Reliability Of Complex Systems Research Articles

Estimate the useful life for a heating, ventilation, and air conditioning system on a high-speed train using failure models

<p class="Abstract">Heating, ventilation, and air conditioning (HVAC) is a widely used system used to guarantee an acceptable level of occupancy comfort, to maintain good indoor air quality, and to minimize system costs and energy requirements. If failure data coming from company database are not available, then a reliability prediction based on failure rate model and handbook data must be carried out. Performing a reliability prediction provides an awareness of potential equipment degradation during the equipment life cycle. Otherwise, if field data regarding the component failures are available, then classical reliability assessment techniques such as Fault Tree Analysis and Reliability Block Diagram should be carried out. Reliability prediction of mechanical components is a challenging task that must be carefully assessed during the design of a system. For these reasons, this paper deals with the reliability assessment of an HVAC using both failure rate model for mechanical components and field data. The reliability obtained using the field data is compared to the one achieved using the failure rate models in order to assess a model which includes all the mechanical parts. The study highlights how it is fundamental to analyze the reliability of complex system integrating both field data and mathematical model.</p>

Fault tree analysis of cargo leakage from manifold connection in fuzzy environment: A novel case of anhydrous ammonia

Ammonia cargo requires special expertise in terms of handling, storage and transportation aspects as it is unquestionably one of the toughest goods carried by tankers due to its intrinsically dangerous properties. Any malfunction experienced during the cargo operation may result in disasters. Cargo manifold leakage is one of the most critical hazards that may arise during cargo operations. According to the characteristics of the ammonia, manifold leakages contain risks that may result in explosion, fire, pollution and poisoning. In this study, all probable root causes and risk of cargo manifold leakage event of a gas tanker carrying ammonia is introduced by employing Fault Tree Analysis (FTA) in fuzzy environment, which is a systematic method to access reliability of complex systems both quantitatively and qualitatively by using exact occurrence probability values of all probable root causes. As a result, occurrence probability of ammonia leakage from cargo manifold is calculated as 0.00539 which is found realistic by consulted field experts. This study aims to introduce an appropriate management tool to identify root causes and mitigate the cargo manifold leakage risk by reducing the occurrence probabilities of the root causes.

Efficient reliability analysis of complex systems in consideration of imprecision

In this work, the reliability of complex systems under consideration of imprecision is addressed. By joining two methods coming from different fields, namely, structural reliability and system reliability, a novel methodology is derived. The concepts of survival signature, fuzzy probability theory and the two versions of non-intrusive stochastic simulation (NISS) methods are adapted and merged, providing an efficient approach to quantify the reliability of complex systems taking into account the whole uncertainty spectrum. The new approach combines both of the advantageous characteristics of its two original components: 1. a significant reduction of the computational effort due to the separation property of the survival signature, i.e., once the system structure has been computed, any possible characterization of the probabilistic part can be tested with no need to recompute the structure and 2. a dramatically reduced sample size due to the adapted NISS methods, for which only a single stochastic simulation is required, avoiding the double loop simulations traditionally employed.Beyond the merging of the theoretical aspects, the approach is employed to analyze a functional model of an axial compressor and an arbitrary complex system, providing accurate results and demonstrating efficiency and broad applicability.

Dynamic availability analysis using dynamic Bayesian and evidential networks

The probabilistic modelling is widely used in engineering practices, especially for assessing the safety and reliability of complex systems. Dynamic evidential network (DEN) can efficiently deal with epistemic uncertainty based on Dempster-Shafer theory. This work proposes an extended discrete-time DEN model along with an extensive review of its applications in engineering. The proposed model combines the Dempster-Shafer theory, used for handling epistemic uncertainty across a new state-space reconstruction of components, and the dynamic Bayesian network is used for multi-state system reliability. The model application is demonstrated on a real case study from the aviation field. The application quantifies reliability and availability parameters that help to prioritize maintenance activities and avoid failures of complex redundant systems. The proposed model can serve as a tool to assess the reliability and availability of industrial systems suffering from parameter uncertainty and common cause failures.

