The paper considers reliability analysis for aging multi-state system where the system and its components can have different performance levels ranging from perfect functioning to complete failure. Aging is treated as failure rate increasing during system lifetime. Reliability measures for multi-state system such as mean accumulated performance deficiency, mean number of failures, average availability, etc., are interpreted as system performability measures. The suggested approach presents the non-homogeneous Markov reward model for computation of these reliability measures for aging multi-state system under minimal repair. A numerical example is presented in order to illustrate the approach.
Received on August 28, 2008, revised on March 26, 2009
References: 15

A phased mission system represents a system whose performance is divided into consecutive non-overlapping phases. It is important to ensure safety of a phased mission system since the failure of it can have both life threatening and financial consequences. The focus of this paper is to develop an optimisation method to construct an optimal design case for a phased mission system, with the aim of minimising its unreliability and at the same time ensuring optimal usage of available resources throughout all phases. The introduced phased mission optimisation is represented as the constrained single objective problem. Here failure of the overall mission is the objective function and the introduced constraints are employed to determine the optimal use of resources. The implemented optimisation method employs Fault Tree Analysis to represent system performance and Binary Decision Diagrams to quantify each phase failure probability. A single objective Genetic Algorithm has been chosen as the optimisation technique. An Unmanned Aerial Vehicle mission has been selected to demonstrate the methods application. The results and the influence of modifications to the optimisation algorithm are discussed.
Received on October 14, 2008, revised on February 25, 2009
References: 17

This research focuses on quantitative analysis techniques for optimization of conceptual designs for products where lifecycle considerations are crucial. A product for which energy saving is practically mandatory, such as a major home appliance, was chosen, and the proposed procedure for minimizing the total cost through the product's lifecycle focuses especially on the use and maintenance stages. A multiobjective optimization problem is developed to minimize two evaluative characteristics, the manufacturing cost of the product (I), and the sum of the energy and maintenance costs of the product over an assumed period of time (II), treating the longevity of specified portions of the product and energy consumption rate as design variables. The optimization simulation was carried out for a numerical example based on this model, and a Pareto optimum solution for costs (I) and (II) was obtained. Using this Pareto optimum solution, we analyzed the optimum values of design variables and clarified quantitatively how the design parameters affect the optimum solution. The proposed model demonstrates potential for use in decision making during the conceptual product design stage, when determining design variable values that meet desired lifecycle cost requirements is a goal.
Received on April 02, 2008, revised on February 19, 2009
References: 17

The exact upper bound of the variance of properties from multiple sources is attained from sampling not more than two sources. This paper discusses important applications of this result referred to as variance upper bound theorem. A new conservative, non-parametric estimate has been proposed for the capability index of a process whose output combines contributions from multiple sources of variation. A new method for assessing and increasing the robustness of processes, operations and products where the mean value can be easily adjusted or is not critical has been presented, based on the variance upper bound theorem. We show that the worst-case variation of a property from multiple sources, obtained by using the variance upper bound theorem, can be used as a basis for developing robust engineering designs and products. If a design is capable of accommodating the worst-case variation of the reliability-critical parameters, it will also be capable of accommodating the variation of the reliability-critical parameters from any combination of sources of variation and mixing proportions. In this respect, a new algorithm for virtual testing based on the variance upper bound theorem has been proposed for determining the probability of a faulty assembly from multiple sources. For sources of variation that can be removed, the robustness can be improved further, by removing the source that yields the largest decrease in the variance upper bound. Consequently, the correspondent algorithm is also presented. A number of engineering applications have been discussed where the variance upper bound theorem can be used to assess and increase the robustness of mechanical and electrical components, manufacturing processes and operations.
Received on March 23, 2008, revised on November 11, 2008
References: 15

In continuous process industries the importance of predictive maintenance is increasing day by day. The unscheduled shutdowns and performance degradation of control components causes severe issues as regards to quantity/quality of production. The moving parts associated with control elements make them susceptible to faults and failures. In this paper a method is proposed to identify the faults of a final control element. The detailed study of a single seated globe valve using vibration signal analysis is presented. The QMF bank is used for processing the vibration signal. Main issues associated with this study are the positioning of the vibration sensors, signal to noise ratio, and filter coefficients along with the selection of network topology, training rule|Noof hidden layers, and number of perceptrons in each layer.
Received on July 2, 2008, revised on November 12, 2008
References: 15

In this paper, the method of detecting a runaway reaction in a batch process using artificial neural network (ANN) model is proposed. From the safety point of view, it is difficult to investigate what the causes of runaway reactions in the chemical plants are, besides as the consequences of the accident cannot be so well investigated. In this study, the parameters of temperature, pressure, and level of the reactor that influence a runaway reaction are studied. Based on historical data of the parameters (temperature, pressure, and level of the reactor) for normal and runaway reaction, the ANN model and simulation of Polyvinyl Chloride plant has been developed. Analysis of the learning and results of the ANN algorithm and simulation are presented and discussed. It is established that by using this approach, we can observe and compare what's the dominant factor of the runaway reaction. Finally, we also can visualize the characteristic of runaway reaction so we can anticipate and isolate this kind of fault.
Received on July 1, 2008, revised on January 24, 2009
References: 13

ISO/IEC Guide 51 recommends to estimate and to evaluate the safety-related risk in order to reduce it to a tolerable level. For the reasonable estimation and evaluation of risk reduction made by a final protection layer (FPL), it is necessary to understand the relationship between failures of FPL, demands and hazardous-event rates (HER). In the present paper, firstly, generic models for risk assessment are classified into three types by use of state-transition diagrams involving a fault state of an FPL, demand state and fatal harm state. And new generic Markov models are introduced and analyzed to estimate the HER in a steady state. Moreover, relationships between HER and the mean calendar-time to a hazardous event, MTH, are examined. And it is explored that HER equals the reciprocal of MTH, and HER can be calculated by use of the reciprocals of MTH even if the overall system has two process-inoperative states.
Received on October 26, 2008, revised on 12.02.2009
References: 10

The robustness of a network is the ability to maintain a satisfactory performance level when there may be system endogenous random failures plus possible failures caused by external attacks. A new approach for determining network robustness is presented based on the difference between the possibilistic and probabilistic network dependability estimates. Both the probabilistic and possibilistic estimates are derived here using a simple approximation method proposed by von Collani [9], but with different operations for the possibility estimate in some system structures. The proposed robustness estimation method is demonstrated for a sample of network architectures.
Received on July 04, 2008, revised March 1, 2009
References: 11

In this paper, we study the effect of critical human errors and common-cause failures on the performance of a system composed of three-state devices parallel components assuming that the open-mode failure rates of the operating units and the repair rates of the units failed due to open-mode failure are time varying. In this case, the system fails when a device fails in short-mode, or a common-cause failure or a critical human error occurs, or all devices fail in open-mode. The Markov method is used to develop generalized expressions for system state probabilities, system availability and reliability.
Received on September 8, 2008, revised March 24, 2009
References: 06