Total cumulative work until failure of a system modelled by a finite semi-Markov process

Let Y = (Y_t , t ≥ 0) be a semi-Markov reliability model of a system whose finite state space S is partitioned as S = W ∪ R ∪ F, where W, R and F stand for the sets of working, repair, and failed system states respectively. The system characteristic considered in this paper is the cumulative operational time until failure, C, defined as the time spent by Y in the set of working states W until failure, i.e. until absorption into F. A method is described here for the computation of the cumulative distribution function of C. It is based on approximating the continuous-time model by a discrete-parameter semi-Markov process for which the cumulative distribution function of the discrete-time counterpart of C can be computed by a recurrence relation. The reliability model of a two-unit parallel system with sequential preventive maintenance is examined numerically by the present method and a comparison is made with results from simulation.     

Real-time reliability prediction for dynamic systems with both deteriorating and unreliable components

As an important technology for predictive maintenance, failure prognosis has attracted more and more attentions in recent years. Real-time reliability prediction is one effective solution to failure prognosis. Considering a dynamic system that is composed of normal, deteriorating and unreliable components, this paper proposes an integrated approach to perform real-time reliability prediction for such a class of systems. For a deteriorating component, the degradation is modeled by a time-varying fault process which is a linear or approximately linear function of time. The behavior of an unreliable component is described by a random variable which has two possible values corresponding to the operating and malfunction conditions of this component. The whole proposed approach contains three algorithms. A modified interacting multiple model particle filter is adopted to estimate the dynamic system’s state variables and the unmeasurable time-varying fault. An exponential smoothing algorithm named the Holt’s method is used to predict the fault process. In the end, the system’s reliability is predicted in real time by use of the Monte Carlo strategy. The proposed approach can effectively predict the impending failure of a dynamic system, which is verified by computer simulations based on a three-vessel water tank system.     

Simultaneous control of maintenance and production rates of a manufacturing system with defective products

In the past three decades, studies of simultaneous maintenance and production planning have been focusing on age-dependent machine failure and inventory. This paper presents the interaction between defective products and optimal control of production rate, lead time and inventory. Our aim is to minimize the expected discounted overall cost due to maintenance activities, inventory holding and backlogs. Through Condition-Based Maintenance, we monitor in a real time the manufacturing system’s health by describing N operational states. We consider two maintenance states of a machine controlled by two decision variables: production and maintenance rates. The optimal policy is characterized by the dynamic programming solution to a piecewise deterministic optimal control problem. A numerical illustration and a sensitive analysis are developed with a set of parameters calibrated on an existing manufacturing system.     

Periodic and sequential preventive maintenance policies over a finite planning horizon with a dynamic failure law

The purpose of this study is to propose and model periodic and sequential preventive maintenance policies for a system that performs various missions over a finite planning horizon. Each mission can have different characteristics that depend on operational and environmental conditions. These proposed preventive maintenance policies are defined and modeled mathematically. The study of these two policies is based on a dynamic system failure law that takes into account the different missions performed. The first step is to determine the optimal business plan to achieve, i.e. the set of missions to perform in order to maximize the profit of missions minus maintenance costs. Thus, for each plan, we determine the maintenance planning considering two policies. The first preventive maintenance policy is periodic and the objective is to determine the optimal number of preventive maintenance to achieve. For the second policy, namely sequential, we calculate the optimal number of preventive maintenance intervals and the duration of these different intervals.     

An interleaving crescent broadcasting protocol for near video-on-demand services

This work presents a novel interleaving crescent broadcasting protocol for near video-on-demand service. The interleaving crescent broadcasting protocol is a trade-off among the subscriber’s access latency, maximum buffer requirement, needed subscriber’s bandwidth, and maximum disk I/O transfer rate. A longer subscriber’s access latency may cause a subscriber to leave. A lower maximum buffer requirement, a lower needed subscriber’s bandwidth, and a lower maximum disk I/O transfer rate reduce subscribers’ costs. The interleaving crescent broadcasting protocol not only makes access latency shorter, but also lowers the overall system’s cost. We prove the correctness of the interleaving crescent protocol; provide mathematical analyses to demonstrate its efficiency.     

