Evaluation of full and degraded mission reliability and mission dependability for intermittently operated, multi-functional systems

Availability is one of the metrics often used in the evaluation of system effectiveness. Its use as an effectiveness metric is often dictated by the nature of the system under consideration. While some systems operate continuously, many others operate on an intermittent basis where each operational period may often involve a different set of missions. This is the most likely scenario for complex multi-functional systems, where each specific system mission may require the availability of a different combination of system elements. Similarly, for these systems, not only is it important to know whether a mission can be initiated, it is just as important to know whether the system is capable of completing such a mission. Thus, for these systems, additional measures become relevant to provide a more holistic assessment of system effectiveness. This paper presents techniques for the evaluation of both full and degraded mission reliability and mission dependability for coherent, intermittently operated multi-functional systems. These metrics complement previously developed availability and degraded availability measures of multi-functional systems, in the comprehensive assessment of system effectiveness.     

Reliability modeling of multi‐state degraded repairable systems and its applications to automotive systems

In this paper, we presented a continuous‐time Markov process‐based model for evaluating time‐dependent reliability indices of multi‐state degraded systems, particularly for some automotive subsystems and components subject to minimal repairs and negative repair effects. The minimal repair policy, which restores the system back to an “as bad as old” functioning state just before failure, is widely used for automotive systems repair because of its low cost of maintenance. The current study distinguishes with others that the negative repair effects, such as unpredictable human error during repair work and negative effects caused by propagated failures, are considered in the model. The negative repair effects may transfer the system to a degraded operational state that is worse than before due to an imperfect repair. Additionally, a special condition that a system under repair may be directly transferred to a complete failure state is also considered. Using the continuous‐time Markov process approach, we obtained the general solutions to the time‐dependent probabilities of each system state. Moreover, we also provided the expressions for several reliability measures include availability, unavailability, reliability, mean life time, and mean time to first failure. An illustrative numerical example of reliability assessment of an electric car battery system is provided. Finally, we use the proposed multi‐state system model to model a vehicle sub‐frame fatigue degradation process. The proposed model can be applied for many practical systems, especially for the systems that are designed with finite service life.     

巨型框架多功能减振结构的有限元计算方法

巨型框架多功能减振结构的结构复杂、规模庞大,并且它是由具有不同阻尼特性的材料组成的。因此,采用有限元方法进行计算时面临着一系列问题需要解决。针对巨型框架多功能减振结构的受力特性,给出了巨型框架多功能减振结构的三维简化计算模型,大大缩减了计算自由度。由于隔震橡胶垫的变形主要是水平剪切变形,因此,将隔震橡胶垫看做具有阻尼特性的三维弹性或弹塑性铰,并提出了隔震橡胶垫单元的三维单元模型。由于巨型框架多功能减振结构的非经典阻尼特性,可以采用子结构技术对巨型框架多功能减振结构进行有限元建模、计算。     

Availability consideration in the optimal selection of multiple-aspect RMS configurations

Machine availability has a profound influence on the performance of manufacturing systems. This paper extends a model for optimizing reconfigurable manufacturing systems (RMS) configurations with multiple-aspects to incorporate the effect of machine availability using the universal generating function (UGF). Two powerful meta-heuristic optimization techniques, namely genetic algorithms (GAs) and tabu search (TS), are used for optimizing the capital cost and system availability of the RMS configurations. The optimized configurations can handle multiple-parts and their structure is that of flow lines allowing paralleling of identical machines in each production stage. The various aspects considered in the RMS configurations include arrangement of machines, equipment selection and assignment of operations. A case study is presented and implementation of the optimization model is carried out using MATLAB software. The results of using both GAs and TS to solve the problem are then reported and compared for validation. Analysis of different cases of availability consideration including infinite and no buffer capacity is performed and results are compared to those obtained when machine availability is not considered. It has been shown that considering availability affects the optimal configuration selection and increases the required equipment. This increases the costs of the near-optimal configurations obtained especially in the case without buffers. The presented model can support the manufacturing systems configuration selection decisions at both the initial design and reconfiguration stages.     

