具有隐藏故障的多状态竞争失效系统检测策略研究

复杂工业系统的故障中有40%属于隐藏故障,若隐藏故障得不到及时消除,则可能导致巨大的经济损失。本文针对具有隐藏故障的多状态竞争失效系统,在考虑不完全检测的基础上,对其进行了维修建模。首先,基于制定的视情维修策略,分析了系统的更新情形;然后,基于所推导出的各种系统更新情形的发生概率,建立了以期望成本率为目标函数,以检测间隔时间为决策变量的维修模型。最后,以电容器组为例对所构建维修模型的适用性和有效性进行了验证,研究结果表明,检测质量对检测策略的制定有重要影响,因此研究具有隐藏故障的多状态竞争失效系统的检测策略时,有必要考虑检测误差。本文提出的维修建模方法不仅能在一定程度上丰富多状态竞争失效系统的维修策略理论与方法,还能为工程实际中复杂工业系统的维修工作提供理论基础与决策依据。     

Further results in the optimal policy for imperfect inspection in discrete time

The paper reports investigations into how the optimal inspection interval for a fallible system with imperfect inspection is best determined. This work can be viewed as an extension of Raz and Ladany's 1992 work on imperfect inspection in discrete time. Here the cost functions are rewritten to include a probability conditioning that was omitted. In addition, an upper bound on the search space for the optimal inspection interval is presented. This bound allows one to find the global optimum with very modest computational effort. Insights gained from this bound and from the computational tests are used to present some general properties of the system.     

自动生产线的同步维修模型及实例研究

自动生产线故障停机时间长、停机费用高,其原因在于:设备种类多且相关联,存在各设备协同维修的难题。首先,寻求生产线故障时间和检查时间之间的平衡点,建立检查周期与总停机时间之间关系的目标函数。其次,借鉴同步维修的"对故障隐患集中式批处理,减少分散维修的停机时间"思想,以及时间延迟维修理论,建立生产线的同步维修模型,该模型利用生产线每天停机次数、每次停机时间及检查时发现的缺陷数,计算出合理的生产线检查周期,并以此为依据制定维修计划,实现"提高维修批量,减少生产线停机时间"的目标。最后,实例研究。收集某生产线近十年的故障记录数据,在分析生产流程、设备布局、各设备停机影响的基础上,提出对策指导生产线维修管理。     

Sample Size Allocation for Food Item Radiation Monitoring and Safety Inspection

The objective of this study is to identify a procedure for determining sample size allocation for food radiation inspections of more than one food item to minimize the potential risk to consumers of internal radiation exposure. We consider a simplified case of food radiation monitoring and safety inspection in which a risk manager is required to monitor two food items, milk and spinach, in a contaminated area. Three protocols for food radiation monitoring with different sample size allocations were assessed by simulating random sampling and inspections of milk and spinach in a conceptual monitoring site. Distributions of ¹³¹I and radiocesium concentrations were determined in reference to ¹³¹I and radiocesium concentrations detected in Fukushima prefecture, Japan, for March and April 2011. The results of the simulations suggested that a protocol that allocates sample size to milk and spinach based on the estimation of ¹³¹I and radiocesium concentrations using the apparent decay rate constants sequentially calculated from past monitoring data can most effectively minimize the potential risks of internal radiation exposure.     

考虑故障停机的生产控制与维修计划联合决策模型

通过生产控制与维修计划协同决策,降低生产成本。首先描述生产过程,分析各项费用。其次,建立了考虑生产过程失控、故障率和故障停时间的生产过程控制、生产计划优化和维修管理联合优化决策的模型。通过模型求解,联合制定出生产过程检查策略、生产计划（经济生产批量、生产批次）以及维修计划（PM间隔期）,实现单位时间内总费用最低的目标。再次,案例研究,分析生产过程失控、故障率和故障停机时间对于经济生产批量、生产过程检查策略和生产系统维修计划的影响。该模型从理论上解决了生产过程控制、生产计划优化和维修管理联合优化决策难题,对于指导企业制定生产计划和生产系统的检修计划,进而提高产品质量、降低生产成本、确保准时交货都具有指导意义和实用价值。     

Inspecting a Vital Component Needed upon Emergency

We consider a stochastically failing component that will be needed at a random future time when an emergency occurs. If the component is not operational at that time, the system incurs a large penalty, which we want to avoid through inspections and replacements. We propose a model and solution algorithm for finding an inspection policy that minimizes the infinite horizon discounted expected penalty, replacement, and inspection costs. We also discuss structural properties of the solution, as well as insights based on numerical results.     

