Nonlinear degradation modeling and maintenance policy for a two-stage degradation system based on cumulative damage model

Ni, Xianglong; Zhao, Jingzhe; Song, Wenyuan; Guo, Chuangxin; Li, Haiping

doi:10.17531/ein.2016.2.3

Cited by 11 publications

(5 citation statements)

References 20 publications

(33 reference statements)

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“…Formula (5a) is the degradation state evolution function. The system degradation process is considered as smooth Gamma process [4,5], and the shape-parameter () t   is assumed to be…”

Section: Ssm-moe Based On Gamma Processmentioning

confidence: 99%

A State-Space Degradation Model with Multiple Observations and Different Sampling Times

Ni¹

2018

IJPE

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A traditional state-space model (SSM) only contains one observation equation. There are some restricted conditions when using the traditional SSM to describe the evolution process between a state indicator and multiple observation indicators instantaneously. In order to solve this problem, this paper puts forward an SSM that has multiple observation equations, which can be applied to multiple observation indicators with different sampling times. The modeling process and parameters evaluation approach of the proposed SSM are studied and given. A simulation study is conducted to indicate advantages of the proposed SSM when sampling times and observation equations are not the same for different observation indicators. Simulation results show that the proposed SSM is more accurate than the traditional SSM in system degradation prediction.

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“…Formula (5a) is the degradation state evolution function. The system degradation process is considered as smooth Gamma process [4,5], and the shape-parameter () t   is assumed to be…”

Section: Ssm-moe Based On Gamma Processmentioning

confidence: 99%

A State-Space Degradation Model with Multiple Observations and Different Sampling Times

Ni¹

2018

IJPE

Self Cite

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“…Now we can calculate optimal diagnostic signal (technical state) for restoration S po using equation (4) substituting Weibull distribution function to equation (16) and by application MS Excel, we can calculate unit costs c(S p ) of preventive maintenance, diagnostics and failure risk versus diagnostic signal for predictive maintenance, optimal diagnostic signal S po (technical state) for restoration and mean operating time versus diagnostic signal for predictive maintenance Table 5 and Fig. 3.…”

Section: Numerical Solutionmentioning

confidence: 99%

“…eksploatacja i niezawodnosc - Maintenance and reliability 2017; 19 (1): 134-141, http://dx.doi.org/10.17531/ein.2017 It determines the optimal preventive maintenance and replacement schedule of the system. The paper [16] takes into account degradation modeling and maintenance policy for a two-stage degradation system, which degradation process is nonlinear and degradation rate is change over time in both stages. Influence analysis of different model parameter and maintenance policy is studied in numerical examples with results that the proposed optimal maintenance policy can help to reduce the mean cost rate.…”

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confidence: 99%

Preventive maintenance models – higher operational reliability

Legát

Mošna

Aleš

et al. 2016

EiN

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Article citation info: Introduction and literature surveyMany maintenance strategies, policies and methods have been developed, which are aimed at making maintenance cheaper and more effective. Such programs have the minimization of costs, downtime and losses due to failure of critical objects of the equipment as their main objective. Cost minimization improves the effectiveness and profitability of the organization [1,2,9,12,13,20].For creation of the maintenance policies, well described data mining input is very important. [4].In recent years, useful models of preventive and predictive maintenance optimization with different complexity and applicability have been further developed.In the paper, [5] the authors proposed a quasi-periodic imperfect preventive maintenance policy. Finally, a real case study of preventive maintenance on Chinese diesel locomotives is examined to illustrate the proposed maintenance policy.The paper [6] proposes an approach in which preventive and failure replacement costs as well as inspection cost are taken into account to determine the optimal replacement policy and an age-based inspection scheme, such that the total average costs of replacements and inspections is minimized.Determination of the preventive effect of optimal replacement policies in the paper [8] is based on aging intensity and the cost ratio of failure and preventive replacements. One of its conclusions is that not every preventive maintenance is fully effective and a policy of, "run to failure" can be more effective (note: in some cases).The proposed model in the paper [10] takes into consideration the stochastic nature of equipment failures. The output from the model is a cost distribution against the time from which the minimum cost may be found for a particular period and this period is defined as the optimum lifespan of the machine part.The paper [11] considers periodic preventive maintenance policies for a deteriorating repairable system. On each failure, the system is repaired and, at the planned times, it is periodically maintained to improve its performance reliability. Most periodic preventive maintenance (PM) models for repairable systems have been studied assuming that the failure process between two PMs follows the nonhomogeneous Poisson process (NHPP), implying the minimal repair on each failure.The paper [14] regarding warranty policy considering three maintenance options for products with multiple failure modes also showed the broad usability of the Weibull distribution. This fact supports the decision of the authors to also use the Weibull function.The paper [15] presents a new mathematical function to model an improvement based on the ratio of maintenance and repair costs, and demonstrate how it outperforms fixed improvement factor models by analyzing the effectiveness in terms of cost and reliability of a system. Legát V, MošnA F, ALeš Z, JurčA V. Preventive maintenance models -higher operational reliability. eksploatacja i niezawodnosc - Maintenance and reliability 2017; 19 (1): 134-141, http://dx...

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“…The degradation model has been extensively used to assess the reliability of a device in reliability engineering 8–10 . Ni et al 11 . developed a reliability model with degradation rate change over time.…”

Section: Introductionmentioning

confidence: 99%

Reliability assessment of a system with multi‐shock sources subject to dependent competing failure processes under phase‐type distribution

Lyu

et al. 2022

Quality & Reliability Eng

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For a system affected by multiple shock sources, the system usually experiences not only one failure process. This paper develops a reliability model for systems with multi‐shock sources subject to dependent competing failure processes (DCFPs). DCFPs consist of two failure modes: soft and hard failures. Multiple shock sources act on the system as follows: assuming there are m shock sources in total, the kth shock source works on the system at first until the system fails, and then the next shock source re‐acts on the system. Unlike the methods in other papers, the phase‐type distribution is used to build the hard failure reliability model in this paper. We consider the time lag of impacts and assume that the impact magnitudes do not exceed the hard failure threshold as an element in the transition matrix. At the same time, consider these two situations to establish a reliability model. In addition, we divide shock magnitudes into three areas: dead, nondeadly, and safe zones. An application example of a micro‐engine is studied to describe the availability of the developed reliability model. And we conduct the sensitivity analysis to exemplify the influence of the performance of the micro‐engine with parameter changing. With the proposed model, the reliability analysis is more efficient with multi‐shock sources subject to DCFPs

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Nonlinear degradation modeling and maintenance policy for a two-stage degradation system based on cumulative damage model

Cited by 11 publications

References 20 publications

A State-Space Degradation Model with Multiple Observations and Different Sampling Times

A State-Space Degradation Model with Multiple Observations and Different Sampling Times

Preventive maintenance models – higher operational reliability

Reliability assessment of a system with multi‐shock sources subject to dependent competing failure processes under phase‐type distribution

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