A study of availability-centered preventive maintenance for multi-component systems

This paper studies preventive maintenance (PM) in simultaneously considering three actions, mechanical service, repair and replacement for a multi-components system based on availability. Mechanical service denotes the activities including lubricating, cleaning, checking and adjusting, etc. which is set to alleviate strength degradation. Repair is defined on that not only slow down the degraded velocity but also restore the degraded strength partly. Replacement is settled to recover a component to its original condition. According to the definitions, the degradation of components is analyzed from its failure mechanisms and the improvements of various actions to it in reliability were measured by using two improved factors. Following the proposed model of reliability, the mean-up and mean-down times of each component are also investigated and the replacement intervals of components are determined based on availability maximization. Here, the minimum one among the intervals is chosen as the PM interval of system for programming the periodical PM policy. The selection of action for the components on every PM stage is decided by maximizing system benefit in maintenance. Repeatedly, the scheduling is progressed step by step and is terminated until the system extended life reaching to its expected life. The complete schedule provides the information, the actions adopted for the components, the availability and the total cost of system on each stage. Validly, a multi-components system is used as an example to describe the proposed algorithm.     

A model based approach to assess the performance of production systems in degraded mode

Nowadays production systems are asked to perform their activities in a high uncertainty environment and to guarantee their performance in this environment. Therefore, they are asked to master risks that are part of their daily activities, to maintain the performance which is considered as their key success factor. Risks may cause serious effects that threaten the production systems and degrade their performance. Nevertheless, we cannot estimate the degradation that a risk may cause to system performance, since risk analysis methods found in the literature do not allow simulating the behaviour of the system in degraded mode. In order to help production systems to assess their performance in risk situations, we propose in this paper a model-based approach that enables assessing the performance of production systems in degraded mode. Our approach is based on function, interaction, structure (FIS) modelling framework that enables modelling complex system and its failures. The resulting model is converted into an executable simulation model based on a new class of Petri Nets (PNs) called predicate-transition, prioritised, synchronous (PTPS) PN. The obtained simulation model is then executed in order to obtain performance indicators in degraded mode. This tool is used during the system design, in order to study the impact of risks on the designed production system performance. It is also used to study an existing production system in order to analyse and optimise its behaviour in degraded mode. In this article, we present our tool and apply it to a special case of production systems which is a hospital sterilisation system.     

Computer systems availability evaluation using a segregated failures model

This paper presents the segregated failures model (SFM) of availability of fault‐tolerant computer systems with several recovery procedures. This model is compared with a Markov chain model and its advantages are explained. The basic model is then extended for the situation when the coverage factor is unknown and the failure escalation rates must be used instead. A simple practical analytical approach to availability evaluation is provided and illustrated in detail by estimating the availability of two versions of a reliable clustered computing architecture. For these examples, numeric values of availability indexes are computed and the contribution of each recovery procedure to total system availability is analysed. Copyright © 2008 John Wiley & Sons, Ltd.     

Multifunctional nanoparticles, nanocages and degradable polymers as a potential novel generation of non-invasive molecular and cellular imaging systems

In recent years, polymeric scaffolds have been used in several biomedical applications for delivery of drugs or other biologically relevant molecules. Polymeric nanostructures display different (and in some cases more powerful) properties respect to bulk materials. This, lead academic researchers and industry to cooperate in developing pioneering nanostructured materials for industrial and biomedical applications. Moreover, the preparation and use of systems with multiple (multifunctional) properties (i.e., bioconjugation with superparamagnetic, fluorescent or targeting molecules) is positioned to become a viable and innovative tool for application in several clinical fields. Other nanostructured systems like nanocages and degradable nanoparticles, are emerging as potential innovative systems that could be exploited as multifunctional delivery vectors. This brief critical review is aimed at collecting and discussing some recent patents dealing with the preparation and use of multifunctional nanoparticles, nanocages and degradable nanoparticles in biomedicine and non-invasive bioimaging applications. Perspectives for a potential use of these multifunctional nanosystems in pediatries have been also discussed.     

Availability of Maintained Systems: A State-of-the-Art Survey

Availability appears to be a more appropriate measure than reliability for measuring the effectiveness of maintained systems because it includes reliability as well as maintainability. This paper is a survey and a systematic classification of the literature relevant to availability. Emphasis in this paper is centered on the current state of the art on a variety of topics related to availability. Among the topics discussed are: the definition and concepts of the availability; the probability density functions (pdf) of failure times, the pdf of repair times, system configurations, and the various approaches employed to obtain the availability models; confidence intervals of availability; effect of preventive maintenance policies on availability; availability parameters in the model; and systems optimization.     

