Multiple Inspection Research Articles

Sensitivity of probability-of-failure estimates with respect to probability of detection curve parameters

A methodology has been developed and demonstrated that can be used to compute the sensitivity of the probability-of-failure (POF) with respect to the parameters of inspection processes that are simulated using probability of detection (POD) curves. The formulation is such that the probabilistic sensitivities can be obtained at negligible cost using sampling methods by reusing the samples used to compute the POF. As a result, the methodology can be implemented for negligible cost in a post-processing non-intrusive manner thereby facilitating implementation with existing or commercial codes. The formulation is generic and not limited to any specific random variables, fracture mechanics formulation, or any specific POD curve as long as the POD is modeled parametrically. Sensitivity estimates for the cases of different POD curves at multiple inspections, and the same POD curves at multiple inspections have been derived. Several numerical examples are presented and show excellent agreement with finite difference estimates with significant computational savings.

A common cycle approach for solving the economic lot and inspection scheduling problem

In this study, we consider an imperfect production system in which the manager not only faces the Economic Lot Scheduling Problem, but also needs to conduct multiple inspections during a production lot of any product. Inspection plays an important role in an imperfect production system since it saves the cost from producing and restoring defective items though it also incurs extra inspection cost at the same time. In this study, we employ the common cycle approach in which all the products share the same replenishment cycle, and adopt a consensus inspection policy. The focus of this study is to determine the optimal cycle time and an optimal production and inspection schedule that minimize the total cost per unit time. We formulate a mathematical model in which we take into accounts both the production capacity and inspection capacity constraints. Also, we conduct full theoretical analysis and propose an effective search algorithm for solving an optimal solution. Our numerical experiments demonstrate the effectiveness of the proposed search algorithm.

A Truncated Logistic Regression Model in Probability of Detection Evaluation

ABSTRACT In nondestructive evaluation (NDE) studies, the probability of detection curve (POD) is an important performance metric. The traditional POD estimation is to conduct NDE inspections for artificially fabricated specimens with known flaws. This approach is often challenges because not only do fabricated flaws not adequately represent the flaws found in the field, but the cost and time of fabricating artificial specimens can also be very high. In practice, field samples and components in service with naturally occurring defects are readily available and much less expensive to test. However, the disadvantage of this field approach is that the exact number and sizes of the flaws in a sample (especially for flaws with small sizes) are unknown. As a result, serious bias in estimating the POD can occur. In this article, a truncated logistic regression method is developed that can estimate POD accurately and consistently with field samples based on multiple inspections. A case study illustrates the successful application of the proposed approach in a leading manufacturing company. The simulation studies also show that the proposed methods estimate the POD on field samples with quality comparable to that of the traditional approach on artificial specimens.

New image sensor offers multiple inspections and Ethernet interface

New image sensor offers multiple inspections and Ethernet interface

Comprehensive Evaluation of Virginia Department of Transportation’s Experience with its First Performance-Based Road-Maintenance Contract

The Virginia Department of Transportation’s (VDOT) first performance-based road-maintenance contract was concluded in July 2007. This contract required the contractor to maintain all assets and carry out incident management and snow and ice removal services on a total of 250 mi (402 km) of a number of Virginia’s interstate highways. This contract acted as a pilot project for VDOT and other states departments of transportation (DOT). Since performance-based road-maintenance contracting is rather new and yet to be utilized by many state DOTs, there is an emerging need to (1) assess whether its use is viable, and (2) inform the state DOTs of the key issues to consider when using performance-based road-maintenance contracting. The purpose of this paper is to address this need by providing a comprehensive evaluation of VDOT’s overall experience with its pilot performance-based road-maintenance contract. The findings from the analyses over a period of 6 years indicate that while meeting or coming very close to the performance targets most of the time, there have been years in which the contractor was not able to meet performance targets in fence-to-fence asset groups and bridges. As far as the comparison of the level-of-service effectiveness performance of the contractor with that of VDOT utilizing traditional maintenance approaches is concerned, the findings show that the contractor outperformed VDOT in fence-to-fence asset groups. The key issues that a state DOT should consider when using performance-based road-maintenance contracting, as learned from VDOT’s pilot project experience, can be summarized as (1) tying payments to be made to the contractor to actual performance, (2) generating a detailed baseline condition information, (3) using performance targets that increase (as opposed to being constant) over the contract period, (4) establishing a performance target for every single item required to be maintained, (5) having multiple inspections per year, (6) developing a standard rating procedure for all elements, and (7) developing objective, quantifiable, and easily measurable performance criteria.

