Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach

Guilani, Pedram Pourkarim; Azimi, Parham; Niaki, Seyed Taghi Akhavan; Niaki, Seyed Armin Akhavan

doi:10.1016/j.ress.2016.03.010

Cited by 29 publications

(11 citation statements)

References 25 publications

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“…Perform Reliability Goal for New System. Weibull distribution [32][33][34] and modifications of the Weibull distribution [35,36] for reliability analysis were discussed by several authors. Many researchers have suggested the lifetime distribution of the hydraulic excavator follows the Weibull distribution [37][38][39][40]; they stated above use Weibull distribution as theoretical reliability model, according to the experimental data, analyzed the reliability of the subsystems for the excavator.…”

Section: Proposed Comprehensive Methods For Reliability Allocationmentioning

confidence: 99%

A Comprehensive Method of Apportioning Reliability Goals for New Product of Hydraulic Excavator

Liu

Zeng

Wan

et al. 2019

Mathematical Problems in Engineering

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It is important to allocate a reliability goal for the hydraulic excavator in the early design stage of the new system. There are some effective methods for setting reliability target and allocating its constituent subsystems in the field of aerospace, electric, vehicles, railways, or chemical system, but until now there is no effective method for the hydraulic excavator or engineering machinery. In this paper, an approach is proposed which combines with the conventional reliability allocation methods for setting reliability goals and allocating the subsystem and parts useful in the early design stage of the hydraulic excavator newly developed. It includes Weibull analysis method, modified Aeronautical Radio Inc. (ARINC) method, and modified systematic failure mode and effect analysis (FMEA) method. After completing reliability allocation, it is necessary to organize the designers and experts to evaluate the rationality of the reliability target through FEMA analysis considering feasibility of the improvement technically for the part which was new developed or had fault in its predecessor. The proposed approach provides an easy methodology for allocate a practical reliability goal for the hydraulic excavator capturing the real life behavior of the product. It proposes a simple and unique way to capture the improvement of the subsystems or components of the hydraulic excavator. The proposed approach could be extended to consider other construction machinery equipment and have practicality value to research excellent mechanical product.

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Section: Proposed Comprehensive Methods For Reliability Allocationmentioning

confidence: 99%

A Comprehensive Method of Apportioning Reliability Goals for New Product of Hydraulic Excavator

Liu

Zeng

Wan

et al. 2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

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“…Currently, Mousavi et al 22 solved their reliability redundancy allocation problem under a homogeneous series–parallel system using an enhanced fruit fly algorithm. On the other hand, Guilani et al 23 provided a RAP problem in which if the failure function followed the Weibull distribution function, it would result in increasing the failure rates. In this model, the system was configured in a series–parallel structure, where the system components could have two types of active redundancy and cold-readiness, based on which the reliability objective was estimated using simulation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The reliability evaluation of the production machines in the job shop takes into accounts both the exponential and Weibull failures. For the parallel machines with an exponential failure rate in a shop, the reliability at time t is obtained using equation (1) 23…”

Section: Problem Definitionmentioning

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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“…An FT is composed of events and logic gates. Fault tree analysis (FTA) method analyzes the causality of failures from top events to bottom events. AND logic gate and OR logic gate are both in common use; and sometimes, other logic gates can be simplified to these two gates.…”

Section: The Construction Of Dtbn For Uncertain Systemmentioning

confidence: 99%

Application of discrete‐time Bayesian network on reliability analysis of uncertain system with common cause failure

Song

Cheng

et al. 2018

Quality & Reliability Eng

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With the increasing complexity of engineering systems, reliability analysis and evaluation of systems with traditional methods can't meet practical engineering requirements. Based on limited experimental conditions, lack of data, complex structure models, insufficient cognitive abilities, and many other issues, people have to consider many uncertain factors in system reliability research. Besides, common cause failure (CCF) has become an important factor of system failure. In this paper, a discrete‐time Bayesian network (DTBN) associated with an eight‐rotor unmanned aerial vehicle (UAV) system is presented to discuss above problems. In this approach, the system is assumed as a two‐state system. After that, interval analysis theory is employed to deal with uncertainty. We consider the four sets of auxiliary propellers in the auxiliary power group as a 3/8 voting system, and β factor model is used to process CCF in the auxiliary power group. The proposed methods prove the validity of proposing interval analysis theory to solve uncertain problems and it is necessary to consider reducing or avoiding CCFs in system.

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Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach

Cited by 29 publications

References 25 publications

A Comprehensive Method of Apportioning Reliability Goals for New Product of Hydraulic Excavator

A Comprehensive Method of Apportioning Reliability Goals for New Product of Hydraulic Excavator

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

Application of discrete‐time Bayesian network on reliability analysis of uncertain system with common cause failure

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