Availability and mean life time prediction of multistage degraded system with partial repairs

In some environments, components might not always fail fully, but can degrade, and there can be multiple stages of degradation. In such cases, the efficiency of the system may decrease. After a certain stage of degradation the efficiency of the system may decrease to an unacceptable limit and can be considered as a total failure. However, the system can fail randomly from any stage. and can be repaired. Further, the repair action cannot bring the system to the good stage, but can make it operational and the failure rate of the system will, therefore, remain the same as before the failure. In this study, we present a model for predicting the reliability, availability, mean life time, and mean time to first failure of multistage degraded systems with partial repairs. In the analysis, state dependent transition rates for the degradation process, as well as repair processes, are considered. A numerical example is provided to illustrate the results.     

可溶性聚醚醚酮对复合环氧/DDM的改性

热熔法制备了可溶性聚醚醚酮（s-PEEK）/E-51/多官能度环氧树脂复合体系,测试了体系的冲击强度、高温拉伸剪切强度和玻璃化温度,用扫描电镜（SEM）观察体系的微观结构,并与聚醚醚酮（PEEK）改性进行对比。结果表明,复合环氧体系加入两种聚醚醚酮后冲击强度下降,但含量为5g时出现较大值;体系的玻璃化温度随着s-PEE...     

Monte Carlo-based assessment of system availability. A case study for cogeneration plants

The complexity of the modern engineering systems besides the need for realistic considerations when modeling their availability and reliability render analytic methods very difficult to be used. Simulation methods, such as the Monte Carlo technique, which allow modeling the behavior of complex systems under realistic time-dependent operational conditions, are suitable tools to approach this problem.The scope of this paper is, in the first place, to show the opportunity for using Monte Carlo simulation as an approach to carry out complex systems' availability/reliability assessment. In the second place, the paper proposes a general approach to complex systems availability/reliability assessment, which integrates the use of continuous time Monte Carlo simulation. Finally, this approach is exemplified and somehow validated by presenting the resolution of a case study consisting of an availability assessment for two alternative configurations of a cogeneration plant.In the case study, a certain random and discrete event will be generated in a computer model in order to create a realistic lifetime scenario of the plant, and results of the simulation of the plant's life cycle will be produced. After that, there is an estimation of the main performance measures by treating results as a series of real experiments and by using statistical inference to reach reasonable confidence intervals. The benefits of the different plant configurations are compared and discussed using the model, according to their fulfillment of the initial availability requirements for the plant.     

Analysis of a two-level software rejuvenation policy

A two-level rejuvenation policy for software systems with degradation process is studied. Both full restarts and partial restarts are considered in this rejuvenation strategy. A semi-Markov process model is constructed, and based on its closed-form solution we obtain the system availability as a bivariate function. Then, the rejuvenation policy is analyzed to maximize the system availability. Several different scenarios of software rejuvenation strategy are demonstrated by numerical examples.     

In situ electrokinetic enhancement for self-assembled-monolayer-based electrochemical biosensing

This study reports a multifunctional electrode approach which directly implements electrokinetic enhancement on a self-assembled-monolayer-based electrochemical sensor for point-of-care diagnostics. Using urinary tract infections as a model system, we demonstrate that electrokinetic enhancement, which involves in situ stirring and heating, can enhance the sensitivity of the strain specific 16S rRNA hybridization assay for 1 order of magnitude and accelerate the time-limiting incubation step with a 6-fold reduction in the incubation time. Since the same electrode platform is used for both electrochemical signal enhancement and electrochemical sensing, the multifunctional electrode approach provides a highly effective strategy toward fully integrated lab-on-a-chip systems for various biomedical applications.     

Uncertain process–based reliability and maintenance modeling for systems under mutually dependent degradation and shock processes

For the systems that experience competing failure processes, an uncertain process–based degradation model is developed to describe the systems. The competing degradation process is composed of internal continuous degradation and external shocks, and the mutual dependence between them is considered. When the magnitude of the internal degradation exceeds the threshold, the soft failure occurs. While for the shock processes involving the randomness and the subjective information, we adopt the uncertain random renewal reward process to characterize it. Hard failure occurs when the damage of the shock process exceeds the strength threshold of the system. By using the belief reliability metric, the reliability of the degraded system is defined as the chance measure that neither soft failure nor hard failure occurs. And the effect of the degradation-shock dependence on the system reliability is performed by the parametric studies. Then the proposed degradation model is introduced into the preventive maintenance strategy to minimize the average maintenance cost. Using the microelectromechanical systems as an example, the effectiveness of the constructed degradation model and maintenance strategy is illustrated, and the proposed model can characterize the system degradation process in a superior way to the stochastic process model. These methods can be applied to other similar degraded systems and provide support for maintenance decisions.     