Camtek receives a $3 million order for multiple wafer inspection systems

Camtek receives a $3 million order for multiple wafer inspection systems

Camtek receives order for multiple wafer inspection systems

Camtek receives order for multiple wafer inspection systems

Visual inspection of glass bottlenecks by multiple-view analysis

The narrow structure of bottlenecks poses a very challenging problem for automated visual inspection systems and surprisingly, this issue has received little attention in literature. Bottleneck inspection is highly relevant to the fabrication of glass bottles, e.g., for the wine and beer industry. Defects in glass bottles can arise in various situations such as an incomplete reaction in a batch, batch contaminants and interactions of the melted material among others. This paper presents an inspection approach that utilises geometry of multiple views along with a rich set of feature descriptors to discriminate real flaws from false alarms in uncalibrated images of glass bottlenecks. The proposed method is based on an automatic multiple view inspection (AMVI) technique for the automatic detection of flaws. This technique involves an initial step that extracts numerous segmented regions from a set of views of the object under inspection. These regions are subsequently classified either as real flaws or as false alarms. The classification process considers that image noise and false alarms occur as random events in different views while real flaws induce geometric and featural relations in the views where they appear. Therefore, by analysing such relations it is possible to successfully localise real flaws and to discard a large number of false alarms. An important characteristic of the proposed methodology is the complete lack of camera calibration which makes our method very suitable for applications where camera calibration is difficult or expensive to carry out. Our inspection system achieves a true positive rate of 99.1% and a false positive rate of 0.9%.

Fully employing software inspections data

Software inspections provide a proven approach to quality assurance for software products of all kinds, including requirements, design, code, test plans, among others. Common to all inspections is the aim of finding and fixing defects as early as possible, and thereby providing cost savings by minimizing the amount of rework necessary later in the life cycle. Measurement data, such as the number and type of found defects and the effort spent by the inspection team, provide not only direct feedback about the software product to the project team, but are also valuable for process improvement activities. In this paper, we discuss NASA’s use of software inspections and the rich set of data that has resulted. In particular, we present results from analysis of inspection data that illustrate the benefits of fully utilizing that data for process improvement at several levels. Examining such data across multiple inspections or projects allows team members to monitor and trigger cross project improvements. Such improvements may focus on the software development processes of the whole organization as well as improvements to the applied inspection process itself.

Integrated Conveyance Condition Assessment Techniques Support Asset Management and Capacity Driven Projects

Traditional asset internal condition assessment inspection techniques gather data that improve the understanding of an asset’s condition and capacity performance. Inspection data are difficult to compile because of the differing ways the inspection data are collected and documented. This drove the need for a modified data collection and analysis process. An integrated asset scoring and multiple inspection scoring process was developed after reviewing and assessing the availability of existing industry approaches. A unique method of applying a common scoring scale of 1–100 to each inspection technique was developed using a combination of advanced root-square-mean mathematical principles. The benefits of the integrated inspection process are that large amounts of field inspection data can be screened, analyzed, and consistently prioritized using automated processes saving considerable labor resources and expediting corrective action solutions. These features will aide utility owner efforts to efficiently and effectively address both asset management and capacity driven projects.

Miniature Mobile Sensor Platforms for Condition Monitoring of Structures

In this paper, a wireless, multisensor inspection system for nondestructive evaluation (NDE) of materials is described. The sensor configuration enables two inspection modes-magnetic (flux leakage and eddy current) and noncontact ultrasound. Each is designed to function in a complementary manner, maximizing the potential for detection of both surface and internal defects. Particular emphasis is placed on the generic architecture of a novel, intelligent sensor platform, and its positioning on the structure under test. The sensor units are capable of wireless communication with a remote host computer, which controls manipulation and data interpretation. Results are presented in the form of automatic scans with different NDE sensors in a series of experiments on thin plate structures. To highlight the advantage of utilizing multiple inspection modalities, data fusion approaches are employed to combine data collected by complementary sensor systems. Fusion of data is shown to demonstrate the potential for improved inspection reliability.