Preface: Special Issue on Reliability and Safety Modeling of Complex Systems

Preface: Special Issue on Reliability and Safety Modeling of Complex Systems

A hybrid machine learning method for procurement risk assessment of non-ferrous metals for manufacturing firms

ABSTRACT With the growing complexity of manufacturing systems nowadays, the effective assessment of important risk factors inherent in the manufacturing process is crucial for the stability and reliability of such complex systems. Thus, this article proposes a data-driven approach using the state-of-art machine learning techniques to assess and forecast the procurement risks of non-ferrous metals associated with complex manufacturing systems. A variety of state-of-art machine learning models including ANN, LSTM, BLSTM, GARCH, as well as their combinations which compose the proposed hybrid models, are deployed and analyzed. The testing results show that the proposed hybrid machine learning method can forecast the price uncertainty in procurement and effectively evaluate the procurement risk in a precautious manner. Moreover, it is shown that the hybrid model that combines GARCH, ANN, and LSTM significantly improves the forecasting results. Besides, the optimal choice of the network configurations in the hybrid model is also analyzed via a series of sensitivity analyses. This research can serve as a useful reference for the effective assessment and control of procurement risk for manufacturing firms.

Формалізоване подання експонентних моделей основних показників надійності, обмеженість їх застосування для характеристики машин інженерного озброєння

The article deals with the solution of a scientific and applied problem to study the possibility of using existing exponential models to determine the reliability indicators of engineering weapons. Exponential models are widely used to assess the reliability of objects, mainly consisting of radio electronic elements, which led to their mass distribution in the aviation industry, air defense facilities, etc. Experimental operation of typical samples of military road-building equipment and experimental studies of the operating time of the main blocks and assemblies of engineering weapons show that the rate of failure and restoration of these products are functions of time. This state of affairs is associated with the design features of engineering weapons, which are characterized by the complex use of electrical, mechanical, hydraulic and other systems, while during use these systems can often experience significant overloads. At the same time, it should be borne in mind that today the engineering weapons that are in the units generally have a service life longer than that guaranteed by the manufacturer, which significantly affects the parameters of failure rates and recovery. The article shows the procedure for obtaining expressions for calculating the main indicators of the reliability of complex technical systems with an exponential distribution of operating time to failure and their recovery time and it is allowed to use them only for minimal periods of time (from several hours to several days, depending on the intensity of the use of machines) due to for the non-ergodic nature of the process of failures and restorations. In addition, the use of these models should be accompanied by an assessment of the adequacy of the results obtained to the real process with the adjustment of the duration of the corresponding time intervals. Thus, the construction of mathematical models of the technical state of engineering equipment will be accompanied by a search for other conceptual approaches to determining the reliability indicators of engineering equipment and methods for calculating these indicators.

Reliability evaluation of non-repairable systems with failure mechanism trigger effect

Trigger effect indicates that some events occur because of the trigger of other events. This kind of effect often appears in the operation of products and leads to failure. Due to the randomness of trigger events, it is difficult to predict the reliability of a product that embraces triggering processes. In this paper, we develop a new reliability model for non-repairable systems with the trigger effect. The effect is divided into two types: degradation-degradation trigger effect and degradation-overstress trigger effect. To model this effect, the degradation process is described by the continuous or discrete stochastic process, while the overstress process is described by the homogeneous Poisson process. Furthermore, a method integrating Petri Net and Monte Carlo is proposed to evaluate the complex system reliability. To demonstrate the proposed model, a conductive slip ring in an electromechanical orientation device is introduced as a case, where the trigger effect of one trigger mechanism and three dependent basic mechanisms are considered. It is shown that the trigger time model and system modeling method can describe the trigger failure behaviors and evaluate the reliability of complex systems with the trigger effect.

Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability

Selective maintenance problem plays an essential role in reliability optimization decision-making problems. Systems are a configuration of several components, and there are situations the system needs small intervals or break for maintenance actions, during the intervals expert carried out the maintenance actions to replace or repair the deteriorated components of the systems. Because of the uncertainty associated with the component’s operational time, failure, and next mission duration create a new challenge in determining optimal components allocation and evaluating future missions successfully. In this paper, a multi-objective selective maintenance allocation problem is formulated with fuzzy parameters under neutrosophic environment. A new defuzzification technique is introduced based on beta distribution to convert fuzzy parameters into crisp values. The neutrosophic goal programming technique is used to determine the compromise allocation of replaceable and repairable components based on the system reliability optimization. A numerical illustration is used to validate the model and ascertain its effectiveness. The result is compared with two other approaches and found to be better. The method is flexible and straightforward and can be solved using any available commercial packages. The extension of the concept can be useful to other complex system reliability optimization.