磁性水凝胶作为药物载体的应用研究进展

磁性水凝胶是一类同时具有磁性材料、高分子材料及水凝胶的性质特点的无机/有机复合材料。因具有优良的磁学性能及生物相容性,其作为新一代的药物载体可以实现磁响应、磁靶向及磁热疗等功能,在药物控制释放领域具有广阔的应用前景。对磁性水凝胶的制备方法及其在药物载体领域的研究情况进行了综述,详细介绍了磁性水凝胶作为药物载体的两种药物释放机理(ON/OFF模型及热敏释放原理),及其在磁靶向药物控释、磁热疗和磁共振成像方面的应用研究现状。     

Integration of process simulations in availability studies

The aim of this paper is to describe a method to integrate the results of process simulations in availability studies. It is shown that this can be achieved if two conditions are met: firstly, close co-operation between process experts and reliability engineers and secondly, a flexible modelling tool. Principles of the modelling method, the interpreted stochastic Petri nets, are provided. The way to use them to model plant availability is described, together with a computer code enabling calculations to be made. The aim of the plant availability study and how results of process simulations were integrated in the Petri net model is then explained. Results are discussed and conclusions given on the ability of interpreted stochastic Petri nets to model complex systems.     

论述数据中心电力系统的可用性

数据中心最关键的两个环节是电力和制冷。电力系统的可用性日益成为数据中心等级区分的一个关键指标。本文试图分析数据中心的几种典型电力系统配置,从理论方面剖析系统可靠性计算,为广大数据中心从业者提供帮助。     

Dynamic behavioural model for assessing impact of regeneration actions on system availability: Application to weapon systems

Mastering system availability all along the system life cycle is now a critical issue with regards to systems engineering. It is more true for military systems which operate in a battle context. Indeed as they must act in a hostile environment, they can become unavailable due to failures of or damage to the system. In both cases, system regeneration is required to restore its availability. Many approaches based on system modelling have been developed to assess availability. However, very few of them take battlefield damage into account and relevant methods for the model development are missing. In this paper, a modelling method for architecture of weapon system of systems that supports regeneration engineering is proposed. On the one hand, this method relies on a unified failure/damage approach to extend acknowledged availability models. It allows to integrate failures, damages, as well as the possibility of regeneration, into operational availability assessment. Architectures are modelled as a set of operational functions, supported by components that belong to platform (system). Modelling atoms (i.e. elementary units of modelling) for both the architecture components and functions are defined, based on state-space formalism. Monte Carlo method is used to estimate availability through simulation. Availability of the architecture is defined on the basis of the possible states of the required functions for a mission. The states of a function directly depend on the state of the corresponding components (i.e. the components that support the function). Aggregation rules define the state of the function knowing the states of each component. Aggregation is defined by means of combinatorial equations of the component states. The modelling approach is supported by means of stochastic activity network for the models simulation. Results are analysed in terms of graphs of availability for mission's days. Thus, given the simulation results, it is possible to plan combat missions based on criteria such as the number of platforms to be involved given functions required for the mission or the mean of regeneration to be deployed given the possible threats. Further, the simulation will help towards the design of improved architecture of system of systems which could focus on the factors affecting the availability.     

Packaging handling evaluation methods in the grocery retail industry

The grocery retail industry, with its large product volumes, low margins and fierce competition, is constantly seeking efficiency improvements in its supply chain. The grocery retail industry uses an immense amount of packaging and is directly affected by packaging logistics activities. There is, therefore, a potential for efficiency improvements in the grocery retail supply chain through the integration and development of new systems of packaging and logistics. Packaging handling is identified as one of the main activities that has a strong impact on the overall logistical cost of a grocery chain. This research article investigates packaging handling evaluation methods and discusses how these are employed to benefit the industry. Case studies, involving six major companies from the Swedish grocery retail industry, have been used to evaluate packaging and logistics activities. This work, together with a literature review, was used to identify the need for evaluative methods and the present availability of such methods. The results indicated a lack of sufficient and usable packaging handling evaluation methods in today's grocery and packaging industry especially from a logistical point of view. The paper also highlights the lack of systematization among the few methods used and discusses how these can be used to build a systematic and multifunctional evaluation model in order to utilize the information from different studies to build a knowledge base for the future. Copyright © 2001 John Wiley & Sons, Ltd.