When Does Poor Governance Presage Biosecurity Risk?

Border inspection, and the challenge of deciding which of the tens of millions of consignments that arrive should be inspected, is a perennial problem for regulatory authorities. The objective of these inspections is to minimize the risk of contraband entering the country. As an example, for regulatory authorities in charge of biosecurity material, consignments of goods are classified before arrival according to their economic tariff number. This classification, perhaps along with other information, is used as a screening step to determine whether further biosecurity intervention, such as inspection, is necessary. Other information associated with consignments includes details such as the country of origin, supplier, and importer, for example. The choice of which consignments to inspect has typically been informed by historical records of intercepted material. Fortunately for regulators, interception is a rare event; however, this sparsity undermines the utility of historical records for deciding which containers to inspect. In this article, we report on an analysis that uses more detailed information to inform inspection. Using quarantine biosecurity as a case study, we create statistical profiles using generalized linear mixed models and compare different model specifications with historical information alone, demonstrating the utility of a statistical modeling approach. We also demonstrate some graphical model summaries that provide managers with insight into pathway governance.     

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.     

The optimum targeting for a single filling operation with rectifying inspection

One of the important issues in quality control is finding the optimal target value for a process under various inspection policies. Researchers have considered various aspects of this problem with 100% inspection and with quality sampling plans. In this paper we consider the problem of targeting the set point when rectifying inspection is used. We develop a model for this problem and propose a scheme for solving it. We also provide a numerical example.     

供应链质量管理中抽样检验决策的非合作博弈分析

保证产品质量是建立与维护供应链企业间长期稳定合作关系的重要基础.本文提出一种供应链质量管理中抽样检验决策的非合作博弈模型,以分析供应链的下游制造商应如何根据供应商产品的质量水平确定其抽检方案.仿真结果表明,供应链背景下抽检方案不同于单个企业各自优化的制造商抽检方案.考虑供应链企业间互动关系的抽检方案与不考虑这种关系的独立抽检方案相比,能有效降低抽样成本,并使供应商和制造商获得更大的期望收益.     

社会共治下的食品企业失信经营问题三方演化博弈研究

针对食品企业失信经营的问题,借鉴日常活动理论,从机会、动机和控制方法三个方面,对企业失信经营进行了分析。在监管机构传统监管与共治监管两种方式下,基于演化博弈方法,构建了食品企业、消费者、监管机构的三方演化博弈模型。依据企业失信经营获利的大小,从博弈均衡上对食品企业失信经营问题进行了研究,并运用Matlab对博弈模型进行了分析验证。通过对两种监管方式的效率和应用范围进行深入分析,研究结果表明处罚和赔偿可有效降低食品企业失信经营的动机;当企业失信经营动机较小时,传统监管方式即可有效威慑食品企业,从而使其选择诚信经营策略;当企业失信动机较大时,即便使用共治监管方式仍无法有效监管食品企业失信经营。     

Bias‐Corrected Estimation in Continuous Sampling Plans

Continuous sampling plans (CSPs) are algorithms used for monitoring and maintaining the quality of a production line. Although considerable work has been done on the development of CSPs, to our knowledge, there has been no corresponding effort in developing estimators with good statistical properties for data arising from a CSP inspection process. For example, information about the failure rate of the process will affect the management of the process, both in terms of selecting appropriate CSP parameters to keep the failure rate after inspection at a suitable level, and in terms of policy, for example, whether the process should be completely inspected, or shut down. The motivation for this exercise was developing sampling protocols for Australia's Department of Agriculture and Water Resources for monitoring the biosecurity compliance of incoming goods at international borders. In this study, we show that maximum likelihood estimation of the failure rate under a sampling scheme can be biased depending on when estimation is performed, and we provide explicit expressions for the main contribution of the bias under various CSPs. We then construct bias‐corrected estimators and confidence intervals, and evaluate their performance in a numerical study.     

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.     

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.     

“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。     

Optimal two-stage production-inventory policy with whole lot and split lots

This paper deals with the problem of determining the optimal lot sizes for a two-stage production-inventory system. The first stage has a large lot to be processed in a single batch and is called the ‘whole lot’; this is split in the second stage into smaller lots of equal size called ‘split lots’. The lot in stage 1 is inspected for its conformity to standards before it is passed on to stage 2. We use a single sampling attribute plan for inspection and examine the consequences of rejecting or accepting the lot. The rejected lots are 100 % inspected and defectives are eliminated..The accepted lots contain defectives in the uninspected part which are identified during stage 2 processing. We have combined these aspects of inspection with the usual inventory costs and developed a model to determine the optimal sizes of the whole lot and split lots     

Sourcing with Deferred Payment and Inspection under Supplier Product Adulteration Risk

We study the deferred payment and inspection mechanisms for mitigating supplier product adulteration, with endogenous procurement decision and general defect discovery process. We first derive the optimal deferred payment contract, which reveals that either entire or partial deferral can arise, depending on the moral hazard severity and the information accumulation rate. Because of the supplier's incentive to adulterate, the optimal procurement quantity under deferred payment generally is smaller than the first‐best quantity. We then investigate the inspection mechanism and characterize the equilibrium. We find that under the inspection mechanism, the optimal procurement quantity is no less than the first best. A comparison between these two mechanisms shows that the deferred payment mechanism generally can outperform the inspection mechanism when either the market size is small or the profit margin is low. However, we find that these two mechanisms can also be complementary, for which we characterize a necessary condition.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.     