Improving product quality by multiple inspections: Prior and posterior planning of serial inspection procedures

In many practical situations, a complex product is inspected more than once in a sequential manner to further improve its quality. In this paper, the problem of designing the multiple inspection plan via a Bayesian method is considered. As a prior distribution in the Bayesian model, a negative binomial distribution that has many desirable properties is used. Two types of design problem are considered. In prior planning of a serial inspection procedure, the number of inspections necessary to achieve a desired level of quality must be determined prior to starting the inspection process. In posterior planning, the inspection process can be terminated if the product meets a given level of quality. In both cases, the improved level of quality is measured in this paper either by the expected number of undetected errors still remaining in the product or by the probability of no undetected errors in the product.

Improvement of SNM Detection Performance by Fusion of Data From Multiple Inspection Systems

Data fusion has the potential to improve the performance of multiple systems over algorithms involving only Boolean combinations of decisions from the separate systems. To achieve this improvement, it is essential to utilize the complementary aspects of the systems involved. In this paper, we demonstrate that data fusion of x-ray radiography and neutron capture gamma ray spectroscopy provide complementary data to differential die away analysis, and thereby a substantial improvement in both detection performance and throughput.

Automated planning support for on-site construction inspection

Construction inspectors need inspection planning assistance to specify goals for inspection and to develop and search among feasible inspection plans that inspectors can implement to address these inspection goals on construction sites. This paper presents the details of an automated planning approach to support on-site construction inspections and thereby permit inspectors to both generate complete, detailed inspection plans and to consider numerous possible alternatives in detail. The approach consists of representations and reasoning mechanisms to develop inspection goals and plans, and to support consideration of multiple possible inspection plans. In particular, the approach consists of a series of matching processes, facilitated by faceted classification reasoning, and a generative method-based approach to inspection planning that features a measurement distribution concept to permit various approaches for distributing measurements throughout components. The authors present an object-oriented prototype to illustrate and demonstrate this approach, together with detailed validation discussions that utilize inspection scenarios documented in construction inspection literature to demonstrate the generality and applicability of the developed approach.

Bayesian Analysis of the Sequential Inspection Plan via the Gibbs Sampler

A complex product, such as a software system, is often inspected more than once in a sequential manner to further improve its quality and reliability. In such a case, a particularly important task is to accurately estimate the number of errors still remaining in the product after a series of multiple inspections. In the paper, we first develop a maximum likelihood method of estimating both the number of undiscovered errors in the product and the detection probability. We then compare its performance with that of an existing estimation method that has several limitations. We also propose a Bayesian method with noninformative priors, which performs very well in a Monte Carlo simulation study. As the prior knowledge is elicited and incorporated in the analysis, the prediction accuracy of the Bayesian method improves even further. Thus, it would be worthwhile to use various estimation methods and compare their estimates in a specific inspection environment.

Portable Weld Inspection Management System

Manual visual inspection is by far the most widely used weld inspection method. A given weld may be visually examined multiple times as parts are joined and made into assemblies. Because visual inspection is somewhat subjective, and prone to error (a typical inspector only identifies about 85% of the visible defects); welds that pass one inspection may fail subsequent inspections, resulting in multiple inspection and repair cycles. This paper discusses a project that tested the benefits and limitations of a semiautomated weld inspection system. The goal of this semiautomated inspection approach is to provide quantitative, nonsubjective quality measurements of welded structures in order to: eliminate redundant inspections, reduce unnecessary multiple repair cycles, avoid repair of welds that meet minimum size requirements, and enable recording of weld size so that overwelding can be identified and reduced. The technology would also allow tracking of weld quality and statistical analysis of welding process capability to support lean/six-sigma continuous improvement initiatives. A prototype system was assembled and field tested by inspecting actual ship structures. The equipment evaluated has potential, but needs both hardware and software modifications before it can be used as a tool on a regular basis in a shipbuilding environment. As is, it will be useful as an audit tool to gauge the health of the visual inspection process and to further document the inherent variability of the visual inspection process. Recommendations were made for improvements to refine the prototype tool prior to broader deployment.

