Optimal preventive maintenance for reparable networks

Memari, Maryam; Zarezadeh, Somayeh; Asadi, Majid

doi:10.1002/asmb.2634

Cited by 6 publications

(11 citation statements)

References 43 publications

(77 reference statements)

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“…Memari et al 148 have proposed an adopted age‐based PM models for verifying the optimal PM time of the system. Assume that a system, with a known signature vector and reliability function in (2), starts to operate at time

t = 0

.…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…Assume that at time

t > 0

, the operator knows the event that “the system still operates at time

t

, but exactly

k

components have failed at that time.” Under this information, Memari et al 148 have proposed some PM policies for optimal preserving of the system. If

T

denotes the lifetime of the system and

X_{i : n}

denotes the

i

th ordered component lifetime, then this event is equivalent to saying that

T > t

and the event

E_{k}

occurs, where

E_{k} = (X_{k : n} \leq t < X_{k + 1 : n}) .

Under these conditions, the residual lifetime of the system is

T_{t, k} = (T - t | T > t, E_{k}) .

Then, the reliability function of

T_{t, k}

, denoted by

{\overline{H}}_{t, k} (x)

, is represented as

\begin{align} {\overset{H}{true}}_{t, k} false(x false) = \sum_{i = 0}^{n prefix- k prefix- 1} S_{k, n} false(i false) 𝒬_{i false| t, k} false(x false), \end{align}

where

…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…Memari et al 148 considered a system with

n

independent components partitioned to

L \geq 2

different groups such that

n_{j}

j = 1, \dots, L

, components are of type

j

and

\sum_{j = 1}^{L} n_{j} = n

. Let each failed component of type

j

be replaced by a new one with cost

c_{0}^{(j)}

, and an unfailed component of type

j

be renewed with cost

c_{1}^{(j)}

j = 1, \dots, L

.…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…Memari et al 148 have considered a system consisting of

L

types of components such that the number of the components of type

j

n_{j}, j = 1, \dots, L

, where

\sum_{j = 1}^{L} n_{j} = n

. Suppose the system is alive at time

t

and assume that at that time, exactly

k_{j}

components of type

j

have failed.…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…The optimal PM time

T_{PM}^{*}

is obtained by minimizing

η_{t, k_{1}, \dots, k_{L}} (T_{PM})

over

T_{PM}

. For some examples on PM on communication networks based on this policy, we refer to Memari et al 148 …”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

See 4 more Smart Citations

An overview of some classical models and discussion of the signature‐based models of preventive maintenance

Asadi

Hashemi

2022

Appl Stoch Models Bus & Ind

Self Cite

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In reliability engineering literature, a large number of research papers on optimal preventive maintenance (PM) of technical systems (networks) have appeared based on preliminary many different approaches. According to the existing literature on PM strategies, the authors have considered two scenarios for the component failures of the system. The first scenario assumes that the components of the system fail due to aging, while the second scenario assumes the system fails according to the fatal shocks arriving at the system from external or internal sources. This article reviews different approaches on the optimal strategies proposed in the literature on the optimal maintenance of multi‐component coherent systems. The emphasis of the article is on PM models given in the literature whose optimization criteria (cost function and stationary availability) are developed by using the signature‐based (survival signature‐based) reliability of the system lifetime. The notions of signature and survival signature, defined for systems consisting of one type or multiple types of components, respectively, are powerful tools assessing the reliability and stochastic properties of coherent systems. After giving an overview of the research works on age‐based PM models of one‐unit systems and k‐out‐of‐n systems, we provide a more detailed review of recent results on the signature‐based and survival signature‐based PM models of complex systems. In order to illustrate the theoretical results on different proposed PM models, we examine two real examples of coherent systems both numerically and graphically.