Analysis of maintenance policies for finite life-cycle multi-state systems

Maintenance policies for multi-state systems (MSS) are often analyzed under infinite horizon assumptions. In practice, it is important to consider maintenance policies under a finite horizon because the life cycles of most systems are finite. In this paper, we consider a finite life-cycle MSS that is subject to both degradation and Poisson failures. We study two classes of maintenance policies – preventive replacements and corrective replacements, and their effectiveness in controlling the customer’s expected discounted maintenance cost (EDMC). For both policies, replacement decisions are modelled via two control parameters – a threshold on the current system state and a threshold on the residual life cycle, which is measured as the time span from present to the end of life cycle. We derive close-to-explicit forms of the cost models under each of the policy. Methodologies for optimizing the maintenance thresholds are further proposed. Computational results verify that preventive replacements outperform corrective replacements typically when the downtime cost per failure is relatively high compared to the repair cost.     

A concrete realization of the Hoare powerdomain

The lattice of non-empty Scott-closed subsets of a domain D is called the Hoare powerdomain of D. The Hoare powerdomain is used in programming semantics as a model for angelic nondeterminism. In this paper, we show that the Hoare powerdomain of any domain can be realized as the lattice of full subinformation systems of the domain’s corresponding information system as well as the lattice of non-empty down-sets of the system’s consistency predicate.     

Analysis of maintenance policies for finite life-cycle multi-state systems

Maintenance policies for multi-state systems (MSS) are often analyzed under infinite horizon assumptions. In practice, it is important to consider maintenance policies under a finite horizon because the life cycles of most systems are finite. In this paper, we consider a finite life-cycle MSS that is subject to both degradation and Poisson failures. We study two classes of maintenance policies – preventive replacements and corrective replacements, and their effectiveness in controlling the customer’s expected discounted maintenance cost (EDMC). For both policies, replacement decisions are modelled via two control parameters – a threshold on the current system state and a threshold on the residual life cycle, which is measured as the time span from present to the end of life cycle. We derive close-to-explicit forms of the cost models under each of the policy. Methodologies for optimizing the maintenance thresholds are further proposed. Computational results verify that preventive replacements outperform corrective replacements typically when the downtime cost per failure is relatively high compared to the repair cost.     

Adaptation and user expertise modelling in AthosMail

This article describes the User Model component of AthosMail, a speech-based interactive e-mail application developed in the context of the EU project DUMAS. The focus is on the system’s adaptive capabilities and user expertise modelling, exemplified through the User Model parameters dealing with initiative and explicitness of the system responses. The purpose of the conducted research was to investigate how the users could interact with a system in a more natural way, and the two aspects that mainly influence the system’s interaction capabilities, and thus the naturalness of the dialogue as a whole, are considered to be the dialogue control and the amount of information provided to the user. The User Model produces recommendations of the system’s appropriate reaction depending on the user’s observed competence level, monitored and computed on the basis of the user’s interaction with the system. The article also discusses methods for the evaluation of adaptive user models and presents results from the AthosMail evaluation.The research was done while the author was affiliated with the University of Art and Design Helsinki as the scientific coordinator of the DUMAS project.     

Making it easier for older people to talk to smart homes: the effect of early help prompts

It is well known that help prompts shape how users talk to spoken dialogue systems. This study investigated the effect of help prompt placement on older users’ interaction with a smart home interface. In the dynamic help condition, help was only given in response to system errors; in the inherent help condition, it was also given at the start of each task. Fifteen older and sixteen younger users interacted with a smart home system using two different scenarios. Each scenario consisted of several tasks. The linguistic style users employed to communicate with the system (interaction style) was measured using the ratio of commands to the overall utterance length (keyword ratio) and the percentage of content words in the user’s utterance that could be understood by the system (shared vocabulary). While the timing of help prompts did not affect the interaction style of younger users, it was early task-specific help supported older users in adapting their interaction style to the system’s capabilities. Well-placed help prompts can significantly increase the usability of spoken dialogue systems for older people.     

