Reliability analysis of electronic devices with multiple competing failure modes involving performance aging degradation

This paper presents an extension of reliability analysis of electronic devices with multiple competing failure modes involving performance aging degradation. The probability that a product fails on a specific mode is derived. Using this probability, the dominant failure mode on the product can be predicted. A practical example is presented to analyze an electronic device with two kinds of major failure modes–solder/Cu pad interface fracture (a catastrophic failure) and light intensity degradation (a degradation failure). Reliability modeling of an individual failure mode and device reliability analysis is presented and results are discussed. Copyright © 2003 John Wiley & Sons, Ltd.     

Analysis of investments in autonomous maintenance activities

In this paper, we model the situation where operator maintenance activities improve the failure process of equipment. We analyze the business decision to reduce both the mean and variance of the production cycle time and the overall inventory level through an investment in planned autonomous maintenance. We answer: (i) when do optimal autonomous maintenance decisions most improve inventory levels?; and (ii) how do capacity restrictions, equipment characteristics the maintenance response function, and product characteristics impact the autonomous maintenance investment decision? Extensive numerical analyses are performed to develop an approximation to the optimal response for both inventory and autonomous maintenance investments over a wide range of problem parameters. Our solutions provide guidelines on how much time should be invested in autonomous maintenance activities and describe when companies can most benefit from autonomous maintenance programs that increase equipment reliability. We determine the investment in autonomous maintenance activities as a function of available capacity, equipment reliability and demand characteristics.     

On preventive maintenance policy of a critical reliability level for system subject to degradation

Conventional preventive maintenance (PM) policies generally hold same time interval for PM actions and are often applied with known failure modes. The same time interval will give unavoidably decreasing reliabilities at the PM actions for degradation system with imperfect PM effect and the known failure modes may be inaccurate in practice. Therefore, field managers would prefer policy with an acceptable reliability level to keep system often at a good state.A PM policy with the critical reliability level is presented to address the preference of field managers. Through assuming that system after a PM action starts a new failure process, a parameter so-called degradation ratio is introduced to represent the imperfect effect. The policy holds a law that there is same number of failures in the time intervals of various PM cycles, and same degradation ratio for the system reliability or benefit parameters such as the optimal time intervals and the hazard rates between the neighboring PM cycles. This law is valid to any of the failure modes that could be appropriately referred as a ‘general isodegrading model’, and the degradation ratio as a ‘general isodegrading ratio’. In addition, life cycle availability and cost functions are derived for system with the policy. An analysis of the field data of a loading and unloading machine indicates that the reliability, availability and cost in life cycle might be well modeled by the present theory and approach.     

面向维修的机械系统可靠度预测与仿真研究

机电产品在服役期间因零件失效而产生故障,重组维修破坏了原有的系统可靠性模型,因而需要对设备可靠性问题重新进行研究和评价。基于机电系统中零件的失效时间分布密度函数,研究了在重组维护过程中机电系统服役期间零件年龄结构的分布规律,发展了机电系统可靠性数学模型。通过仿真研究,探讨了系统服役期间年龄结构、可靠度和失效率的发展规律,定量地研究了失效时间分布密度函数的参数对系统可靠度的影响。这对于评估机械系统的可靠性和全生命周期的失效率,制定合理的维修策略具有重要意义。     

Modelling maintenance effects on manufacturing equipment performance: results from simulation analysis

Equipment maintenance and system reliability are important factors affecting the organisation’s ability to provide quality and timely services to customer. While maintenance remains an important function to manufacturing, it is only recently that attempts have been made to quantify its impact on equipment performance. In this research, an approach of linking maintenance with equipment performance is developed using simulation modelling. The modelling approach involves defining probabilistic models and assumptions affecting system performance, such as: the probabilistic model for the initial failure rate/intensity of the equipment; the probabilistic model for the system deterioration and corresponding effect; the probabilistic model for the random times of corrective maintenance (CM) and preventive maintenance (PM) that takes into the account the types of maintenance plans/policies and the potential dependency between CM and PM times; and the probabilistic model for the random effects of CM and PM on the reliability of the equipment. Using a continuous manufacturing equipment, the model is used to analyse the impact of deterioration, failures and maintenance (policies, timing and efficiency) on equipment performance. It is shown that modelling the effect maintenance provides a basis of evaluating maintenance efforts with the potential application in performance evaluation and decision support while investigating opportunities for manufacturing equipment performance improvement.     