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t = 0

.…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…Assume that at time

t > 0

, the operator knows the event that “the system still operates at time

t

, but exactly

k

components have failed at that time.” Under this information, Memari et al 148 have proposed some PM policies for optimal preserving of the system. If

T

denotes the lifetime of the system and

X_{i : n}

denotes the

i

th ordered component lifetime, then this event is equivalent to saying that

T > t

and the event

E_{k}

occurs, where

E_{k} = (X_{k : n} \leq t < X_{k + 1 : n}) .

Under these conditions, the residual lifetime of the system is

T_{t, k} = (T - t | T > t, E_{k}) .

Then, the reliability function of

T_{t, k}

, denoted by

{\overline{H}}_{t, k} (x)

, is represented as

\begin{align} {\overset{H}{true}}_{t, k} false(x false) = \sum_{i = 0}^{n prefix- k prefix- 1} S_{k, n} false(i false) 𝒬_{i false| t, k} false(x false), \end{align}

where

…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…Memari et al 148 considered a system with

n

independent components partitioned to

L \geq 2

different groups such that

n_{j}

j = 1, \dots, L

, components are of type

j

and

\sum_{j = 1}^{L} n_{j} = n

. Let each failed component of type

j

be replaced by a new one with cost

c_{0}^{(j)}

, and an unfailed component of type

j

be renewed with cost

c_{1}^{(j)}

j = 1, \dots, L

.…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…Memari et al 148 have considered a system consisting of

L

types of components such that the number of the components of type

j

n_{j}, j = 1, \dots, L

, where

\sum_{j = 1}^{L} n_{j} = n

. Suppose the system is alive at time

t

and assume that at that time, exactly

k_{j}

components of type

j

have failed.…”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

“…The optimal PM time

T_{PM}^{*}

is obtained by minimizing

η_{t, k_{1}, \dots, k_{L}} (T_{PM})

over

T_{PM}

. For some examples on PM on communication networks based on this policy, we refer to Memari et al 148 …”

Section: Signature‐based Pm Models For Coherent Systems Under Agingmentioning

confidence: 99%

See 3 more Smart Citations

An overview of some classical models and discussion of the signature‐based models of preventive maintenance

Asadi

Hashemi

2022

Appl Stoch Models Bus & Ind

Self Cite

View full text Add to dashboard Cite

show abstract

System Signatures: A Review

Asadi

Hashemi

2022

Wiley StatsRef: Statistics Reference Online

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The signature of coherent systems, as a structure‐dependent concept, is a useful tool for assessing the reliability and stochastic properties of multicomponent systems. In this article, we give various notions of signatures that can be applied to evaluate the reliability of coherent systems when the system components fail under different scenarios. We also briefly review the recent works on applications of signatures in the preventive maintenance of coherent systems.

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Preventive maintenance for coherent systems considering postponed replacement

Asadi

2024

Appl Stoch Models Bus & Ind

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One primary objective of reliability engineering is to achieve optimal maintenance of technical systems, which ensures they remain in good operating condition. This paper proposes an age‐based preventive optimal maintenance policy for ‐component coherent systems. Under this proposed strategy, the system begins operating at and undergoes preventative maintenance (PM) at a time . If the system fails before , it will be replaced with a new one. If the system is still functioning at time , an assessment is made based on the number of failed components to determine whether the system should be replaced or allowed to continue operating. If the number of failures at is below a predetermined threshold , the PM time is postponed and a new PM time will be scheduled, and the system continues operating in the interval . Otherwise, the entire system is preventively replaced at with a new one. In this scenario, we use a cost function to determine the optimal values of decision variables , , and . To examine the effectiveness of our proposed model, we analyze some examples of coherent systems using graphical and numerical methods.

show abstract

Optimal preventive maintenance for reparable networks

Cited by 6 publications

References 43 publications

An overview of some classical models and discussion of the signature‐based models of preventive maintenance

An overview of some classical models and discussion of the signature‐based models of preventive maintenance

System Signatures: A Review

Preventive maintenance for coherent systems considering postponed replacement

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