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1

Reliability modeling for dependent competing failure processes with phase-type distribution considering changing degradation rate

Lyu Hao, Wang Shuai, Zhang Xiaowen, Yang Zaiyou, Pecht Michael

Eksploatacja i Niezawodność

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2021

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Vol. 23, no. 4

627--635

EN

In this paper, a system reliability model subject to Dependent Competing Failure Processes (DCFP) with phase-type (PH) distribution considering changing degradation rate is proposed. When the sum of continuous degradation and sudden degradation exceeds the soft failure threshold, soft failure occurs. The interarrival time between two successive shocks and total number of shocks before hard failure occurring follow the continuous PH distribution and discrete PH distribution, respectively. The hard failure reliability is calculated using the PH distribution survival function. Due to the shock on soft failure process, the degradation rate of soft failure will increase. When the number of shocks reaches a specific value, degradation rate changes. The hard failure is calculated by the extreme shock model, cumulative shock model, and run shock model, respectively. The closed-form reliability function is derived combining with the hard and soft failure reliability model. Finally, a Micro-Electro-Mechanical System (MEMS) demonstrates the effectiveness of the proposed model.

2

A queueing system with heterogeneous impatient customers and consumable additional items

Baek J., Dudina O., Kim C.

International Journal of Applied Mathematics and Computer Science

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2017

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Vol. 27, no. 2

367--384

EN

A single-server queueing system with a marked Markovian arrival process of heterogeneous customers is considered. Type-1 customers have limited preemptive priority over type-2 customers. There is an infinite buffer for type-2 customers and no buffer for type-1 customers. There is also a finite buffer (stock) for consumable additional items (semi-products, half-stocks, etc.) which arrive according to the Markovian arrival process. Service of a customer requires a fixed number of consumable additional items depending on the type of the customer. The service time has a phase-type distribution depending on the type of the customer. Customers in the buffer are impatient and may leave the system without service after an exponentially distributed amount of waiting time. Aiming to minimize the loss probability of type-1 customers and maximize throughput of the system, a threshold strategy of admission to service of type-2 customers is offered. Service of type-2 customer can start only if the server is idle and the number of consumable additional items in the stock exceeds the fixed threshold. Stationary distributions of the system states and the waiting time are computed. In the numerical example, we show some interesting effects and illustrate a possibility of application of the presented results for solution of optimization problems.

3

Analysis of an MMAP/PH1, PH2/N/∞ queueing system operating in a random environment

Kim C., Dudin A., Dudin S., Dudina O.

International Journal of Applied Mathematics and Computer Science

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2014

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Vol. 24, no. 3

485--501

EN

A multi-server queueing system with two types of customers and an infinite buffer operating in a random environment as a model of a contact center is investigated. The arrival flow of customers is described by a marked Markovian arrival process. Type 1 customers have a non-preemptive priority over type 2 customers and can leave the buffer due to a lack of service. The service times of different type customers have a phase-type distribution with different parameters. To facilitate the investigation of the system we use a generalized phase-type service time distribution. The criterion of ergodicity for a multi-dimensional Markov chain describing the behavior of the system and the algorithm for computation of its steady-state distribution are outlined. Some key performance measures are calculated. The Laplace–Stieltjes transforms of the sojourn and waiting time distributions of priority and non-priority customers are derived. A numerical example illustrating the importance of taking into account the correlation in the arrival process is presented.

4

Analysis of a multi-server queueing model with vacations and optional secondary services

Chakravarthy S. R.

Mathematica Applicanda

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2013

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Vol. 41, No. 2

145--169

EN

In this paper we study a multi-server queueing model in which the customer arrive according to a Markovian arrival process. The customers may require, with a certain probability, an optional secondary service upon completion of a primary service. The secondary services are offered (in batches of varying size) when any of the following conditions holds good: (a) upon completion of a service a free server finds no primary customer waiting in the queue and there is at least one secondary customer (including possibly the primary customer becoming a secondary customer) waiting for service; (b) upon completion of a primary service, the customer requires a secondary service and at that time the number of customers needing a secondary service hits a pre-determined threshold value; (c) a server returning from a vacation finds no primary customer but at least one secondary customer waiting. The servers take vacation when there are no customers (either primary or secondary) waiting to receive service. The model is studied as a QBD-process using matrix-analytic methods and some illustrative examples arediscussed.

