Optimal imperfect preventive maintenance policies for a used system

In some practical situations, it may be more economical to work a used system than do a new one. From this viewpoint, this article considers three basic preventive maintenance (PM) policies for a used system: the system with initial variable damage Y ₀ begins to operate at time 0, and suffers damage due to shocks. It fails when the total damage exceeds a failure level K and corrective maintenance is made immediately. To prevent such failure, it undergoes PM at a planned time T, a shock number N and a damage level k, but maintenances are imperfect. However, failure rate of a used system maybe higher than that of a new one, so some maintenance is applied to the policies at each shock in the extended models. Using the theory of cumulative processes, expected cost rate models are obtained, optimal policies which minimise them are derived analytically and discussed numerically.     

Inspection strategy for availability improvement

In this paper, an inspection strategy is proposed for systems subject to random shocks and whose state is only known through inspection. The shocks magnitudes and times between shocks arrivals are random variables. Each shock induces an amount of damage to the system which is gradually weakened as damage accumulates. The system fails when the total damage exceeds some threshold level. The proposed inspection strategy suggests to inspect the system at predetermined times T₁, T₂,...T _k . If failure is detected, then the system is repaired to a state as good as new, otherwise, it is kept operating. The expression of the system availability is derived. A numerical procedure is developed to generate an inspection sequence which maximizes the system availability. The proposed strategy has been developed for some critical subsystems of trees harvesters. An illustrative example is provided.     

Optimisation of PM scheduling for multi-component systems – a simulated annealing approach

Proper planning of preventive maintenance (PM) is crucial in many industries such as oil transmission pipelines, automotive and food industries. A critical decision in the PM plans is to determine frequencies and types of maintenance actions in order to achieve a certain level of system availability with a minimum total cost. In this paper, we consider the problem of obtaining availability-based non-periodic optimal PM planning for systems with deteriorating components. The objective is to sustain a certain level of availability with the minimal total maintenance-related costs. In the proposed approach, the planning horizon is divided into some inspection periods of equal intervals. For any given interval, a decision must be made to perform one of the three actions on each component; inspection, preventive repair and preventive replacement. Any of these activities has different effects on the reliability of the components and the corresponding distinct costs based on the required recourses. The cost function includes the cost for repair, replacement, system downtime and random failures. System availability and PM resources are the main constraints considered. Since the proposed model is combinatorial in nature involving non-linear decision variables, a simulated annealing algorithm is employed to provide good solutions within a reasonable time.     

AT89C51单片机的智能空气净化系统设计

基于 AT89 C51单片机设计了一个智能空气净化系统,可以实时监测空气中 PM2.5有害物质浓度并在浓度超出限制时发出警报,并自动清除PM2.5.给出了系统的总体设计要求、系统主要模块、系统中传感器、控制电路以及除尘模块的主要构成.对该系统除尘效果的实验表明,该系统对清除PM2.5、净化空气有良好的效果.     

Optimal maintenance policy incorporating system level and unit level for mechanical systems

The study works on a multi-level maintenance policy combining system level and unit level under soft and hard failure modes. The system experiences system-level preventive maintenance (SLPM) when the conditional reliability of entire system exceeds SLPM threshold, and also undergoes a two-level maintenance for each single unit, which is initiated when a single unit exceeds its preventive maintenance (PM) threshold, and the other is performed simultaneously the moment when any unit is going for maintenance. The units experience both periodic inspections and aperiodic inspections provided by failures of hard-type units. To model the practical situations, two types of economic dependence have been taken into account, which are set-up cost dependence and maintenance expertise dependence due to the same technology and tool/equipment can be utilised. The optimisation problem is formulated and solved in a semi-Markov decision process framework. The objective is to find the optimal system-level threshold and unit-level thresholds by minimising the long-run expected average cost per unit time. A formula for the mean residual life is derived for the proposed multi-level maintenance policy. The method is illustrated by a real case study of feed subsystem from a boring machine, and a comparison with other policies demonstrates the effectiveness of our approach.     