基于时间延迟理论的预防维修模型及案例研究

本文旨在解决设备维修决策过程中预防维修检查数据缺乏情况下如何确定出合理的维修间隔期问题。首先,通过预防维修技术经济分析,提出了有关维修间隔期和总的停机时间之间关系的预防维修模型。其次,根据时间延迟维修理论,利用故障记录数据和预防维修检查数据的估计值,建立了统计模型并用来计算维修间隔期内故障次数的期望值。计算机仿真检验证明统计模型正确后,采用最大拟然法估计有关参数,这些参数包括缺陷发生率、时间延迟分布、检查出缺陷的概率等。最后是案例分析,应用估计参数和预防维修模型,计算出最佳的维修间隔期。     

A Probabilistic Methodology for the Assessment of Safety from Dropped Loads in Offshore Engineering

Pipeline damage by dropped objects from crane activities is a significant hazard for offshore platform installations. In this paper a probabilistic methodology is utilized for the estimation of the pipeline impact and rupture frequencies; this information is obtained both for the overall pipeline section exposed to the hazard and for a number of critical locations along the pipeline route. The presented algorithm has been implemented in a computer program that allows the analysis of a large number of possible drop points and pipeline target point locations. This methodology may be used in common risk analysis studies for evaluating the risk for platform personnel from dropped objects; however, the proposed technique may also be useful for other applications where engineering judgment has so far been the main driving criterion. In particular, two sample cases have been analyzed. The first one is the problem of selecting the best approaching route to a platform. By analyzing different route alternatives, a reduction of the impact frequency and therefore of the risk for the platform personnel may be achieved. The second application deals with the selection of the location for a safety valve at the riser base. The analysis may give useful information, such as the highest impact frequency location and the rupture frequencies upstream and downstream of the valve as a function of the valve position; this information, together with the transported medium inventory upstream of the valve, may give the designer a documented and justifiable rationale for selecting the best location for the valve from a safety point of view.     

Contaminated consignment simulation to support risk-based inspection design

Invasive nonnative plant pests can cause extensive environmental and economic damage and are very difficult to eradicate once established. Phytosanitary inspections that aim to prevent biological invasions by limiting movement of nonnative plant pests across borders are a critical component of the biosecurity continuum. Inspections can also provide valuable information about when and where plant pests are crossing national boundaries. However, only a limited portion of the massive volume of goods imported daily can be inspected, necessitating a highly targeted, risk-based strategy. Furthermore, since inspections must prioritize detection and efficiency, their outcomes generally cannot be used to make inferences about risk for cargo pathways as a whole. Phytosanitary agencies need better tools for quantifying pests going undetected and designing risk-based inspection strategies appropriate for changing operational conditions. In this research, we present PoPS (Pest or Pathogen Spread) Border, an open-source consignment inspection simulator for measuring inspection outcomes under various cargo contamination scenarios to support recommendations for inspection protocols and estimate pest slippage rates. We used the tool to estimate contamination rates of historical interception data, quantify tradeoffs in effectiveness and workload for inspection strategies, and identify vulnerabilities in sampling protocols as changes in cargo configurations and contamination occur. These use cases demonstrate how this simulation approach permits testing inspection strategies and measuring quantities that would otherwise be impossible in a field-based setting. This work represents the first steps toward a decision support tool for creating dynamic inspection protocols that respond to changes in available resources, workload, and commerce trends.     

Integrating Software into PRA: A Software-Related Failure Mode Taxonomy

Probabilistic risk assessment is a methodology to assess the probability of failure or success of a mission. Results provided by the risk assessment methodology are used to make decisions concerning choice of upgrades, scheduling of maintenance, decision to launch, etc. However, current PRA neglects the contribution of software to the risk of failure of the mission. Our research has developed a methodology to account for the impact of software to system failure. This article focuses on an element of the approach: a comprehensive taxonomy of software-related failure modes. Application of the taxonomy is discussed in this article. A validation of the taxonomy and conclusions drawn from this validation effort are described. Future research is also summarized.     