PL

Ten artykuł poświęcony jest modelom kolejkowym dla systemów z wieloma serwerami z Markowskim strumieniem zgłoszeń. Klienci żądają, aby obsługa świadczyła również pewne opcjonalne usługi po zakończeniu podstawowego procesu. Te usługi dodatkowe (o różnym zakresie) mają być dostępne i oferowane z pewnym prawdopodobieństwem, gdy którykolwiek z następujących warunków jest spełniony: (a) po zakończeniu obsługi na darmowy, podstawowy, serwis nie czeka klient w kolejce i jest co najmniej jeden chętny klient na serwis wtórny (tym chętnym prawdopodobnie jest klientem, który właśnie otrzymał podstawową usługę), (b) po zakończeniu podstawowego serwisu, klient wymaga dodatkowego serwisu i w tym czasie liczba klientów, którzy reflektują na tę dodatkową usługę przekroczy wcześniej ustaloną wartość progową; (c) serwer który wznawia obsługę po przerwie nie ma klientów na podstawową usługę, ale przynajmniej jeden klient czeka na dodatkowy serwis. Serwery mogą zostać wyłączone na pewien czas, gdy nie ma klientów (podstawowych lub chętnych na serwis dodatkowy) czekających na obsługę. Model jest badane jako uogólniony proces urodzin i śmierci (quasi-birth-death-matrix-process) analizowany analitycznie. Podane są przykłady ilustrujące zastosowane podejście.

5

Probability of ruin for a dependent, two-dimensional Poisson process

Heilpern S.

Badania Operacyjne i Decyzje

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2009

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nr 1

77-90

EN

A two-dimensional, dependent Poisson risk process is investigated in the paper. Claims are divided into two classes. Within each class claims have the same distribution, but claims belonging to different classes can have different distributions and the corresponding counting processes can be dependent. This dependence is induced by a common factor. Three models of ruin and the probabilities of ruin are investigated. The influence of the degree of class dependence on the probability of ruin are studied for each model.

PL

W pracy rozpatrywany jest dwuwymiarowy, zależny proces ryzyka Poissona. Wielkości wypłat podzielono na dwie klasy. W każdej klasie wypłaty mają ten sam rozkład, natomiast wypłaty należące do różnych klas mogą mieć różne rozkłady, a procesy liczące wypłaty mogą być zależne. Zależność ta jest generowana przez wspólny czynnik. Rozpatrywane są trzy modele ruiny, oparte na różnych sposobach wyznaczania czasu ruiny: czas wystąpienia pierwszej ruiny, pierwszy moment wystąpienia ruiny w obydwu klasach oraz ruina dla sumy procesów. Badane jest prawdopodobieństwo wystąpienia ruiny oraz wpływ stopnia zależności klas na to prawdopodobieństwo. Rozpatrzono przykłady, w których wypłaty mają rozkłady wykładnicze. W dwóch pierwszych modelach prawdopodobieństwa ruiny zostały wyznaczone metodami symulacyjnymi. W trzecim modelu wykorzystano metodę opartą na rozkładach fazowych.

6

Shock models under policy N

Pérez-Ocón R., Montoro-Cazorla D., Segovia M. C.

Journal of Polish Safety and Reliability Association

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2008

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Vol. 2

295--298

EN

We present the life distribution of a device subject to shocks governed by phase-type distributions. The probability of failures after shock follows discrete phase-type distribution. Lifetimes between shocks are affected by the number of cumulated shocks and they follow continuous phase-type distributions. The device can support a maximum of N shocks. We calculate the distribution of the lifetime of the device and illustrate the calculations by means of a numerical application. Computational aspects are introduced. This model extends other previously considered in the literature.