Volume 3, Number 2, 2006
Special Issue on System Reliability and Safety (pp.107-214)
Ro-Ro vessels for cargo and passengers (RoPax) are a relatively new concept that has proven to be popular in the Mediterranean region and is becoming more widespread in Northern Europe. Due to its design characteristics and amount of passengers, although less than a regular passenger liner, accidents with RoPax vessels have far reaching consequences both for economical and for human life. The objective of this paper is to identify hazards related to casualties of RoPax vessels. The terminal casualty events chosen are related to accident and incident statistics for this type of vessel. This paper focuses on the identification of the basic events that can lead to an accident and the performance requirements. The hazard identification is carried out as the first step of a Formal Safety Assessment (FSA) and the modelling of the relation between the relevant events is made using Fault Tree Analysis (FTA). The conclusions of this study are recommendations to the later steps of FSA rather than for decision making (Step 5 of FSA). These recommendations will be focused on the possible design shortcomings identified during the analysis by fault trees throughout cut sets. Also the role that human factors have is analysed through a sensitivity analysis where it is shown that their influence is higher for groundings and collisions where an increase of the initial probability leads to the change of almost 90% of the accident occurrence.
Risk analysis of chemical spills at sea and their consequences for sea environment are discussed. Mutual interactions between the process of the sea accident initiating events, the process of the sea environment threats, and the process of the sea environment degradation are investigated. To describe these three particular processes, the separate semi-Markov models are built. Furthermore, these models are jointed into one general model of these processes interactions. Moreover, some comments on the method for statistical identification of the considered models are proposed.
Economic efficiency of a multi-station transfer line (TL) is evaluated directly by the quantity of parts produced; therefore, each single manufactured part counts. The contribution presents an approach which applies a reliability-adaptive operating strategy in combination with tool derating. It is the objective to hold the system harmonisation of tool changes as maintenance actions. The significant effectiveness of the approach is demonstrated by different configurations and contexts. The output-time function of a TL without reliability-adaptive control is compared with functions of a system with reliability-adaptive control.
In this paper, we systematically discuss the basic concepts of grey theory, particularly the grey differential equation and its mathematical foundation, which is essentially unknown in the reliability engineering community. Accordingly, we propose a small-sample based approach to estimate repair improvement effects by partitioning system stopping times into intrinsic functioning times and repair improvement times. An industrial data set is used for illustrative purposes in a stepwise manner.
In this paper, we consider the problem of the evaluation of system reliability using statistical data obtained from reliability tests of its elements, in which the lifetimes of elements are described using an exponential distribution. We assume that this lifetime data may be reported imprecisely and that this lack of precision may be described using fuzzy sets. As the direct application of the fuzzy sets methodology leads in this case to very complicated and time consuming calculations, we propose simple approximations of fuzzy numbers using shadowed sets introduced by Pedrycz (1998). The proposed methodology may be simply extended to the case of general lifetime probability distributions.
Minimal cut sets (or prime implicants: minimal combinations of basic event conditions leading to system failure) are important information for reliability/safety analysis and design. To obtain minimal cut sets for general non-coherent fault trees, including negative basic events or multi-valued basic events, a special procedure such as the consensus rule must be applied to the results obtained by logical operations for coherent fault trees, which will require more steps and time. This paper proposes a simple method for a non-coherent fault tree, whose top event is represented as an AND combination of monotonic sub-trees. A monotonic sub-tree means that it does not have both positive and negative representations for each basic event. It is proven that minimal cut sets can be obtained by a conventional method for coherent fault trees. An illustrative example of a simple event tree analysis shows the detail and characteristics of the proposed method.
In the paper, excess methods for improving the reliability of multi-state series-parallel systems are presented: for the hot reserve of single components, the cold reserve of single components, and the mixed (hot and cold) reserve of single components. A process is also introduced to improve the reliability of these methods by replacing their components with more reliable ones. New theorems for multi-state limit reliability functions in homogeneous and non-homogeneous series-parallel large systems composed of components with improved reliability are presented, and applied to compare the effects of these systems in different reliability improving methods.
The problems associated with evacuation of people from the ship in an emergency situation are analyzed, especially passenger ships are taken under consideration. The most dangerous accidents requiring evacuation are described. Marine accidents often occur as eliminating all of the hazards to human health and life is still impossible. In every case, the evacuation process from the ship must be taken under consideration. Evacuation route arrangement should provide the possibility of safe departure from danger areas for passengers and crew members. Evacuation routes designed for human interaction within the evacuation process and other important factors are reviewed. Additipnally, the method for seeking evacuation time as a function of initial distribution of passengers and evacuation routes choosing is suggested. A genetic algorithm will be used, whilst the calculated evacuation time is connected with a fitness function. Parameters of evacuation routes topology are coded as non-binary chromosomes. Genetic operators are fitted for such types of problems to avoid receiving infeasible solutions. The objective of the proposed method is to find the evacuation time in worse case scenarios.
Construction conception of an object requires multi-criterion analysis. In such a case, reliability analysis gives rough information on availability and fulfillment of main functions. In the paper, the analysis of drive system in river barge pusher is presented. It consists of Reliability Block Diagram (RBD) analysis of various composition of the system and Markov analysis based on prior estimated operational data.
A novel approach to estimate reliability properties of systems or components individually during operation is presented. It is distinguished between slow and fast reliability states based on an equivalent system representation. Conditions for their observability and control are given and objectives for optimal reliability-based control are discussed in general.
This paper presents a methodology for risk assessment of plants producing and storing explosives. The major procedural steps for quantified risk assessment (QRA) in explosive plants are the following: hazard identification, accident sequence modeling, data acquisition, accident sequence quantification, consequence assessment and integration of results. This methodology is demonstrated and applied in an explosive plant consisting of four separate units, which produce detonating cord, nitroglycol, dynamites and ammonium nitrate fuel oil (ANFO). A GIS platform is used for depicting individual risk from explosions in this plant. Total individual risk is equal to 1.0 10-4/y in a distance of 340m from the center of the plant, and 1.0 10-6/y in a distance of 390m from the center of the plant.
This contribution discusses the concept of Reliability-Adaptive Systems (RAS) to multi-system operation. A fleet of independently operating systems and a single maintenance unit are considered. It is the objective in this paper to increase overall performance or workload respectively by avoiding delay due to busy maintenance units. This is achieved by concerted and coordinated derating of individual system performance, which increases reliability. Quantification is carried out by way of a convolution-based approach. The approach is tailored to fleets of ships, aeroplanes, spacecraft, and vehicles (trains, trains, buses, cars, trucks, etc.) - Finally, the effectiveness of derating is validated using different criteria. The RAS concept makes sense if average system output loss due to lowered performance level (yielding longer time to failure) is smaller than average loss due to waiting for maintenance in a non-adaptive case.
In this paper, a semi-Markov model of system operation processes is proposed and its selected parameters are determined. A series-parallel multi-state system is considered, and its reliability and risk characteristics found. Subsequently, a joint model of system operation process and system multi-state reliability and risk is constructed. Moreover, the asymptotic approach to reliability and risk evaluation of a multi-state series-parallel system in its operation process is applied to a port grain transportation system.
New development trends in electronic operating data logging systems enable classification, recording and storage of load spectrums of mechanical transmission components during usage. Based on this fact, the application of online reliability evaluation and reliability prediction procedures are presented. Different methods are considered to calculate reliability, depending on actual load spectrum and a Wohler curve. The prediction of a reliability trend is analyzed by the application of time series models. For this purpose, exponential smoothing model, regression model, and the ARIMA model are considered to evaluate data and predict an decreasing reliability trends during usage.