Quality Management in Multi‐Level Supply Chains with Outsourced Manufacturing

Outsourcing stretches supply chains longer with added contract manufacturers responsible for the manufacturing of parts and final products. Should a firm change its quality management approach as its supply chain becomes longer with outsourced manufacturing? This paper studies a brand owner's optimal choice between two commonly used quality management approaches: an inspection‐based approach and an external failure‐based approach, in two supply chains – a dyadic supply chain and a multi‐level supply chain where the brand owner outsources manufacturing to an independent contract manufacturer. Our study finds that the brand owner's optimal choice between the two quality management approaches could be opposite in the two supply chains. Specifically, we show that if agency costs exist between the contract manufacturer and the brand owner, the brand owner may prefer an inspection‐based approach in the multi‐level supply chain in contrast to preferring an external failure‐based approach in the dyadic supply chain. In particular, inspections can be effective for the brand owner to limit the manufacturer's profit by excluding defective finished products and components, which in turn reduce agency costs in the multi‐level supply chain. Hence, the efficiency of an inspection‐based approach relative to an external failure‐based approach can be higher in the multi‐level supply chain as compared to the dyadic one. Our findings suggest that firms should adjust to changes in supply chain structures and re‐evaluate the efficiencies of different quality management approaches accordingly.     

Planning Replacement of Natural Gas Distribution Systems Under Constraints on Acceptable Risk from Explosions

Natural gas distribution systems in the United States were developed primarily in the first half of this century, utilizing materials such as cast iron and then steel. Over time, cast iron and steel pipe sections became weak from corrosion and are subject to failure which in turn can lead to explosions and possible injury and loss of life. Gas utilities maintain system integrity through repair-replacement programs where pipe sections are prioritized for replacement in any given year through cost-benefit analysis; however, the total annual amount to be budgeted for replacement is left to engineering judgment. This approach has left some utilities vulnerable to criticism that their current replacement rate on cast iron pipe is not great enough and that public safety is being compromised. This paper addresses the problem situation by formulating a linear programming replacement decision model which augments cost-benefit analysis with explicit constraints on acceptable risk to human life from fire/explosion. The model is illustrated for a hypothetical utility.     

“双随机、一公开”产品质量监管模型研究

在市场监管领域全面推行“双随机、一公开”监管，是党中央、国务院作出的重大决策部署，是市场监管理念和方式的重大创新。本文首次构建“双随机、一公开”产品质量监管的理论模型，理清“双随机”与“一公开”及各参与主体之间的作用关系，分析市场主体名录库和执法检查人员名录库中抽查企业与检查人员的群体行为演化机理，得出针对“双随机、一公开”监管的激励机制。研究发现：通过“双随机”抽取检查人员和抽查企业并“公开”产品质量信息，需配以恰当的激励机制才能有效制约抽检企业的假冒伪劣行为和检查人员的无效抽检行为；当公开声誉较高时，对检查人员实施质检激励或对抽查企业实施质量激励均可以使得系统良性演化，但如果公开声誉较低，需同时对检查人员和抽查企业实施质检与质量双重激励；质检激励机制设计时需对标准质量和假冒伪劣对应的检查人员分别给予质检激励，质量激励机制设计时需对有效抽检和无效抽检对应的抽查企业分别给予质量激励；质检激励和质量激励下系统稳定点的演化轨迹存在很大差异，质检激励先使得检查人员演化到有效抽检，然后通过公开声誉带动抽查企业演化到标准质量，而质量激励先使抽查企业演化到标准质量，然后通过公开声誉带动检查人员演化到有效抽检，如果公开声誉较低，这种传动机制会被阻断导致系统不会演化到理想状态。最后本文为完善和创新“双随机、一公开”监管提出了针对性的政策建议。     

Risk of Extreme Events Under Nonstationary Conditions

The concept of the return period is widely used in the analysis of the risk of extreme events and in engineering design. For example, a levee can be designed to protect against the 100-year flood, the flood which on average occurs once in 100 years. Use of the return period typically assumes that the probability of occurrence of an extreme event in the current or any future year is the same. However, there is evidence that potential climate change may affect the probabilities of some extreme events such as floods and droughts. In turn, this would affect the level of protection provided by the current infrastructure. For an engineering project, the risk of an extreme event in a future year could greatly exceed the average annual risk over the design life of the project. An equivalent definition of the return period under stationary conditions is the expected waiting time before failure. This paper examines how this definition can be adapted to nonstationary conditions. Designers of flood control projects should be aware that alternative definitions of the return period imply different risk under nonstationary conditions. The statistics of extremes and extreme value distributions are useful to examine extreme event risk. This paper uses a Gumbel Type I distribution to model the probability of failure under nonstationary conditions. The probability of an extreme event under nonstationary conditions depends on the rate of change of the parameters of the underlying distribution.     

Optimal policy for imperfect inspection in discrete time

Abstract

The problem of finding the optimal inspection interval for a fallible system that operates in discrete time when inspection is subject to errors was addressed. A Markov chain model of the system state was developed to formulate the objective function, which is the minimum expected total cost per lime unit. A numerical search procedure was used to find local minima for a representative range of parameter values. The objective function turned out to be quite insensitive to deviations in the inspection interval in the neighbourhood of the minimum, so an approximate method based on curve fitting was developed and tested, yielding good results in the representative range.     

