Defense and attack of complex and dependent systems

A framework is constructed for how to analyze the strategic defense of an infrastructure subject to attack by a strategic attacker. Merging operations research, reliability theory, and game theory for optimal analytical impact, the optimization program for the defender and attacker is specified. Targets can be in parallel, series, combined series-parallel, complex, k-out-of-n redundancy, independent, interdependent, and dependent. The defender and attacker determine how much to invest in defending versus attacking each of multiple targets. A target can have economic, human, and symbolic values, subjectively assessed by the defender and attacker. A contest success function determines the probability of a successful attack on each target, dependent on the investments by the defender and attacker into each target, and on characteristics of the contest. The defender minimizes the expected damage plus the defense costs. The attacker maximizes the expected damage minus the attack costs. Each agent is concerned about how his investments vary across the targets, and the impact on his utilities. Interdependent systems are analyzed where the defense and attack on one target impacts all targets. Dependent systems are analyzed applying Markov analysis and repeated games where a successful attack on one target in the first period impacts the unit costs of defense and attack, and the contest intensity, for the other target in the second period.     

Strategic defense and attack for reliability systems

This article illustrates a method by which arbitrarily complex series/parallel reliability systems can be analyzed. The method is illustrated with the series–parallel and parallel–series systems. Analytical expressions are determined for the investments and utilities of the defender and the attacker, depend on their unit costs of investment for each component, the contest intensity for each component, and their evaluations of the value of system functionality. For a series–parallel system, infinitely many components in parallel benefit the defender maximally regardless of the finite number of parallel subsystems in series. Conversely, infinitely many components in series benefit the attacker maximally regardless of the finite number of components in parallel in each subsystem. For a parallel–series system, the results are opposite. With equivalent components, equal unit costs for defender and attacker, equal intensity for all components, and equally many components in series and parallel, the defender always prefers the series–parallel system rather than the parallel–series system, and converse holds for the attacker. Hence from the defender's perspective, ceteris paribus, the series–parallel system is more reliable, and has fewer “cut sets” or failure modes.     

Performance optimization of a two-circuit cycle with parallel evaporators for a domestic refrigerator-freezer

A two-circuit cycle with parallel evaporators (called a “parallel cycle”) for a domestic refrigerator-freezer (RF) shows energy saving potential compared with a conventional cycle with a single loop or serial evaporators because of a low compression ratio in the fresh food compartment (R)-operation. The objective of this study is to investigate the effects of the refrigerant charge, R-capillary tube, and refrigerant recovery operation on the performance of a parallel cycle. In addition, design guidelines for the heat transfer area and air flow rate of an R-evaporator are proposed. When the parallel cycle was optimized in terms of the refrigerant charge and R-capillary tube diameter, the energy consumption was reduced by 7.8% over a bypass two-circuit cycle with the same RF platform. In addition, an additional energy saving of 1.8% was obtained by the optimization of the operating sequence and refrigerant recovery operation.     

A case study in productivity-cost trade-off in the design of paced parallel production systems

This paper examines the investment and operational cost differences between high-volume serial CNC-based machining lines and parallel CNC-based machining lines. With the progress of CNC technology and their descending cost, more CNC machines have been used in high-volume production systems. CNC machines increase the flexibility and machining capability of production lines, greatly increasing the number of line configurations. Parallel configurations improve system throughput and have the same effect as adding buffers to a pure serial line but without additional work-in-process inventory. This analysis is performed through a case study of a CNC-based automotive cylinder head machining line. Examining machine reliability, line balance, configuration throughput, and cost yields insight into the cost-benefit tradeoff of implementing parallelism. It is found that even with large increases in investment in automated material handling, parallel configurations can yield significant annual cost savings over pure serial lines through reductions in capital investment, especially in CNC machines, and improvements in efficiency, and on a per unit capacity basis, parallel configurations are the least expensive.     