A geometric process repair model for a two-component system with shock damage interaction

In this article, the repair-replacement problem for a two-component system with shock damage interaction and one repairman is studied. Assume that component 1 will be replaced as soon as it fails, and each failure of component 1 will induce a random shock to component 2. The shock damages may be accumulative, and whenever the total shock damage equals or exceeds a given threshold Δ, component 2 fails and the system breaks down. Component 2 is repairable, and it follows a geometric process repair. Under these assumptions, we consider a replacement policy N based on the number of failures of component 2. Our problem is to determine an optimal replacement policy N* such that the average cost rate (i.e. the long-run average cost per unit time) is minimised. The explicit expression of the average cost rate is derived by the renewal reward theorem, and the optimal replacement policy can be determined analytically or numerically. The existence and uniqueness of the optimal replacement policy N* is also proved under some mild conditions. Finally, two appropriate numerical examples are provided to show the effectiveness and applicability of the theoretic results in this article.     

New integration of preventive maintenance and production planning with cell formation and group scheduling for dynamic cellular manufacturing systems

This paper proposes a new integration method for cell formation, group scheduling, production, and preventive maintenance (PM) planning problems in a dynamic cellular manufacturing system (CMS). The cell formation sub-problem aims to form part families and machine groups, which minimizes the inter-cell material handling, under-utilization, and relocation costs. The production planning aspect is a multi-item capacitated lot-sizing problem accompanied by sub-contracting decisions, while the group scheduling problem deals with the decisions on the sequential order of the parts and their corresponding completion times. The purpose of the maintenance sub-problem is to determine the availability of the system and the time when the noncyclical perfect PM must be implemented to reduce the number of corrective actions. Numerical examples are generated and solved by Bender’s decomposition pack in GAMS to evaluate the interactions of the proposed model. Statistical analysis, based on a nonparametric method, is also used to study the behavior of the model’s cost components in two different situations. It is shown that by adding the PM planning decisions to the tactical decisions of the dynamic CMS, the optimal configuration and production plans of the system are heavily affected. The results indicate that omitting the PM actions increases the number of sudden failures, which leads to a higher total cost. Finally, it is concluded that the boost in the total availability of the dynamic CMS is one of the main advantages of the proposed integrated method.     

Quantitative synthesis of a five-loop plant-modification control system

Achievement of specified performance tolerances despite plant parameter uncertainty is one of the main reasons for using feedback in control. The effect of sensor noise at the plant input is used as a measure of the resulting ‘cost of feedback’. This cost can be too high if only the plant output is available. Previous studies have shown how the cost can be greatly reduced if internal variables can also be used, even if all feedback loops must be returned only to the plant input. In plant-modification (PM) feedback, such loops are allowed to be returned also to internal plant variables, causing increase in plant signal levels needed to produce the specified system output. It is then necessary to specify the maximum increases allowed. In this paper, a complex five-loop PM system is illustrated to give more insight into PM system design. It is shown that the cost is then reduced significantly more than in the non-PM designs.     

A bivariate optimal imperfect preventive maintenance policy for a used system with two-type shocks

This article studies an optimal imperfect preventive maintenance policy based on a cumulative damage model for a used system with initial variable damage. The used system is subject to shocks occurring to a non-homogeneous Poisson process, and suffers one of two types of shocks with stochastic probability: type-I shock (minor) yields a random amount of additive damage of the system, or type-II shock (catastrophic) causes the system to fail. A bivariate preventive maintenance schedule (n, T) is presented in which the system undergoes preventive maintenance at a planned time T and the nth type-I shock, or corrective maintenance at any type-II shock and the total damage exceeds a threshold level, whichever occurs first. The optimal preventive maintenance schedule which minimizes the expected cost rate is derived analytically and discussed numerically.     

Object‐oriented integration testing

Object‐oriented software development is an evolutionary process, and hence the opportunities for integration are abundant. Conceptually, classes are encapsulation of data attributes and their associated functions. Software components are amalgamation of logically and/or physically related classes. A complete software system is also an aggregation of software components. All of these various integration levels warrant contemporary integration techniques. Traditional integration techniques towards the end of software development process do not suffice any more. Integration strategies are needed at class level, component level, sub‐system level, and system levels. Classes require integration of methods. Various types of class interaction mechanisms demand different testing strategies. Integration of classes into components presses its own integration requirements. Finally, the system integration demands different types of integration testing strategies. This paper discusses the various integration levels prevalent in object‐oriented software development. The integration requirements of each level are met by suggesting a solution for the same. An integration framework for integrating classes into a system is also proposed. This revised version was published online in June 2006 with corrections to the Cover Date.     