Incorporation of Pharmacokinetics in Noncancer Risk Assessment: Example with Chloropentafluorobenzene

Noncancer risk assessment traditionally relies on applied dose measures, such as concentration in inhaled air or in drinking water, to characterize no-effect levels or low-effect levels in animal experiments. Safety factors are then incorporated to address the uncertainties associated with extrapolating across species, dose levels, and routes of exposure, as well as to account for the potential impact of variability of human response. A risk assessment for chloropentafluorobenzene (CPFB) was performed in which a physiologically based pharmacokinetic model was employed to calculate an internal measure of effective tissue dose appropriate to each toxic endpoint. The model accurately describes the kinetics of CPFB in both rodents and primates. The model calculations of internal dose at the no-effect and low-effect levels in animals were compared with those calculated for potential human exposure scenarios. These calculations were then used in place of default interspecies and route-to-route safety factors to determine safe human exposure conditions. Estimates of the impact of model parameter uncertainty, as estimated by a Monte Carlo technique, also were incorporated into the assessment. The approach used for CPFB is recommended as a general methodology for noncancer risk assessment whenever the necessary pharmacokinetic data can be obtained.     

Integrating Software into PRA: A Test-Based Approach

Probabilistic risk assessment (PRA) is a methodology to assess the probability of failure or success of a system's operation. PRA has been proved to be a systematic, logical, and comprehensive technique for risk assessment. Software plays an increasing role in modern safety critical systems. A significant number of failures can be attributed to software failures. Unfortunately, current probabilistic risk assessment concentrates on representing the behavior of hardware systems, humans, and their contributions (to a limited extent) to risk but neglects the contributions of software due to a lack of understanding of software failure phenomena. It is thus imperative to consider and model the impact of software to reflect the risk in current and future systems. The objective of our research is to develop a methodology to account for the impact of software on system failure that can be used in the classical PRA analysis process. A test-based approach for integrating software into PRA is discussed in this article. This approach includes identification of software functions to be modeled in the PRA, modeling of the software contributions in the ESD, and fault tree. The approach also introduces the concepts of input tree and output tree and proposes a quantification strategy that uses a software safety testing technique. The method is applied to an example system, PACS.     

Optimal Inspection of Imports to Prevent Invasive Pest Introduction

The United States imports more than 1 billion live plants annually—an important and growing pathway for introduction of damaging nonnative invertebrates and pathogens. Inspection of imports is one safeguard for reducing pest introductions, but capacity constraints limit inspection effort. We develop an optimal sampling strategy to minimize the costs of pest introductions from trade by posing inspection as an acceptance sampling problem that incorporates key features of the decision context, including (i) simultaneous inspection of many heterogeneous lots, (ii) a lot‐specific sampling effort, (iii) a budget constraint that limits total inspection effort, (iv) inspection error, and (v) an objective of minimizing cost from accepted defective units. We derive a formula for expected number of accepted infested units (expected slippage) given lot size, sample size, infestation rate, and detection rate, and we formulate and analyze the inspector's optimization problem of allocating a sampling budget among incoming lots to minimize the cost of slippage. We conduct an empirical analysis of live plant inspection, including estimation of plant infestation rates from historical data, and find that inspections optimally target the largest lots with the highest plant infestation rates, leaving some lots unsampled. We also consider that USDA‐APHIS, which administers inspections, may want to continue inspecting all lots at a baseline level; we find that allocating any additional capacity, beyond a comprehensive baseline inspection, to the largest lots with the highest infestation rates allows inspectors to meet the dual goals of minimizing the costs of slippage and maintaining baseline sampling without substantial compromise.     

基于贝叶斯网络的航空安全中不安全信息分析

针对航空安全中收集到的不安全信息,本文将安全检查发现的问题进行了分类,建立了民航安全检查的故障树模型,同时利用故障树模型进行了最小割集、结构重要度的定性分析。然后利用贝叶斯网络的学习能力结合故障树模型最终构建了民航安全检查贝叶斯网络模型,基于某航空公司安全检查发现问题的数据并利用贝叶斯网络的双向推理计算得到各影响因素对不安全事件的影响程度和不安全事件发生时各影响因素的重要程度。基于民航安全检查贝叶斯网络模型分析,本文得出个体原因、设施不完善、信息沟通因素最易导致工作流程管理中发现问题;管理流程、知识技能不足最易导致人员管理中发现问题;个体原因、培训、设备故障最易导致设备管理中发现问题。