Time‐Series Models for Border Inspection Data

We propose a new modeling approach for inspection data that provides a more useful interpretation of the patterns of detections of invasive pests, using cargo inspection as a motivating example. Methods that are currently in use generally classify shipments according to their likelihood of carrying biosecurity risk material, given available historical and contextual data. Ideally, decisions regarding which cargo containers to inspect should be made in real time, and the models used should be able to focus efforts when the risk is higher. In this study, we propose a dynamic approach that treats the data as a time series in order to detect periods of high risk. A regulatory organization will respond differently to evidence of systematic problems than evidence of random problems, so testing for serial correlation is of major interest. We compare three models that account for various degrees of serial dependence within the data. First is the independence model where the prediction of the arrival of a risky shipment is made solely on the basis of contextual information. We also consider a Markov chain that allows dependence between successive observations, and a hidden Markov model that allows further dependence on past data. The predictive performance of the models is then evaluated using ROC and leakage curves. We illustrate this methodology on two sets of real inspection data.     

Economic Models for Single Sample Acceptance Sampling Plans,No Inspection,and 100 Percent Inspection

Once a process is stabilized using control charts, it is necessary to determine whether this process is capable of producing die desired quality, as determined by the specifications, without the use of some additional inspection procedure such as 100 percent inspection or acceptance sampling. One common method of making this determination is the use of process capability ratios. However, this approach may lead to erroneous decisions due to the omission of economic information. This paper attempts to remedy this situation by developing economic models to examine the profitability of different inspection policies. These models employ the quadratic loss function to represent the economic cost of quality from external failures, which is commonly omitted or overlooked. Moreover, assuming a normal distribution for the quality characteristic allows the use of simplified formulas that are provided. Thus the calculations can be made using standard normal tables and a calculator. Additionally, these economic models may be used to determine if additional inspection procedures should be reinstated if the quality of the process was to decline, to make capital budgeting decisions involving new equipment that produces parts of a higher quality, and to determine the preferred 100 percent inspection plan or acceptance sampling plan.     

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。     

Optimal Food Safety Sampling Under a Budget Constraint

Much of the literature regarding food safety sampling plans implicitly assumes that all lots entering commerce are tested. In practice, however, only a fraction of lots may be tested due to a budget constraint. In such a case, there is a tradeoff between the number of lots tested and the number of samples per lot. To illustrate this tradeoff, a simple model is presented in which the optimal number of samples per lot depends on the prevalence of sample units that do not conform to microbiological specifications and the relative costs of sampling a lot and of drawing and testing a sample unit from a lot. The assumed objective is to maximize the number of nonconforming lots that are rejected subject to a food safety sampling budget constraint. If the ratio of the cost per lot to the cost per sample unit is substantial, the optimal number of samples per lot increases as prevalence decreases. However, if the ratio of the cost per lot to the cost per sample unit is sufficiently small, the optimal number of samples per lot reduces to one (i.e., simple random sampling), regardless of prevalence. In practice, the cost per sample unit may be large relative to the cost per lot due to the expense of laboratory testing and other factors. Designing effective compliance assurance measures depends on economic, legal, and other factors in addition to microbiology and statistics.     

Predictive Modeling and Categorizing Likelihoods of Quarantine Pest Introduction of Imported Propagative Commodities from Different Countries

The present study investigates U.S. Department of Agriculture inspection records in the Agricultural Quarantine Activity System database to estimate the probability of quarantine pests on propagative plant materials imported from various countries of origin and to develop a methodology ranking the risk of country–commodity combinations based on quarantine pest interceptions. Data collected from October 2014 to January 2016 were used for developing predictive models and validation study. A generalized linear model with Bayesian inference and a generalized linear mixed effects model were used to compare the interception rates of quarantine pests on different country–commodity combinations. Prediction ability of generalized linear mixed effects models was greater than that of generalized linear models. The estimated pest interception probability and confidence interval for each country–commodity combination was categorized into one of four compliance levels: “High,” “Medium,” “Low,” and “Poor/Unacceptable,” Using K‐means clustering analysis. This study presents risk‐based categorization for each country–commodity combination based on the probability of quarantine pest interceptions and the uncertainty in that assessment.     

考虑观察成本的秘书问题仿真实验研究

针对具有观察成本的秘书问题,分析了决策策略和观察成本对决策结果的影响,并在此基础上提出了柔性标杆和可变观察成本;阐述了仿真试验的理论假设和设计,通过仿真试验考察了观察成本与柔性标杆的不同变化对仿真结果的影响;给出了对仿真结果的分析和探讨。仿真结果验证了理论假设的合理性。     

Optimal sampling techniques in off-line quality control

This paper addresses the problem of quality control for manufacturing environments. The quality control station is placed in an off-line position, i.e. external to the item flow. This layout is mandatory when the station is unable (because of costs and times) to inspect the whole set of items produced. The aim of the present study is to describe and evaluate how the limited capacity of the quality control station affects the efficiency of the connected production system and how the service time of the inspection station may be profitably managed as a further variable of the quality inspection process. Optimal policies for both random and deterministic sampling techniques are determined and compared.     

Improving the efficiency of remanufacture through enhanced pre-processing inspection – a comprehensive study of over 2000 engines at Caterpillar remanufacturing,U.K.

Remanufacturing returns used product to an ‘as-new’ condition and is a key strategy in environmentally conscious manufacturing and waste management. However, strategies to improve the efficiency of the process are hampered by a lack of remanufacturing-specific industrial research. This paper presents the results of quantitative research, conducted in an industrial remanufacturing facility, to establish the relationship between pre-processing inspection levels and the subsequent remanufacturing process time for returned used products (known as cores). It concludes that for cores having either complex geometry (such as internal ports), a large number of sub-components or that are constructed from, or comprising of, multiple materials the remanufacturing process is shortened by increased inspection prior to processing. However, these benefits are currently limited by the amount of information that can be gained from the inspection methods used. The authors describes the practical use of these results in both a decision-making methodology for inspection and a cost assessment tool.