Genetic fuzzy system for damage detection in beams and helicopter rotor blades

Structural damage detection is an inverse problem of structural engineering having three main parts: finding the existence, location and extent of damage. In this study, a genetic fuzzy system is used to find the location and extent of damage. A finite element model of a cantilever beam is used to calculate the change in beam frequencies because of structural damage. Using these changes in frequencies, a fuzzy system is generated and the rule-base and membership functions optimized by genetic algorithm. The output faults of the fuzzy system are four levels of damage (undamaged, slight, moderate, and severe) at five locations along the beam (root, inboard, center, outboard and tip). The genetic fuzzy system developed for a noise level of 0.20 in the data gives a fault isolation success rate of 99.81% when the first eight natural frequencies are used. With noise level of 0.15 and 0.10, accuracy rates of 100% are obtained even when only the first four natural frequencies are used. The fuzzy system also shows excellent robustness with missing measurements and degrades gradually in the presence of faulty sensors/measurements. The genetic fuzzy system allows easy rule generation for different structures and when the number of inputs and outputs increase, thereby avoiding the ‘curse of dimensionality’ that plagues fuzzy systems. Results with a non-uniform beam and a finer output set of damage at 10 locations in the beam also show excellent results. The genetic fuzzy system also gives very good results for BO-105 hingeless helicopter rotor blade for frequency as well as mode shape-based data. The genetic fuzzy logic system in this study is proposed as a method for automatic rule generation in fuzzy systems for structural damage detection.     

Network effects and embedded options: decision-making under uncertainty for network technology investments

The analysis of network effects in technology-based networks continues to be of significant managerial importance in e-commerce and traditional IS operations. Competitive strategy, economics and IS researchers share this interest, and have been exploring technology adoption, development and product launch contexts where understanding the issues is critical. This article examines settings involving countervailing and complementary network effects, which act as drivers of business value at several levels of analysis: the industry or market level, the firm or process level, the individual or product level, and the technology level. It leverages real options analysis for managerial decision-making under uncertainty across these contexts. We also identify a set of real options—compatibility, sponsorship and ownership option—which are unique to these settings, and which provide a template for managerial thinking and analysis when it is possible to delay an investment decision. We employ a hybrid jump-diffusion process to model countervailing and complementary network effects from the perspective of a user or a firm joining a network. We also do this from the perspective of a network developer. Our analysis shows that when countervailing and complementary network effects occur in the same network technology context, they give rise to real option value effects that may be used to control or modify the valuation trajectory of a network technology. The option value of waiting in these contexts jumps when the related business environment experiences shocks. Further, we find that the functional relationship between network value and the option value is not linear, and that taking into account a risk premium may not always result in a risk-neural investment. We also provide a managerial decision-making template through the different kinds of deferral options that we identify for this IT analysis context.

面向工程CAD的图形库设计

传统的图形库技术有两种：一是用户定制固定的图符;二是对图形分类,每一类图形对应一段程序,即图形库与程序库对应。文中在分析这两种图形库技术的基础上,提出了一种通用的图形库结构,该结构支持元件的参数化表示,支持元件的LOD表示,支持设计过程中元件全生命周期内的图形表述,并支持工程设计的项目管理等。     

Optimal number of minimal repairs with cumulative repair cost limit for a two-unit system with failure rate interactions

A discrete replacement model is presented that includes a cumulative repair cost limit for a two-unit system with failure rate interactions between the units. We assume a failure in unit 1 causes the failure rate in unit 2 to increase, whereas a failure in unit 2 causes a failure in unit 1, resulting in a total system failure. If unit 1 fails and the cumulative repair cost till to this failure is less than a limit L, then unit 1 is repaired. If there is a failure in unit 1 and the cumulative repair cost exceeds L or the number of failures equals n, the entire system is preventively replaced. The system is also replaced at a total failure, and such replacement cost is higher than the preventive replacement cost. The long-term expected cost per unit time is derived using the expected costs as the optimality criterion. The minimum-cost policy is derived, and existence and uniqueness are proved.     

Optimal testing policy for a computer system with fault margin

The periodic testing policy is considered, for a computer system which fails when the total number of hidden faults exceeds a threshold level N of tolerence. Periodic tests are scheduled at times kT(k = 1,2,[tdot]) to detect hidden faults. A fault occurs according to a non-homogeneous Poisson processes. When the ith fault occurs at age S_i < T, (i) it causes a system failure with probability p₁(S_i), (ii) it becomes a hidden fault with probability p₂(S_i) and is accumulated, or (iii) it is removed with probability p₃(S_i). The expected cost rate is derived. The aim of the paper is to find the optimal T which minimizes the expected cost rate per unit time of the policy. Various special cases are considered.     