Reliability and risk analysis of large systems with ageing components

Applications of limit reliability functions to the reliability evaluation of large multi-state systems composed of independent components are considered. The main emphasis is on multi-state systems with ageing components because of the importance of such an approach in safety analysis, assessment and prediction, and analysing the effectiveness of operation processes of real technical systems. The results concerned with multi-state series systems are applied to the reliability evaluation and risk function determination of a homogeneous bus transportation system. Results on limit reliability functions of a homogeneous multi-state “m out of n” system are applied to durability evaluation of a steel rope. A non-homogeneous series-parallel pipeline systems composed of several lines of pipe segments is estimated as well. Moreover, the reliability evaluation of the model homogeneous parallel-series electrical energy distribution system is performed.     

Exo-reversible staging of coolers in series and in parallel

Serial and parallel staging of exo-reversible coolers are formulated, analyzed and compared. The parallel staging includes an extensive parameter which is the proportion of combined stages. This extensive free parameter affects the intensive factors of specific power and figure of merit. Serial staging reduces the 1st Law efficiency and parallel staging improves the 2nd Law efficiency. Comparison of a parallel with a serial staging under common cooling capacity and cooling range, shows that it is always possible to find a parallel arrangement of lower specific power and more compact. Some results are demonstrated on staging of Joule-Thomson cryocoolers (below and above the Joule-Thomson inversion temperature).     

Joint redundancy and maintenance optimization for multistate series–parallel systems

This paper formulates the joint redundancy and replacement schedule optimization problem generalized to multistate system, where the system and its components have a range of performance levels. Multistate system reliability is defined as the ability to maintain a specified performance level. The system elements are chosen from a list of available products on the market and the number of such elements is determined for each system component. Each element is characterized by its capacity, reliability and cost. The reliability of a system element is characterized by its lifetime distribution with the hazard rate, which increases with time. It is specified as the expected number of failures during different time intervals. The optimal system structure and the number of element replacements during the study period are defined as those which provide the desired level of system reliability with minimal sum of costs of capital investments, maintenance and unsupplied demand caused by failures. A universal generating function technique is applied to evaluate the multistate system reliability. A genetic algorithm is used as an optimization technique. Examples of determination of the optimal system structure and replacement schedule are provided.     

Reliability equivalence of independent and non-identical components series systems

This paper is devoted to obtain the reliability equivalence factors of n independent and non-identical components series system. The lifetime of each component is assumed to be exponentially distributed random variable. The results introduced by Råde [Råde L. Reliability equivalence. Microelectronics and Reliability 1993a;33:323–325; Råde L, Reliability survival equivalence. Microelectronics and Reliability 1993b;33:881–894.] can be obtained as special cases from this work when n=1,2 and assuming the components are identical.     

Experimental study of a miniature vapor compression refrigeration system with two heat sink evaporators connected in series or in parallel

A miniature vapor compression refrigeration system included two heat sinks connected in series (indicated as series system) or in parallel (indicated as parallel system) was built. The performance of the series system was studied and compared with that of the parallel system. The results indicate that the largest cooling capacity of the two systems is about 160 W and the optimal refrigerant charge is about 0.6 M_total in the miniature vapor compress refrigeration (VCR) system. There is no relation between the optimal refrigerant charge and the arrangement of the heat sinks. The coefficient of performance (COP) of the series system ranged from 1.81 to 3.22, while the COP of the parallel system was in the range of 1.51–2.92 under the cooling capacity of 100 W. The cooling of the heat sink 2 lag behind that of the heat sink 1 in the serial system, while the refrigerant is difficult to equally distribute in the parallel system.     

