Optimal Design of a Series-Parallel System with Time-Dependent Reliability

The paper formulates an optimal reliability design problem for a series system made of parallel redundant subsystems. The variables for optimization are the number of redundant units in each subsystem and the reliability of each unit. There is a cost-constraint. The time for which the system reliability exceeds a specified value is to be maximized. Similarly the cost could be minimized for a constraint on the mission time and reliability. A solution method for the formulated problems is presented along with an example.     

Optimal Design for System Reliability and Maintainability

A complex system consisting of N modules that are logically interconnected for mission success is to be placed in the field for a fixed period of time. For some modules, standby units can be provided, for others this option is not available, but we must select from among several design alternatives differing in cost, weight, and reliability. The problem is to determine simultaneously the module designs and the numbers of standby units to maximize the system reliability, subject to cost and/or weight constraints. Other authors have considered a similar problem for a pure series inter-connection of modules, but we permit the system to be any configuration of modules in series and/or parallel. A dynamic programming model is presented for this problem. The notion of the generalized decomposition operator is used to develop a set of recursive relations. An example is included.     

Optimal Reliability of a Complex System

In a complex system where the redundant units cannot be reduced to a purely parallel or series configuration, the reliability is obtained by using Bayes' theorem. A mathematical model is formulated for the reliability of a system with nonlinear constraints. The system reliability is optimized based on the model and the solution is obtained by using the sequential unconstrained minimization technique (SUMT). This method is an efficient method for solving this type of problem. Two life support systems, one is the communication system of a two-man space capsule and another is a high-pressure oxygen supply system in a space capsule, have been identified to have the complex system configuration treated in this work.     

Identifying Optimal Components in a Reliability System

The first step in a reliability optimization process is to make a reliability assessment for each component in the system. If this assessment is made in a qualitative way, by grouping together components with the same reliability, and establishing a prevalence order among groups, is there a way to decide which components have the greatest Birnbaum measure without computing the exact value of this measure? In this paper, three relations between components are introduced and studied, and it is proved that they are useful for selecting the components that have the biggest effect on the system reliability in the sense of Birnbaum. An algorithm that uses the results in the paper to select these important components is also provided.     

Optimal Reliability Design of Process Systems

The optimal design of system reliability which takes into account the quantitative aspect of systems throughput or capacity is proposed. It is based on the concept of an r-out-of-n configuration instead of the conventional parallel 1-out-of-n configuration and is especially suitable for treating problems which arise in process systems. The problem is solved by the pseudo-Boolean programming method of Lawler and Bell.     

A Note on Heuristic Methods in Optimal System Reliability

Many optimization techniques have been used to solve redundancy allocation problems, most of which result in noninteger solutions. A few, including dynamic programming and integer programming, as well as a host of heuristic methods give integer solutions. This note critically reviews six promising heuristic approaches. The advantages and disadvantages of each of the approaches are discussed. An extended approach is presented which incorporates some of the ideas of the previous methods for solving a general non series-parallel system. The extended approach appears to be quite efficient and is general. The simplicity and efficiency of the approach will lend itself to solving large practical problems.     

A New Look at the Practical Design of Compact Diplexers

This paper presents a method for the design of compact diplexers, where the common junction is considered part of the filters, thus reducing the diplexer length by roughly one cavity. Starting from two filter prototypes satisfying the desired specifications, the technique provides the design equations in closed form. Effectiveness and accuracy of the proposed method are demonstrated by means of a practical example.     

A New Technique to Optimize System Reliability

This paper describes an algorithm for solving reliability optimization problems formulated as nonlinear binary programming problems with multiple-choice constraints. These constraints stand for restrictions in which only one variable is assigned to each subset making up the set; thus, they are expressed by equations whose r.h.s. is unity. Different types of methods for achieving high reliability (an increase in component reliability, parallel redundancy, standby redundancy, etc.) can be easily used simultaneously as design alternatives for each subsystem. In order to solve the problem effectively, the Lawler & Bell algorithm is improved by introducing a new lexicographic enumeration order which always satisfies the multiple-choice constraints. The function for obtaining feasible solutions which give first ~ L-th minimum values of the objective function is added to the algorithm in order to make it more useful for decision making. After a numerical example assists in understanding the algorithm, the computational efficiency is compared with that of the Lawler & Bell algorithm.     

Optimal System Reliability Parameters with Minimum Costs

This paper gives a procedure for a repairable complex system which will determine the failure and repair rates as well as the number of redundant components to achieve minimum total s-expected cost for a given availability. The total s-expected cost is the s-expected investment and operating costs. The capital investment cost function is related to the steady-state availability of each component and the operating cost function to the steady-state probability of the system's being in a particular state.     