An optimal production and inspection strategy with preventive maintenance error and rework

This study considers the integrated problem of production, preventive maintenance (PM), inspection, and inventory for an imperfect production process where rework and PM error exist. PM is performed when the process is in a controlled state. The correct implementation of PM results in a lower system failure rate, whereas a PM error results in the system shifting to the out-of-control state with a certain probability. The age of the system after PM is correlated with the level of PM performed. When the process in an out-of-control state produces a certain percentage of non-conforming items, we assume that a certain proportion of the non-conforming items can be reworked into conforming items. In a deteriorating production system, we determine the optimal inspection interval, inspection frequency, and production quantity that will yield the maximal unit expected profit. Numerical analyses are used to investigate the effectiveness of imperfect PM and to explore the effect of rework and PM error on profit.     

An exploration of the relationship between software development process maturity and project performance

Software projects have a high rate of failure. Organizations have tried to reduce the rate through methodological approaches but with little perceived success. A model of software development maturity (the capability maturity model (CMM)) describes managerial processes that can be used to attack software development difficulties from the managerial control perspective at five maturity levels. Our study examined performance of projects in relation to the activities at these various levels of maturity. A survey of software engineers indicated that the activities associated with the managerial control of development related positively to project performance measures. However, not each level of maturity demonstrated observable benefits, indicating that greater caution is needed in the planning and implementation of the activities.     

An Analysis of Swapping Policies in Virtual Storage Systems

An important resource allocation mechanism in virtual storage operating systems is the maintainence of the multiprogramming level in main storage, especially when some form of working-set storage management strategy is employed. Swapping of programs in and out of main memory occurs when sufficient storage becomes available and when total storage demand exceeds capacity. In this paper, we propose a class of swapping algorithms that couples storage management parameters with swapping decisions. An analytic model is developed and numerical results are presented to compare the performance of these algorithms.     

按单装配系统中组件生产和库存分配控制策略研究

针对由两种组件、三类顾客需求组成的按单装配系统, 本文研究了其中的组件生产控制与库存分配问题. 在各类顾客需 求是泊松到达过程, 各种组件加工时间服从指数分布的假设下, 我们运用马尔科夫决策理论建立了无限期折扣总成本模型, 根据Lippman转换得到了相应归一化后的离散最优方程, 在此基础之上分析了生产和库存分配联合最优控制策略的结构性质. 本文证明了最优策略是依赖于系统状态的动态策略. 组件的最优生产策略是动态基库存策略, 其中基库存水平是关于系统中其他组件库存水平的非减函数. 而最优的分配策略是动态的阈值策略, 对于只需一种组件构成的顾客需求, 组件的分配阈值是系统中另一组件库存水平的增函数; 而对于同时需要两种组件组成的顾客需求, 其各组件的分配阈值是另一组件库存水平的减函数. 最后通过数值试验给出了各个参数对联合最优控制策略的影响, 并得到了相应的管理启示.     

MatCarloRe: An integrated FT and Monte Carlo Simulink tool for the reliability assessment of dynamic fault tree

With the aim of a more effective representation of reliability assessment for real industry, in the last years concepts like dynamic fault trees (DFT) have gained the interest of many researchers and engineers (dealing with problems concerning safety management, design and development of new products, decision analysis and project management, maintenance of industrial plant, etc.). With the increased computational power of modern calculators is possible to achieve results with low modeling efforts and calculating time. Supported by the strong mathematical basis of state space models, the DFT technique has increased its popularity. Nevertheless, DFT analysis of real application has been more likely based on a specific case to case resolution procedure that often requires a great effort in terms of modeling by the human operator. Moreover, limitations like the state space explosion for increasing number of components, the constrain of using exponential distribution for all kind of basic events constituting any analyzed system and the ineffectiveness of modularization for DFT which exhibit dynamic gates at top levels without incurring in calculation and methodological errors are faces of these methodologies. In this paper we present a high level modeling framework that exceeds all these limitations, based on Monte Carlo simulation. It makes use of traditional DFT systemic modeling procedure and by replicating the true casual nature of the system can produce relevant results with low effort in term of modeling and computational time. A Simulink library that integrates Monte Carlo and FT methodologies for the calculation of DFT reliability has been developed, revealing new insights about the meaning of spare gates.