Cost in a Job Shop Production System with Multiple Fuzzy Parameters

Naeini

Gholizadeh

2023

Scientia Iranica

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An integrated intelligent algorithm is proposed to optimize the reliability, maintainability, and total cost in the job shop production system. The algorithm consists of three basic modules of computer simulation. each comprising three phases of Algorithm, simulation, and Experiments/robustness validation. In the design phase, different scenarios are determined by changing parameters affecting the reliability, maintainability, and total cost. The job shop production system is simulated in the simulation phase. Then, a fuzzy simulation approach is implemented to run the simulation model for each scenario with ambiguous inputs. Accordingly, the investment cost, maintenance cost, mean time to repair (MTTR), and mean time to failure (MTTF) are obtained. Finally, the performance of different scenarios is assessed in the third module. ANN and DEA are separately used in this module and the preferred method is selected based on the robustness test and extensive sensitivity analysis. DEA and ANN are then employed to rank the design alternatives concerning the initial inputs and outputs. To show the applicability and superiority of the proposed integrated algorithm, it is applied to optimize the design of a fuzzy job shop production system consisting of five workstations.

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Section: 1multi-objective Optimizationmentioning

confidence: 99%

Concurrent Optimization of Reliability, Maintainability and Total Cost in a Job Shop Production System with Multiple Fuzzy Parameters

Naeini

Gholizadeh

2023

Scientia Iranica

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“…Fazlollahtabar and Niaki 4 proposed a reliability investigation model for a system of binary state autonomous robots in an AGV system. In their model, some real cases such as the table of truth, block diagram, and the total of the states were analyzed simultaneously.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective optimization of job shops with automated guided vehicles: A non-dominated sorting cuckoo search algorithm

Karimi

Niaki

Niknamfar

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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The reliability of machinery and automated guided vehicle has been one of the most important challenges to enhance production efficiency in several manufacturing systems. Reliability improvement would result in a simultaneous reduction of both production times and transportation costs of the materials, especially in automated guided vehicles. This article aims to conduct a practical multi-objective reliability optimization model for both automated guided vehicles and the machinery involved in a job-shop manufacturing system, where different machines and the storage area through some parallel automated guided vehicles handle materials, parts, and other production needs. While similar machines in each shop are limited to failures based on either an Exponential or a Weibull distribution via a constant rate, the machines in different shops fail based on different failure rates. Meanwhile, as the model does not contain any closed-form equation to measure the machine reliability in the case of Weibull failure, a simulation approach is employed to estimate the shop reliability to be further maximized using the proposed model. Besides, the automated guided vehicles are restricted to failures according to an Exponential distribution. Furthermore, choosing the best locations of the shops is proposed among some potential places. The proposed NP-Hard problem is then solved by designing a novel non-dominated sorting cuckoo search algorithm. Furthermore, a multi-objective teaching-learning-based optimization, as well as a multi-objective invasive weed optimization are designed to validate the results obtained. Ultimately, a novel AHP-TOPSIS method is carried out to rank the algorithms in terms of six performance metrics.

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Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches

Chemweno

Pintelon

Muchiri

et al. 2018

Reliability Engineering & System Safety

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Binary State Reliability Computation for a Complex System Based on Extended Bernoulli Trials: Multiple Autonomous Robots

Cited by 4 publications

References 21 publications

Concurrent Optimization of Reliability, Maintainability and Total Cost in a Job Shop Production System with Multiple Fuzzy Parameters

Concurrent Optimization of Reliability, Maintainability and Total Cost in a Job Shop Production System with Multiple Fuzzy Parameters

Multi-objective optimization of job shops with automated guided vehicles: A non-dominated sorting cuckoo search algorithm

Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches

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