Reliability properties of systems with exchangeable components and exponential conditional distributions

We study basic properties for bivariate systems with exchangeable components and exponential conditional distributions which represent bi-component biological or engineering systems with structural dependency. This is equivalent to suppose that we have similar components with the bivariate exponential conditional joint distribution defined by Arnold and Strauss (1988). Specifically, we study the reliability functions, the moments, some aging measures, ordering and classification properties for series and parallel systems. Supported by Ministerio de Ciencia y Tecnología under grant BFM2003-02947     

Assessment of low probability events of dynamical systems by controlled Monte Carlo simulation

Various procedures to extend the applicability and to increase the efficiency of Monte Carlo simulation (MCS) for the analysis of complex dynamical systems are discussed. In particular, the capabilities of the methods denoted Russian Roulette and Splitting (RR&S) and Double and Clump (D&C) are reviewed with regard to their capabilities to analyze such systems. In this context, the difficulties in identifying the ‘important' regions for simulation are detailed. It is shown that these difficulties may be circumvented by a newly introduced ‘distance controlled' MCS. This procedure, which allows the prediction of very low probability events and the analysis of systems of higher dimension, is applicable not only to mechanical systems and structures but also to complex dynamical systems encountered, for example, in economics, physics, etc. The procedure is shown to be particularly suited to cases where exact analytical methods and direct Monte Carlo simulation are infeasible, hence, being well suited for practical application.     

Hybrid systems for planning and optimization of virtual assembly

Virtual assembly is the simulation of parts assembly processes by computer, analysing, evaluating and optimizing the feasibilities and procedures of assembly. It can thus avoid the potential problems and risks from designing to assembling. In this way, we can achieve the global optimization of the products and timely respond to the needs of the market. This paper presents a modelling framework for virtual assembly paths design and optimization of two objects on the basis of a class of hybrid system, which is applicable in many manufacturing environments. We propose an elementary hybrid machine containing time-driven and event-driven dynamics. We describe in detail a method of assembly paths design. The objective of optimization is evaluated in terms of time in the transition dynamics so as to make the problem more tractable. An explicit algorithm for deriving optimal assembly policies is developed. The optimal results indicate the feasibility and efficacy of the model and control algorithms.     

Bayesian reliability analysis of a products of probabilities model for parallel systems with dependent components

In a Bayesian reliability analysis of a system with dependent components, an aggregate analysis (i.e. system-level analysis) or a simplified disaggregate analysis with independence assumptions may be preferable if the estimations obtained from employing these two approaches do not deviate substantially from those derived through a disaggregate analysis, which is generally considered the most accurate method. This study was conducted to identify the key factors and their range of values that lead to estimation errors of great magnitude. In particular, a copula-based Bayesian reliability model was developed to formulate the dependence structure for a products of probabilities model of a simple parallel system. Monte Carlo simulation, regionalised sensitivity analysis and classification tree learning were employed to investigate the key factors. The resulting classification tree achieved favourable predictive accuracy. Several decision rules suggesting the optimal approach under different combinations of conditions were also extracted. This study has made a methodological contribution in laying the groundwork for investigating systems with dependent components using copula-based Bayesian reliability models. With regard to practical implications, this study also derived useful guidelines for selecting the most appropriate analysis approach under different scenarios with different magnitude of dependence.     

An analytical methodology for the dependability evaluation of non-Markovian systems with multiple components

Very often, in dependability evaluation, the systems under study are assumed to have a Markovian behavior. This assumption highly simplifies the calculations, but introduces significant errors when the systems contain deterministic or quasi-deterministic processes, as it often happens with industrial systems. Existing methodologies for non-Markovian systems, such as device stage method [1], the supplementary variables method or the imbedded Markov chain method [2] do not provide an effective solution to deal with this class of systems, since their usage is restricted to relatively simple and small systems.This paper presents an analytical methodology for the dependability evaluation of non-Markovian discrete state systems, containing both stochastic and deterministic processes, along with an associated systematic resolution procedure suitable for numerical processing. The methodology was initially developed in the context of a research work [3] addressing the dependability modeling, analysis and evaluation of large industrial information systems. This paper, extends the application domain to the evaluation of reliability oriented indexes and to the assessment of multiple components systems. Examples will be provided throughout the paper, in order to illustrate the fundamental concepts of the methodology, and to demonstrate its practical usefulness.     