Two-phase queuing system with a threshold strategy of retrial calls

A two-phase queuing system (QS) has been considered; its first phase is represented by a single-linear system with retrial calls, and the second phase is represented by a multilinear (multiple) unbuffered QS. Queries arrive to the system in the group Markov flow. The system has two operational modes that differ by the strategy of the retrial attempts. Depending on the number of retrial calls, either a decentralized or centralized strategy of retrials is used. A stationary distribution of the system’s state probabilities at the embedded epochs and arbitrary time moments has been found, and formulae for the main characteristics of the system’s productivity have been obtained. Numerical examples are presented.     

Organisational adaptation of multi-agent systems in a peer-to-peer scenario

Organisations in multi-agent systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents’ behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system’s purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents’ relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system’s adaptation is lower than its benefits.     

Optimal maintenance policy incorporating system level and unit level for mechanical systems

The study works on a multi-level maintenance policy combining system level and unit level under soft and hard failure modes. The system experiences system-level preventive maintenance (SLPM) when the conditional reliability of entire system exceeds SLPM threshold, and also undergoes a two-level maintenance for each single unit, which is initiated when a single unit exceeds its preventive maintenance (PM) threshold, and the other is performed simultaneously the moment when any unit is going for maintenance. The units experience both periodic inspections and aperiodic inspections provided by failures of hard-type units. To model the practical situations, two types of economic dependence have been taken into account, which are set-up cost dependence and maintenance expertise dependence due to the same technology and tool/equipment can be utilised. The optimisation problem is formulated and solved in a semi-Markov decision process framework. The objective is to find the optimal system-level threshold and unit-level thresholds by minimising the long-run expected average cost per unit time. A formula for the mean residual life is derived for the proposed multi-level maintenance policy. The method is illustrated by a real case study of feed subsystem from a boring machine, and a comparison with other policies demonstrates the effectiveness of our approach.     

Optimal imperfect preventive maintenance policies for a used system

In some practical situations, it may be more economical to work a used system than do a new one. From this viewpoint, this article considers three basic preventive maintenance (PM) policies for a used system: the system with initial variable damage Y ₀ begins to operate at time 0, and suffers damage due to shocks. It fails when the total damage exceeds a failure level K and corrective maintenance is made immediately. To prevent such failure, it undergoes PM at a planned time T, a shock number N and a damage level k, but maintenances are imperfect. However, failure rate of a used system maybe higher than that of a new one, so some maintenance is applied to the policies at each shock in the extended models. Using the theory of cumulative processes, expected cost rate models are obtained, optimal policies which minimise them are derived analytically and discussed numerically.     

Statistical economic feasibility estimates of the Russian CMTPL automobile insurance system as a reliability theory problem

We show a method of representing basic economic characteristics of the functioning of the Russian Compulsory Motor Third Party Liability (CMTPL) system as a reliability theory system of a special kind with independent components. Each component is characterized by the number of faults (i.e., the number of road traffic accidents), its damage level (i.e., the amount of damage inflicted on third parties), and the initial endurance characteristic (i.e., the insurance premium). We mainly deal with statistical methods of graphical and analytic computerized methods for analyzing the system’s operation and further recommendations on keeping the system operational.     

Dynamic simulation of a contact-enhanced MEMS inertial switch in Simulink?