A new framework of complex system reliability with imperfect maintenance policy

The interactions and dependencies between software and hardware are often neglected in modeling system reliability in the past few decades due to the mathematical complexity. However, many system failures occurred from the interactions or simultaneous occurrences of software and hardware. This paper first proposes a new diagram of categorizing system-level failures and further incorporates such a diagram into the development of complex system reliability framework. System-level failures result from software subsystem, hardware subsystem, and the interactions of software and hardware subsystems. The focus of this study is on the investigation of the interactions failures generated from the interactions of software and hardware subsystems. In addition to the considerations of total hardware failures, software-induced hardware failures, and hardware-induced software failures introduced by Zhu and Pham (Mathematics 7(11):1049, 2019), we further introduce the partial hardware failures that can be respectively induced by hardware and software to explicitly demonstrate the dependencies and interactions between software and hardware. Hence, a new complex system reliability framework is developed based on such system-level failure categorization with the Markov process. Furthermore, the numerical examples are studied to illustrate the impacts on system reliability with the changes of state transition parameters that modeling the interactions of software and hardware subsystems. Finally, we have studied two maintenance policies of the proposed complex system reliability model.

Multi-State System Reliability Evaluation and Component Allocation Optimization Under Multi-Level Performance Sharing

With the development of science and technology, the structure of engineering system has become increasingly large and complex. In order to ensure the safety and stability of the system in operation, the reliability evaluation of complex system has become an important research field. However, previous studies on the reliability of multi-state systems did not take into account the multi-level performance sharing in the system, and it has been unable to accurately assess the reliability of such complex systems. Therefore, based on the actual engineering system, this paper proposes a multi-state system with multi-level performance sharing mechanism. On this basis, we established a system reliability evaluation model using universal generating function technique. Through numerical examples, the application of the model and analyze the influence of different parameters on system reliability are demonstrated. In addition, we also use genetic algorithm to optimize the allocation of components in the system, so as to improve the reliability of the system. Different from the previous studies on system reliability with common bus performance sharing, the system proposed in this study is more general.

RISK-ORIENTED APPROACH IN PUBLIC REGULATION OF MAN-MADE SAFETY OF UKRAINE

Implementation on the territory of Ukraine of modern principles of regulation in the field of man-made and natural safety is carried out at a slow pace. The introduction of European standards of safe living, which is one of the requirements of Ukraine's integration into the EU, is possible subject to the implementation of conceptual and methodological innovations and institutional transformations. Unfortunately, over time, the conceptual principles of risk management today, without losing their relevance, are insufficiently implemented in the practice of governing bodies of the Unified State Civil Protection System. In addition, the need to move from public management of man-made safety to public regulation, as determined by the processes of deregulation in the state poses a scientific problem finding practical ways to implement a risk-oriented approach to the practice of government at all levels. The purpose of the article is to study the possibilities of application in state regulation of man-made safety risk-oriented approach and its content. Risk-oriented approach (ROP) to any activity. assumes that any dangers (in the sphere of production, in everyday life and everyday life), despite their diversity, have the same nature of occurrence and the same logic of events. The main tasks of the ROP are to create a scientific basis for ensuring the reliability of complex technical systems for human safety and the environment, to develop methods for assessing the degree of danger of industrial facilities and the scientific basis of the concept of acceptable risk. The main instruments of public regulation in the field of risk management are state standardization, certification, state expertise, state supervision and control, licensing, economic regulation, declaration of facility safety and insurance. The main processes of state regulation of man-made safety on the basis of a risk-oriented approach are monitoring of emergencies, identification and certification of the risk of their occurrence, minimization of their impact or consequences (in case of catastrophic development of the situation). The risk assessment should be based on the technical concept of assessing the probability of their occurrence. Areas of further research are to determine the strategic directions of publik regulation of man-made safety based on the application of risk-oriented approach, development of proposals for the practical establishment of emergency monitoring centers.

Composite Hybrid Framework for Through-Life Multi-Objective Failure Analysis and Optimisation

Complex engineering systems include several subsystems that interact in a stochastic and multifaceted manner with multiple failure modes (FMs). The dynamic nature of FMs introduces uncertainties that negatively impact the reliability, risk, and maintenance of complex systems. Traditional approaches of adopting standalone techniques for managing FMs independently at various stages of the asset life cycle pose challenges related to utilisation, costs, availability, and in some cases, accidents. Therefore, this paper proposes a composite hybrid framework comprising four independent hybrid models for comprehensive through-life failure management and optimisation. The first hybrid model entails failure mode, effects, and criticality analysis (FMECA) and fault tree analysis (FTA) to identify critical FMs and overall subsystem failure rates. The second hybrid model analyses FMs caused by multiple subsystems using hybrid dynamic Bayesian discretisation. The third hybrid model adopts a hybrid Gaussian process regression machine learning technique to evaluate wear loss. The fourth hybrid model evaluates the overall risk using a Bayesian factorisation and elimination method based on multiple failure causes. Finally, a decision-making step is used to evaluate the results of the previous four steps to decide an appropriate maintenance strategy. The proposed method is verified through a case study of a UK-based train operator’s pantograph system. The results show that the maintenance inspection intervals and strategy obtained using the proposed framework strike a good balance between safety and fleet availability.