Estimation of exponential component reliability from uncertain life data in series and parallel systems

Estimating reliability of components in series and parallel systems from masking system testing data has been studied. In this paper we take into account a second type of uncertainty: censored lifetime, when system components have constant failure rates. To efficiently estimate failure rates of system components in presence of combined uncertainty, we propose a useful concept for components: equivalent failure and equivalent lifetime. For a component in a system with known status and lifetime, its equivalent failure is defined as its conditional failure probability and its equivalent lifetime is its expectation of lifetime. For various uncertainty scenarios, we derive equivalent failures and test times for individual components in both series and parallel systems. An efficient EM algorithm is formulated to estimate component failure rates. Two numerical examples are presented to illustrate the application of the algorithm.     

Ant system for reliability optimization of a series system with multiple-choice and budget constraints

Many researchers have shown that insect colonies behavior can be seen as a natural model of collective problem solving. The analogy between the way ants look for food and combinatorial optimization problems has given rise to a new computational paradigm, which is called ant system. This paper presents an application of ant system in a reliability optimization problem for a series system with multiple-choice constraints incorporated at each subsystem, to maximize the system reliability subject to the system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. This problem is solved by developing and demonstrating a problem-specific ant system algorithm. In this algorithm, solutions of the reliability optimization problem are repeatedly constructed by considering the trace factor and the desirability factor. A local search is used to improve the quality of the solutions obtained by each ant. A penalty factor is introduced to deal with the budget constraint. Simulations have shown that the proposed ant system is efficient with respect to the quality of solutions and the computing time.     

The set-theory method for systems reliability of structures with degrading components

The times and frequencies of inspection, maintenance and replacement in structural systems are complicated by uncertain degradation rates of structural characteristics. Although degradation work at the component, or single failure mode level, is ongoing, this paper presents a method for assessing systems reliability where failure events may be described by time-variant parallel and/or series systems. Herein the models for the degradation rates contain random variables and time. For multiple failure modes and a sequence of discrete times, set theory establishes the true incremental failure region that emerges from a safe region. Probabilities via Monte-Carlo simulation require only time-invariant calculations. The cumulative failure distribution is the summation of the incremental failure probabilities. A practical implementation of the theory requires only two contiguous times. Error analysis suggests ways to predict and minimize errors so the method appears sufficiently accurate for engineering applications. Two structures with elastic-brittle material and time-invariant loads show the details of the method and the potential of the approach. It is shown that the proposed method provides a more realistic and efficient way to predict systems reliability than path-tracing methods that are available in the open literature.     

Reliability and performance analysis of hardware–software systems with fault-tolerant software components

This paper presents an algorithm for evaluating reliability and expected execution time for systems consisting of fault-tolerant software components running on several hardware units. The components are built from functionally equivalent but independently developed versions characterized by different reliability and execution time. Different number of versions can be executed simultaneously depending on the number of available units. The system reliability is defined as the probability that the system produces a correct output in a specified time.     

Industry 4.0 integration with socio-technical systems theory: A systematic review and proposed theoretical model

Industry 4.0 promises the fourth industrial revolution by integration of cyber and physical worlds through technology. Industry 4.0 implementation will result in human interaction with technical system in a specialised manner. Therefore, Industry 4.0 will also be a socio (human related) and technical (nonhuman related) system in pursuit of a common goal. The purpose of this study is to suggest a mechanism to include Socio-Technical Systems Theory perspective while designing architecture for integration while implementing Industry 4.0. Building on the previous literatures on Socio-Technical Systems Theory and Industry 4.0, the article proposes bringing the two approaches together and presents a framework for integration mechanism. Successful implementation of Industry 4.0 warrants vertical, horizontal and end-to-end integration. This study suggests a design mechanism for three types of integration mechanism in Industry 4.0 by considering the socio-technical systems impact on people, infrastructure, technology, processes, culture and goals. Further, the integration is also suggested for analysis on the impact of stakeholders, economic situation and regulatory frameworks around which the operating organizations are operating. This is the first paper to propose the consideration of Socio-Technical Systems theory while designing the horizontal, vertical and end-to-end integration for sustainable implementation of Industry 4.0.