A novel contact-enhanced design of MEMS (micro-electro-mechanical system) inertial switch was proposed and modeled in Simulink^?. The contact effect is improved by an easily realized modification on the traditional design, i.e. introducing a movable contact point between the movable electrode (proof mass) and the stationary electrode, therefore forming a dual mass-spring system. The focus of this paper is limited to a vertically driven unidirectional one for the purposes of demonstration, but this design concept and Simulink^? model is universal for various kinds of inertial micro-switches. The dynamic simulation confirmed the contact-enhancing mechanism, showing that the switch-on time can be prolonged for the dynamic shock acceleration and the bouncing effect can be reduced for the quasi-static acceleration. The threshold acceleration of the inertial switch is determined by the proof mass-spring system’s natural frequency. Since the inertial switches were fabricated by the multilayer electroplating technology, the proof mass thickness were assigned two values, 100 and 50 μm, in order to get threshold levels of 56 and 133 g respectively for the dynamic acceleration of half-sine wave with 1 ms duration. Other factors that influence the dynamic response, such as the squeeze film damping and the contact point-spring system’s natural frequency were also discussed. The fabricated devices were characterized by the drop hammer experiment, and the results were in agreement with the simulation predictions. The switch-on time was prolonged to over 50 μs from the traditional design’s 10 μs, and could reach as long as 120 μs. Finally, alternative device configurations of the contact-enhancing mechanism were presented, including a laterally driven bidirectional inertial switch and a multidirectional one.     

An integrated strategy for efficient business plan and maintenance plan for systems with a dynamic failure distribution

The purpose of this study is to propose an integrated strategy to determine jointly efficient business and maintenance plans. The studied system is subject to random failures with a dynamic failure law. It must perform a set of missions (among M possible missions) over a finite planning horizon. Each mission may have different characteristics that depend on operational and environmental conditions. The determination of a business plan consists in choosing and scheduling the missions to be performed. To maximize the net profit (profits generated by the achievement of missions minus maintenance costs), two meta-heuristics based on genetic algorithms are developed. The first genetic algorithm is used to determine the business plan and the second one generates an efficient maintenance plan. Two maintenance policies are studied: a minimalist policy which involves only corrective maintenance actions and another policy, called sequential, which involves several imperfect preventive maintenance activities performed at predetermined times. Two cases are studied for the latter strategy. The first one considers the maintenance effectiveness factor as being the same for all preventive maintenance actions and we search for the best factor. In the second case, we consider maintenance actions with different efficiency factors and we look for the optimal value of each factor. Finally, a numerical example illustrates the proposed approach and the difference between the maintenance policies.     

Timing predictability of cache replacement policies

Hard real-time systems must obey strict timing constraints. Therefore, one needs to derive guarantees on the worst-case execution times of a system’s tasks. In this context, predictable behavior of system components is crucial for the derivation of tight and thus useful bounds. This paper presents results about the predictability of common cache replacement policies. To this end, we introduce three metrics, evict, fill, and mls that capture aspects of cache-state predictability. A thorough analysis of the LRU, FIFO, MRU, and PLRU policies yields the respective values under these metrics. To the best of our knowledge, this work presents the first quantitative, analytical results for the predictability of replacement policies. Our results support empirical evidence in static cache analysis.

Joint quality control and preventive maintenance strategy for imperfect production processes

In this paper, we develop a joint quality control and preventive maintenance policy for a production system producing conforming and nonconforming units. The considered system consists of one machine which must supply another production line operating on a just-in-time basis. Each lot produced by the machine is subject to a quality control. According to the proportion l of nonconforming units observed and compared to a threshold value l _m , one decides to undertake or not maintenance actions on the system. In order to palliate perturbations caused by the stopping of the machine for preventive and corrective maintenance actions of random durations, a buffer stock h is built up to ensure the continuous supply of the subsequent production line. The proposed strategy is modelled using simulation and experimental design. This approach allows to generate a second order response surface allowing to easily determine the optimal rate, l_m^*{l_{m}^*}, of nonconforming units on the basis of which preventive maintenance actions should be performed, and the optimal size, h*, of the buffer stock to be built. These values minimize the total cost per time unit which includes the costs related to maintenance, quality and inventory.     

Studying high reliability systems in the probabilistic school of B. V. Gnedenko

We give a survey of the works of B.V. Gnedenko’s reliability school, starting from 1950s and up until the latest years in two directions: (1) invariance of state distributions for queueing systems and networks, (2) asymptotic behavior of a redundant system’s characteristics under low load.