Periodic imperfect preventive maintenance with two categories of competing failure modes

A maintenance policy is studied for a system with two types of failure modes: maintainable and non-maintainable. The quality of maintenance actions is modelled by its effect on the system failure rate. Preventive maintenance actions restore the system to a condition between as good as new and as bad as immediately before the maintenance action. The model presented permits to study the equipment condition improvement (improvement factor) as a function of the time of the preventive maintenance action. The determination of the maintenance policy, which minimizes the cost rate for an infinite time span, is examined. Conditions are given under which a unique optimal policy exists.     

汽车运输经济性分析实例

通过对钢厂特种车辆设备不同车型的运行状态和成本的分析,研究了车辆作业量和维修成本等关系,揭示车型在钢厂的适用性和可靠性.运用设备经济性运行的手段,建立分析标准对车辆进行综合评估,为钢厂特种设备的选型、维修模式、报废周期、标准成本等提供决策依据,以使特种车辆实现经济运行、价值效益最大.     

Reliability analysis of standby systems with multi‐state elements subject to constant transition rates

Standby redundancy has been extensively applied to critical engineering systems to enhance system reliability. Researches on reliability evaluation for standby systems focus more on systems with binary‐state elements. However, multi‐state elements with different performances have played a significant role in engineering systems. This paper presents an approach for reliability analysis of standby systems composed of multi‐state elements with constant state transition rates and absorbing failure states. The approach allows modelling different standby systems beyond cold, warm and hot ones by taking into account differences in possible maintenance of elements in standby and operation modes and dependence of elements' operational behavior on their initial state at the time of activation. An iterative algorithm for reliability evaluation based on element state probabilities is suggested. Illustrating examples of evaluating reliability of different types of homogeneous and heterogeneous standby systems are demonstrated.     

一种综合赋权的改进FMEA风险评估方法

针对传统故障模式和影响分析(failure mode and effects analysis, FMEA)方法中的未考虑风险因子权重以及风险因子权重难确定这一问题,提出一种综合赋权的改进FMEA风险评估方法。该方法首先通过FMEA团队明确评估对象和FMEA范围,然后列出所有潜在故障模式,对故障模式进行打分,得到所有的专家打分评估表,再通过语言变量转化为直觉模糊数。由层次分析法确定主观权重,由数据本身确定客观权重,使用直觉模糊混合加权算子(intuitionistic fuzzy hybrid weighted, IFHW)算子集结评价信息,得到所有的故障模式的得分函数,最后基于风险最大化选取每个故障模式的最大分数,进行排名,得到最终的故障模式风险顺序。通过对静电纺丝设备进行FMEA分析,并与其他方法进行比较,验证了所提方法的可行性。     

基于AR模型的Kolmogorov-Smirnov检验性能退化及预测研究

设备性能退化评估是对现有故障诊断技术的全新拓展,它为更有效地实现智能主动维护提供参考,更有利于实现设备的零停机率。开展对设备的性能退化评估研究,还可以实现对设备的性能预测维护功能,大大提高设备运行的可靠性。提出了基于AR预测白噪化的Kolmogorov-Smirnov检验方法,同时实现了滚动轴承的全寿命实验。通过对轴承全寿命实验数据的分析研究,论证了本方法在设备性能退化评估及预测中的研究价值,相对于有效值等传统方法,它不仅能够显著地表现前期的微弱退化状态,而且还能有条件地更早指示设备的异常状态,对于故障预测的研究具有较大的意义。     

