Reliability and Condition-Based Maintenance Analysis of Deteriorating Systems Subject to Generalized Mixed Shock Model

For successful commercialization of evolving devices (e.g., micro-electro-mechanical systems, and biomedical devices), there must be new research focusing on reliability models and analysis tools that can assist manufacturing and maintenance of these devices. These advanced systems may experience multiple failure processes that compete against each other. Two major failure processes are identified to be deteriorating or degradation processes (e.g., wear, fatigue, erosion, corrosion) and random shocks. When these failure processes are dependent, it is a challenging problem to predict reliability of complex systems. This research aims to develop reliability models by exploring new aspects of dependency between competing risks of degradation-based and shock-based failure considering a generalized mixed shock model, and to develop new and effective condition-based maintenance policies based on the developed reliability models. In this research, different aspects of dependency are explored to accurately estimate the reliability of complex systems. When the degradation rate is accelerated as a result of withstanding a particular shock pattern, we develop reliability models with a changing degradation rate for four different shock patterns. When the hard failure threshold reduces due to changes in degradation, we investigate reliability models considering the dependence of the hard failure threshold on the degradation level for two different scenarios. More generally, when the degradation rate and the hard failure threshold can simultaneously transition multiple times, we propose a rich reliability model for a new generalized mixed shock model that is a combination of extreme shock model, δ-shock model and run shock model. This general assumption reflects complex behaviors associated with modern systems and structures that experience multiple sources of external shocks. Based on the developed reliability models, we introduce new condition-based maintenance strategies by including various maintenance actions (e.g., corrective replacement, preventive replacement, and imperfect repair) to minimize the expected long-run average maintenance cost rate. The decisions for maintenance actions are made based on the health condition of systems that can be observed through periodic inspection. The reliability and maintenance models developed in this research can provide timely and effective tools for decision-makers in manufacturing to economically optimize operational decisions for improving reliability, quality and productivity.Industrial Engineering, Department o

Optimization of replacement policy for a one-component system subject to Poisson shocks

In reliability engineering, system failures may occur due to intrinsic or extrinsic factors. For example, drinking water systems may fail due to ageing and deterioration (i.e., intrinsic factors) or flooding (i.e., extrinsic factors). An interesting question is: for such systems, how should preventive maintenance be scheduled? This paper investigates this question. The paper develops a maintenance policy for repairable systems subject to extrinsic shocks. It assumes that a system may fail due to either intrinsic factors or extrinsic factors. Reliability indexes and the expected long run cost rate are then derived. A numerical example is given to illustrate the theoretical results

A complex multi-state k-out-of-n: G system with preventive maintenance and loss of units

In this study, a multi-state k-out-of-n: G system subject to multiple events is modeled through a Markovian Arrival Process with marked arrivals. The system is composed initially of n units and is active when at least k units are operational. Each unit is multi-state, each of which is classified as minor or major according to the level of degradation presented. Each operational unit may undergo internal repairable or non-repairable failures, external shocks and/or random inspections. An external shock can provoke extreme failure, while cumulative external damage can deteriorate internal performance. This situation can produce repairable and non-repairable failures. When a repairable failure occurs the unit is sent to a repair facility for corrective repair. If the failure is non-repairable, the unit is removed. When the system has insufficient units with which to operate, it is restarted. Preventive maintenance is employed in response to random inspection. The system is modeled in an algorithmic and computational form. Several interesting measures of performance are considered. Costs and rewards are included in the system. All measures are obtained for transient and stationary regimes. A numerical example is analyzed to determine whether preventive maintenance is profitable, financially and in terms of performance.Junta de Andalucía (Spain) FQM-307Ministerio de Economía y Competitividad (España) MTM2017-88708-PEuropean Regional Development Fund (ERDF

Integrating Random Shocks Into Multi-State Physics Models of Degradation Processes for Component Reliability Assessment

International audienceWe extend a multi-state physics model (MSPM) framework for component reliability assessment by including semi-Markov and random shock processes. Two mutually ex-clusive types of random shocks are considered: extreme, and cumulative. Extreme shocks lead the component to immediate failure, whereas cumulative shocks simply affect the component degradation rates. General dependences between the degradation and the two types of random shocks are considered. A Monte Carlo simulation algorithm is implemented to compute component state probabilities. An illustrative example is presented, and a sensitivity analysis is conducted on the model parameters. The results show that our extended model is able to characterize the influences of different types of random shocks onto the component state probabilities and the reliability estimates

Rapid gravity filtration operational performance assessment and diagnosis for preventative maintenance from on-line data

Rapid gravity filters, the final particulate barrier in many water treatment systems, are typically monitored using on-line turbidity, flow and head loss instrumentation. Current metrics for assessing filtration performance from on-line turbidity data were critically assessed and observed not to effectively and consistently summarise the important properties of a turbidity distribution and the associated water quality risk. In the absence of a consistent risk function for turbidity in treated water, using on-line turbidity as an indicative rather than a quantitative variable appears to be more practical. Best practice suggests that filtered water turbidity should be maintained below 0.1 NTU, at higher turbidity we can be less confident of an effective particle and pathogen barrier. Based on this simple distinction filtration performance has been described in terms of reliability and resilience by characterising the likelihood, frequency and duration of turbidity spikes greater than 0.1 NTU. This view of filtration performance is then used to frame operational diagnosis of unsatisfactory performance in terms of a machine learning classification problem. Through calculation of operationally relevant predictor variables and application of the Classification and Regression Tree (CART) algorithm the conditions associated with the greatest risk of poor filtration performance can be effectively modelled and communicated in operational terms. This provides a method for an evidence based decision support which can be used to efficiently manage individual pathogen barriers in a multi-barrier system