Improving Reliability of Complex Systems Using Analyses Obtained Through Design Structure Matrix and Interactive Failure Detection Procedures

The process of development and expansion of advanced industries reveals the need to implement more and more predictive methods and mechanisms in readiness to deal with possible failures. With complexities inherent in systems, having a proper and all-embracing model of the entirety of a system is not readily possible. Design structure matrices (DSMs) are regarded as great (a great) help in communicating, comparing, and integrating partial system models. Given that there are numerous relationships among subsystems in complex systems, it is expected that interactive failures occur giving rise to diverse problems as well as gradual or abrupt failures in the system. Correlational dependent (Correlational-dependent) failures, commonly known as interactive failures, most frequently occur in mechanical systems. In this study, we have exploited DSM for identifying interactive failures and the relationships existing among different components in complex systems. The latter matrix is generally used in industries for observing the strengths of existing relationships among interacting elements. From another perspective, by analyzing the relationships among elements and identifying coils and curls, it is possible to investigate the existing nodes in loops. Implementing this procedure leads to identifying critical components and interactive failures, eventually bringing about enhanced reliability in the system. The present paper, while considering prevailing methods adopted in previous studies for selecting critical parts and subsystems, proposes a new method for selecting critical parts so as (delete so as) to increase the reliability rates. The method set forth is derived from the Markov chain model in addition to employing mathematical methods in matrices.

ALGORITHMS AND SOFTWARE SUITE FOR RELIABILITY ASSESSMENT OF COMPLEX TECHNICAL SYSTEMS

Context. One of the most essential properties of technical systems is their reliability, i.e. the ability of the system to perform intended functions, preserving with time the values of operation indicators within the predefined boundaries. The failure cost for modern complex technical system can be very high, which can result in events of different severity ranging from economic losses to harm to human life and health. Hence, the requirements for their reliability constantly increase. The reliability assessment of complex technical systems can be simplified by the combination of analytical research methods with computational capabilities of modern computers. The most widely used analytical methods are based on the theory of Markov processes which in turn provide the possibility to determine the time dependencies of probabilities of the system to be in defined states (operating, recovering, failure etc.), and thus the values and time dependencies of the reliability indices needed. These methods can be successfully used for the reliability analysis of different kinds of technical systems: both non-recovered and recovered; non-redundant and redundant of different redundancy types, maintenance priorities etc. However, the application of these methods for complex technical systems containing large number of elements meets the high dimensional calculation problem, which makes it impossible to perform these tasks manually. Hence the problem of automation of complex technical system reliability modeling using modern computational systems is very relevant research topic. To solve this problem, one can use specific algorithmic and software techniques described in this paper.Objective. The goal of this article is to develop the algorithms for automated RBD processing and reliability indices assessment of complex technical systems along with the software suite for automated reliability assessment.Method. To perform the reliability analysis the RBD approach is used which allows one to represent and visualize each element of the system in the form of a rectangle, joined by the lines in parallel or in series with other elements of the system. To obtain the reliability indices values the mathematical model of technical system reliability behavior using Markovian random process was suggested. The algorithm of RBD processing and automatic determination of operability conditions of a technical system was further considered. To calculate the minimum and maximum number of operational and failure states for the system of n elements and r recoveries the paper introduces a mathematical model based on combinatorial approach. To develop the software suite the objectoriented approach was used.Results. The algorithms and software suite allows us to easily construct RBD for a technical system, to automatically determine the operability condition with execution time of about 10 sec for 1,000 elements with mixed type of connection, to form automatically a state-and-transition matrix along with the corresponding differential equation system and solve it with total execution time of about 35 sec for 109 states and, thus to obtain the numerical values of reliability indices for the technical system studied. A case study of the reliability assessment for the system consisting of 22 elements using RBD shows that the total time of software execution is 36.712 sec. During executing of this test case the most time (35.168 sec) was spent for execution of the algorithm for construction of a state-and-transition graph consisting of 52,694 states.Conclusions. The algorithms and methods for automated reliability indices assessment of complex technical systems based on RBD approach, as well as model for estimating the number of total and working system states are presented. The modular structure of the developed software suite makes it flexible and gives an opportunity to add and make modifications of modules fast and without significant program changes.