以可靠性为中心的维修方法及其在隧道中的应用

本文针对目前隧道监控维修状况及存在的问题,提出以可靠性为中心的维修(RCM)作为维修理念,并将其引入到隧道管理中,对隧道设备的故障模式及可靠性进行分析,并对RCM方法在隧道监控维修中的应用做了初步研究。最后通过案例说明,隧道采用RCM方法可有效降低维修费用,具有一定的经济效益和社会效益。     

A corrective maintenance scheme for engineering equipment

Corrective maintenance is a maintenance task performed to identify and rectify the cause failures for a failed system. The engineering equipment gets many components and failure modes, and its failure mechanism is very complicated. Failure of system-level might occur due to failure(s) of any subsystem/component. Thus, the symptom failure of equipment may be caused by multilevel causality of latent failures.This paper proposes a complete corrective maintenance scheme for engineering equipment. Firstly, the FMECA is extended to organize the numerous failure modes. Secondly, the failure propagation model (FPM) is presented to depict the cause-effect relationship between failures. Multiple FPMs will make up the failure propagation graph (FPG). For a specific symptom failure, the FPG is built by iteratively searching the cause failures with FPM. Moreover, when some failure in the FPG is newly ascertained to occur (or not), the FPG needs to be adjusted. The FPG updating process is proposed to accomplish the adjustment of FPG under newly ascertained failure. Then, the probability of the cause failures is calculated by the fault diagnosis process. Thirdly, the conventional corrective maintenance recommends that the failure with the largest probability should be ascertained firstly. However, the proposed approach considers not only the probability but also the failure detectability and severity. The term REN is introduced to measure the risk of the failure. Then, a binary decision tree is trained based on REN reduction to determine the failure ascertainment order. Finally, a case is presented to implement the proposed approach on the ram feed subsystem of a boring machine tool. The result proves the validity and practicability of the proposed method for corrective maintenance of engineering equipment.     

An adaptive degradation‐based maintenance model taking into account both imperfect adjustments and AGAN replacements

This paper presents an adaptive maintenance model for equipment that can be adjusted (minor preventive maintenance, imperfect state) or replaced (major preventive maintenance, as good as new) at specific scheduled times based on degradation measurements. An initial reliability law that uses a degradation‐based model is built from the collection of hitting times of a failure threshold. Inspections are performed to update the reliability, the remaining useful life, and the optimum time for preventive maintenance. The case of both as good as new replacements and imperfect adjustments is considered. The proposed maintenance model is based on the optimization of the long‐term expected cost per unit of time. The model is then tested on a numerical case study to assess its effectiveness. This results in an improvement for the occurrences of maintenance tasks that minimizes the mean cost per unit of time as well as an optimized number of adjustments that can be considered before replacing an item. The practical application is a decision aid support to answer the 2 following questions: Should we intervene now or wait for the next inspection? For each intervention, should we adjust or replace the item of equipment? The originality is the presence of 2 criteria that help the maintainer to decide to postpone or not the preventive replacement time depending on the measured degradation and to decide whether the item should be adjusted or replaced.     

Calculation of optimum proof test intervals for maximum availability

Failure mode and effect analysis (FMEA) is often performed when assessing equipment reliability. Some failure modes can occur that are only revealed when a demand is placed upon the system, thus causing a hazard. Such failures are only detectable by regular proof testing of the system. Availability calculations generally do not take into consideration down-time caused by the duration of such proof tests. Testing of a large system is both laborious and time consuming, and may cause either partial or total system unavailability. Microprocessor based equipment reduces the duration of this task, but the question arises of how often?' The following method shows how the optimum proof test interval can be determined based on Markovian reliability models. It should be borne in mind that figures used in reliability prediction should not be considered to be precise data. Such figures should be treated as approximations for comparative use only. The purpose of this paper is to provide a guide for use by engineers involved in reliability/availability prediction; it serves to replace intuitive decisions.     