Financial stability challenges in EU candidate countries - Financial systems in the aftermath of the global crisis

This paper reviews financial stability challenges in the EU candidate countries: Croatia, the former Yugoslav Republic of Macedonia and Turkey. It follows a macro-prudential approach, emphasising systemic risks and the stability of financial systems as a whole. The paper recalls that the economies of all three countries experienced a recession in 2008-09 and shows how this slowed the rapid process of financial deepening that had been taking place since the beginning of the last decade. The deteriorating economic and financial conditions manifested themselves, first and foremost, through a marked deterioration in asset quality. These direct credit risks were compounded by the transformation of exchange and interest rate risks through a widespread use of foreign exchange-denominated or indexed loans and variable or adjustable interest rate loans. Moreover, funding and liquidity risks also materialised to some extent, although fully fledged bank runs were avoided, and none of the countries experienced a sharp reversal in external financing. Overall, the deterioration in asset quality has so far been managed well by the banking systems of the candidate countries, facilitated by large capital buffers, pro-active macro-prudential policies pursued by the authorities both before and during the crisis and the relative stability of exchange rates. Looking ahead, although uncertainties remain high regarding credit quality, the shock-absorbing capacities of the banking systems are fairly robust, as also evidenced by their relative resilience so far. Nevertheless, as the economic recovery sets in, the central banks should return to and possibly reinforce the implementation of measures to avoid a pro-cyclical build-up of credit asset) boom-bust cycles. Furthermore, given the relevance of foreign-owned banks in two of the three countries, a continued strengthening of home-host cooperation in the supervisory area will be crucial to avoid any kind of regulatory arbitrage. JEL Classification: E3, E52, E58banking sector, emerging markets, Europe, macro-prudential approach, vulnerability indicators

Radio astronomy

The following subject areas are covered: (1) scientific opportunities (millimeter and sub-millimeter wavelength astronomy; meter to hectometer astronomy; the Sun, stars, pulsars, interstellar masers, and extrasolar planets; the planets, asteroids, and comets; radio galaxies, quasars, and cosmology; and challenges for radio astronomy in the 1990's); (2) recommendations for new facilities (the millimeter arrays, medium scale instruments, and small-scale projects); (3) continuing activities and maintenance, upgrading of telescopes and instrumentation; (4) long range programs and technology development; and (5) social, political, and organizational considerations

Political Contagion in Currency Crises

Existing models of contagious currency crises are summarized and surveyed, and it is argued that more weight should be put on political factors. Towards this end, the concept of political contagion introduced, whereby contagion in speculative attacks across currencies arises solely because of political objectives of countries. A specific model of membership' contagion is presented. The desire to be part of a political-economic union, where maintaining a fixed exchange rate is a condition for membership and where the value of membership depends positively on who else is a member, is shown to give rise to potential contagion. We then present evidence suggesting that political contagion may have been important in the 1992-3 EMS crisis.

Reliability Analysis And Optimal Maintenance Planning For Repairable Multi-Component Systems Subject To Dependent Competing Risks

Modern engineering systems generally consist of multiple components that interact in a complex manner. Reliability analysis of multi-component repairable systems plays a critical role for system safety and cost reduction. Establishing reliability models and scheduling optimal maintenance plans for multi-component repairable systems, however, is still a big challenge when considering the dependency of component failures. Existing models commonly make prior assumptions, without statistical verification, as to whether different component failures are independent or not. In this dissertation, data-driven systematic methodologies to characterize component failure dependency of complex systems are proposed. In CHAPTER 2, a parametric reliability model is proposed to capture the statistical dependency among different component failures under partially perfect repair assumption. Based on the proposed model, statistical hypothesis tests are developed to test the dependency of component failures. In CHAPTER 3, two reliability models for multi-component systems with dependent competing risks under imperfect assumptions are proposed, i.e., generalized dependent latent age model and copula-based trend-renewal process model. The generalized dependent latent age model generalizes the partially perfect repair model by involving the extended virtual age concept. And the copula-based trend renewal process model utilizes multiple trend functions to transform the failure times from original time domain to a transformed time domain, in which the repair conditions can be treated as partially perfect. Parameter estimation methods for both models are developed. In CHAPTER 4, based on the generalized dependent latent age model, two periodic inspection-based maintenance polices are developed for a multi-component repairable system subject to dependent competing risks. The first maintenance policy assumes all the components are restored to as good as new once a failure detected, i.e., the whole system is replaced. The second maintenance policy considers the partially perfect repair, i.e., only the failed component can be replaced after detection of failures. Both the maintenance policies are optimized with the aim to minimize the expected average maintenance cost per unit time. The developed methodologies are demonstrated by using applications of real engineering systems