Applying the law of iterated logarithm to control type I error in cumulative meta-analysis of binary outcomes

Cumulative meta-analysis typically involves performing an updated meta-analysis every time when new trials are added to a series of similar trials, which by definition involves multiple inspections. Neither the commonly used random effects model nor the conventional group sequential method can control the type I error for many practical situations. In our previous research, Lan et al. (Lan KKG, Hu M-X, Cappelleri JC. Applying the law of iterated logarithm to cumulative meta-analysis of a continuous endpoint. Statistica Sinica 2003; 13: 1135-45) proposed an approach based on the law of iterated logarithm (LIL) to this problem for the continuous case. The study is an extension and generalization of our previous research to binary outcomes. Although it is based on the same LIL principle, we found the discrete case much more complex and the results from the continuous case do not apply to the binary case. The simulation study presented here is also more extensive. The LIL based method ;penalizes' the Z-value of the test statistic to account for multiple tests and for the estimation of heterogeneity in treatment effects across studies. It involves an adjustment factor, which is directly related to the control of type I error and determined through extensive simulations under various conditions. With an adjustment factor of 2, the LIL-based test statistics controls the overall type I error when odds ratio or relative risk is the parameter of interest. For risk difference, the adjustment factor can be reduced to 1.5. More inspections may require a larger adjustment factor, but the required adjustment factor stabilizes after 25 inspections. It will be ideal if the adjustment factor can be obtained theoretically through a statistical model. Unfortunately, real life data are too complex and we have to solve the problem through simulation. However, for large number of inspections, the adjustment factor will have a limited effect and the type I error is controlled mainly by the LIL. The LIL method controls the overall type I error for a very broad range of practical situations with a binary outcome, and the LIL works properly in controlling the type I error rates as the number of inspections becomes large.

Optimization of inspection schedule for a surface-breaking crack subject to fatigue loading

Inspections play an essential role in the damage tolerance approach to control fatigue damage. In this paper a method is presented to optimize the cost-effectiveness of inspection scheduling for single and multiple inspections during the expected lifetime. Detailed results are given for a surface-breaking crack of depth a in a cyclic tension field. The original crack depth is treated as a random variable with a known probability density function. The crack growth is governed by the Paris law, and the inspection technique has a known probability of detection. The component fails when the crack depth reaches a critical value a cr . As a part of the damage-tolerant approach, the component is replaced only when the depth of the detected crack is larger than a pre-defined value a r . For a pre-determined number of cycles that defines the expected lifetime the optimal number of cycles for the inspection scheduling has been obtained by minimizing a total cost function. The total cost function is the sum of the cost functions for failure, component replacement and inspection. These functions have been expressed is terms of the relevant probabilities. Analytical and numerical results are given for one, two and multiple inspections. These results show the effects of the magnitude of a r , and the probability of detection (POD) of the inspection technique on the optimum schedule of inspections.

A risk approach to the management of boiler tube thinning

A large set of industrial thickness inspection data covering four boiler units of a power station over a period of five years was made available to the authors. The measurements were made in regions of the boiler where corrosion/erosion was the major cause of failure of the boiler tubes. There were over 40,000 separately measured data points in the data and all were collected with some care and expense. In the development of maintenance strategies for equipment, this type of data is typical of the data that must be collected and assessed. This data thus represents an opportunity to evaluate the ability to generate a useful risk approach to the management of the tubing. An important example of a risk-based approach is the American Petroleum Institute (API) Risk Based Inspection (“RBI”), API 581. A variety of problems were encountered applying this to boiler tubes. The problems include irrelevant API 581 corrosion rate tables, lack of information on how to analyse inspection data, difficulty of dealing with multiple inspection categories and lack of suitable direction for programming inspection intervals.

Evaluation of Human Performanace in a Supervisory Inspection Task Monitoring Multiple Hybrid Inspection Systems

The demand for consistent quality has led to 100% inspection using automated systems rather than the traditional sampling with human inspectors. However, these automated systems cannot adapt to novel situations to meet the required performance without human intervention. The need for costeffective and superior inspection performance has resulted in hybrid systems in which the functions are allocated depending on the capabilities of humans and machines. With the increasing availability of computer technology due to decreased costs and size, the role of humans in inspection systems is changing from that of a continuous “online” inspector to that of a supervisor of multiple tasks. This study uses a computer-based visual inspection simulator to investigate the role of the human as a supervisor in inspection systems, with the main focus on the effect of performance of one hybrid inspection system on human decision to intervene in another system to optimize the inspection performance.