Structure optimization of multi-state system with two failure modes

When systems with two failure modes (STFM) are considered, introducing redundant elements may either increase or decrease system reliability. Therefore the problem of system structure optimization arises. In this paper we consider systems consisting of elements characterized by different reliability and nominal performance rates. Such systems are multi-state because they can have different levels of output performance depending on the combination of elements available at the moment. The algorithm that determines the structure of multi-state STFM, which maximizes system reliability and/or expected performance is presented. In this algorithm, system elements are chosen from a list of available equipment. Reliability is defined as the probability of satisfaction of given constraints imposed on system performance in both modes.The procedure developed to solve this problem is based on the use of a universal moment generating function (UMGF) for the fast evaluation of multi-state system reliability and a genetic algorithm for optimization. Basic UMGF technique operators are developed for two different types of systems, based, respectively, on transmitting capacity and on processing time. Examples of the optimization of series–parallel structures of both types are presented.     

Establishment and Analysis of the Fault Tree for the Oil Transfer Pump System in CNPC Work Zone

The reliability of the equipment is very important for the large petrochemical industry, especially for oil pump as the core component of driving equipment. In order to reduce the loss of the enterprise brought by equipment failure, it is need to find those reasons which may lead to equipment failure and take some preventive measures as early as possible. This article analyzes the failure of the oil transfer pump system in CNPC work zone systematically, qualitatively and quantitatively, using the fault tree analysis method. Then 105 groups of minimal cut sets are found, and the probability of system failure after a certain time operation is calculated by using Weibull distribution. Combined with specific requirements of reliability, the work zone may make a scientific decision of plant maintenance cycle according to the conclusion.     

Structural integrity in electronics

With continuing miniaturisation, increased performance demands and the requirement to remove lead from solder alloys, the challenges to structural integrity and reliability of electronic equipment are substantial and increasing. This paper outlines typical features in electronic equipment of which the structural integrity community may be generally unaware. Potential failure modes in service are described, and the problems of scale and material characteristics are considered. Progress in the application of fracture mechanics to the life prediction of interconnections is reviewed. The limited evidence available suggests that the crack growth resistance of silver‐containing lead‐free solders is superior to that of the traditional Sn‐37Pb under cycle‐controlled conditions but there is no difference when time‐dependent conditions prevail. In several respects, it is contended that the electronics sector is faced with challenges at least equivalent to those encountered in gas turbines and nuclear power generation.     

Reliability improvement through alternative designs—A case study

In today's competitive world, reliability of equipment is extremely important to maintain quality and delivery deadlines. This is achieved by using proper maintenance and design changes for unreliable subsystems and components of a complex system. It is significant to develop a strategy for maintenance, replacement and design changes related to those subsystems and components. An analysis of down time along with causes is essential to identify the unreliable components and subsystems.This paper presents an analysis of failure data of solenoid coils of automatic internal grinding machine used in a bearing manufacturing plant. It analyses various replacement and change of design options such as introduction of pneumatic system in place of electromagnetic solenoids for improvement of reliability of the plunger movement mechanism.     

Risk-based maintenance of ethylene oxide production facilities

This paper discusses a methodology for the design of an optimum inspection and maintenance program. The methodology, called risk-based maintenance (RBM) is based on integrating a reliability approach and a risk assessment strategy to obtain an optimum maintenance schedule. First, the likely equipment failure scenarios are formulated. Out of many likely failure scenarios, the ones, which are most probable, are subjected to a detailed study. Detailed consequence analysis is done for the selected scenarios. Subsequently, these failure scenarios are subjected to a fault tree analysis to determine their probabilities. Finally, risk is computed by combining the results of the consequence and the probability analyses. The calculated risk is compared against known acceptable criteria. The frequencies of the maintenance tasks are obtained by minimizing the estimated risk. A case study involving an ethylene oxide production facility is presented. Out of the five most hazardous units considered, the pipeline used for the transportation of the ethylene is found to have the highest risk. Using available failure data and a lognormal reliability distribution function human health risk factors are calculated. Both societal risk factors and individual risk factors exceeded the acceptable risk criteria. To determine an optimal maintenance interval, a reverse fault tree analysis was used. The maintenance interval was determined such that the original high risk is brought down to an acceptable level. A sensitivity analysis is also undertaken to study the impact of changing the distribution of the reliability model as well as the error in the distribution parameters on the maintenance interval.