Preface

Ensuring the high quality and reliability of complex technical systems in the modern world remains the sharpest and most relevant topic. High dynamics of changes in technical products, such as automobiles, military equipment, marine vessels, electronic industry products, machine tools and equipment, dictates the conditions for revising methods and approaches to ensure quality, reliability and competitiveness. Serious changes in production technologies require a review of the fundamentals of statistical process control, since the effectiveness and efficiency of quality control methods aimed at directly influencing a technological operation remain in doubt.In this regard, fundamental research is becoming particularly relevant. The international scientific-practical conference “Quality Management and Reliability of Technical Systems” is held with the aim of increasing the effectiveness of scientific research, developing regional and international scientific cooperation, creating conditions for scientists to exchange research results, systematizing current problems and identifying trends in scientific research in the field of quality management and reliability of technical systems. Fundamental scientific research aimed at addressing the issues of machines and energy complexes safety, reliability, survivability is of particular relevance; control systems optimization methods and intellectualization and processes; adaptive management; control systems modeling and identification; information interaction in complex systems; modeling of promising structures, materials and technologies; new methods and approaches to ensure the quality and reliability of modern industries study; modern standardization problems; complex technical systems and information management systems; control in deterministic, stochastic systems and in conditions of uncertainty; ergonomics and biomechanics of systems “man - machine - environment”.The issue was prepared with organizing, informational and technical support of the National Technology Initiative Center for Advanced Manufacturing Technologies based on the Institute of Advanced Manufacturing Technologies of Peter the Great St.Petersburg Polytechnic University.The issue was prepared with financial support of the grant from the Program Competitiveness Enhancement of Leading Russian Universities among Global Research and Education Centers, supported by the Ministry of Science and Higher Education of the Russian Federation of Peter the Great St.Petersburg Polytechnic University, Project 5-100-2020.All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.”

One universal method of complex system reliability, maintainability, supportability, testability quotas design and trade‐off based on improved flower pollination algorithm

AbstractFor modern complex system, quality has become a serious and difficult problem that restricts the generation of combat effectiveness. Withal, based on domestic and foreign research and analysis, this paper puts forward a trade‐off method for complex system reliability, maintainability, supportability, testability (RMST) design, which is suitable for product design stage. First, aiming at the uncertain problem of complex system constrained optimization, the good‐point set population initialization, Deb feasibility comparison method and ε constraint method are integrated into the flower pollination algorithm, to construct the algorithm for RMST quotas design and trade‐off. Second, taking the typical series‐parallel repairable system as an example, one general model for complex system RMST quotas design and trade‐off based on effectiveness is constructed. Finally, take an unmanned nuclear radiation detection system as a typical case, to verify its feasibility, advantages, and disadvantages.

Using of particle swarm optimization (PSO) to addressed reliability allocation of complex network

This paper focuses on the reliability of complex system that has been measured as a complex system using minimal paths. The reliability of this system has been assigned to research the possible approaches of the assignment reliability values based on reducing the total cost of this method. The results originally included:(i) Three cost functions were used to measure the cost of the complex system: First, the exponential behavior model with the feasibility factor model. Second, the exponential behavior model. Third, the logarithm model.(ii) The reliability of every component of the system was calculated using Particle Swarm algorithm to solve the problems of optimizing the given reliability of the complex system.

Developing the model of reliability of a complex technical system of repeated use with a complex operating mode

Solving the problems of setting requirements to the reliability of complex technical systems for various purposes presupposes their classification according to the features characterizing the purpose, modes of use, etc. According to the modes of use, systems are divided into objects of continuous long-term use, repeated cyclic use, and single-use. The objects of repeated cyclic use include the systems operating in cycles. Durations of the periods of work and pause in the cycle are considered deterministic values. Technological and/or technical maintenance is carried out in pauses between the operation periods. In addition to the known classification, it was proposed to introduce a group of systems of repeated use with a complex operating mode. A complex mode is understood as a mode that includes waiting for a request of the system use and executing the request after it arrives at a random time. An analytical model of reliability of such a system has been developed in the form of a ratio for a non-stationary total coefficient of operational readiness. This model describes the processes of the system functioning in the intervals of waiting and use. In this case, the duration of the intervals of waiting and/or execution of the request are random values. Ratios for this indicator were obtained for three options of specifying the functions of distribution of durations of waiting in a turn-on condition and fulfilling the request for use. The developed model makes it possible to set requirements for reliability and maintainability of the systems with a complex operating mode. The results of modeling the dependences of the operational indicators of reliability on parameters of the functions of distribution of durations of waiting and executing the request were obtained for different distributions. Recommendations were formulated concerning the substantiation of the requirements to reliability and maintainability of the systems under consideration

Reliability analysis of safety automatic change over switch based on fault tree analysis

Many practical applications for analyzing the reliability of complex system by using fault tree analysis, in this study we introduce fault tree analysis to calculate reliability of safety automatic change over switch which is used in our home in Iraq to determine the failure causes for it.