A New Algorithm for Symbolic System Reliability Analysis

This paper presents a new algorithm for symbolic system reliability analysis. The method is applicable to system graphs with unreliable branches or nodes. Each branch is directed or undirected. Element probabilities need not be equal, but their failures are assumed to be s-independent. The new method makes no attempt to generate mutually exclusive events from the set of paths or cutsets but uses a technique to reduce greatly the number of terms in the reliability expression. Actual programming results show that the new method can efficiently handle systems having fewer than 20 paths or cutsets between the input-output node pair.     

Optimal Allocation of Effort to Improve System Reliability

The optimal allocation of development effort to improve reliability for systems of general, but fixed, structure is discussed from a deterministic standpoint and also when there is uncertainty in component reliabilities at various stages of development. A computational algorithm is given for implementing the optimal allocation, called the optimal policy, and the form of the solution is related to the special case of a series system when development effort functions are the same for all components. This methodology is a useful aid to decision-making about reliability improvements.     

IC卡电话密码锁的设计

介绍了应用ＩＣ卡技术对企事业单位的内部电话系统进行管理的方法，给出了ＩＣ卡电话密码锁的硬件电路和软件流程。     

Review of Optimal Reliability Design, Fundamentals and Applications

This reference covers the extent of the state-of-the-art in optimizing systems reliability. The book consists of fifteen chapters and an appendix. The main part of the book is organized by problem type and solution method. Some of the topics covered include: redundancy allocation methods using heuristics, dynamic programming solutions and discrete optimization methods; reliability optimization using nonlinear programming and meta-heuristic algorithms; and methods to solve reliability-redundancy optimization. The book may serve as a textbook for students or as a reference for researchers and practitioners. It is a comprehensive book that is recommended for anyone concerned with designing reliable systems.     

A New Look at Phase Sampling

There are 1173 AM radio stations in the United States using two or more towers. California leads the list with 101. Texas is next with 87, followed by Pennsylvania with 62, Florida with 61, and New York with 56. Rounding out the top ten are Michigan (52), Ohio (50), Illinois (45), North Carolina (34), and Indiana (33). As workable AM frequencies become more scarce, directional arrays are more complex and stability requirements more severe. A O.1 percent phase monitor, combined with the very best engineering practices in phasor design and tower and ground system installation, becomes an important part in an applicant's quest for a critical frequency. Since the early days of directionals, the sampling of tower currents has been accomplished through the use of loops placed on the tower, or with a tuned sampling transformer located at the base. Both systems have disadvantages, particularly when long-term stability is required. This paper will discuss a broadband untuned phase sampler-a current transformer-utilizing modern ferrites encapsulated in a simple tamper-proof assembly.     

A New Sample-Based Approach to Predict System Performance Reliability

Multiple degradation paths arise when systems operate under uncontrolled, uncertain environmental conditions at customers' hands in the field. This paper presents a design stage method for assessing performance reliability of systems with competing time-variant responses due to components with uncertain degradation rates. Herein, system performance measures (e.g. selected responses) are related to their critical levels by time dependent limit-state functions. System failure is defined as the non-conformance of any response, and hence unions of the multiple failure regions are formed. For discrete time, set theory establishes the minimum union size needed to identify a true incremental failure region that emerges from a safe region. A cumulative failure distribution function is built by summing incremental failure probabilities. A practical implementation of the theory is manifest through evaluating probabilities by Monte Carlo simulation. Error analysis suggests ways to predict and minimize errors. An electrical temperature controller shows the details of the method, and the potential of the approach. It is shown that the proposed method provides a more realistic way to predict performance reliability than either worst-case, or simple average-based approaches that are available in the open literature.     

一种新型飞机全静压检测系统的设计

介绍了以单片机为核心的一种新型飞机全静压检测系统的设计,给出了硬件电路和软件设计流程。     

MOMS-GA: A Multi-Objective Multi-State Genetic Algorithm for System Reliability Optimization Design Problems

A custom genetic algorithm was developed and implemented to solve multiple objective multi-state reliability optimization design problems. Many real-world engineering design problems are multi-objective in nature, and among those, several of them have various levels of system performance ranging from perfectly functioning to completely failed. This multi-objective genetic algorithm uses the universal moment generating function approach to evaluate the different reliability or availability indices of the system. The components are characterized by having different performance levels, cost, weight, and reliability. The solution to the multi-objective multi-state problem is a set of solutions, known as the Pareto-front, from which the analyst may choose one solution for system implementation. Two illustrative examples are presented to show the performance of the algorithm; and the multi-objective formulation considered for both of them is the maximization of system availability, and the minimization of both system cost, and weight.