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The purpose of this paper is to model a block-based inspection policy for a multi-component system with stochastic dependence. Some components may develop a hidden failure, an occurrence of which neither stops the system nor accelerates the other components’ deterioration. On the other hand, other components may experience three states: healthy, defective and revealed failures. Any revealed failure of each component not only stops the system but also generates a shock to all the other ones, which increases their occurrence rate of hidden, defect and revealed failures.

A block-based inspection policy is considered to take advantage of economic dependence as follows. In addition to the periodic inspections, the system is also inspected at revealed failures’ moments of each component to detect and fix both defects and hidden failures on all the other components. To calculate the expected total cost, the recursive equations for the required expected values is first mathematically derived. Then, due to computational complexity, an efficient Monte Carlo simulation algorithm is designed to calculate the expected values.

The proposed approach is illustrated through a numerical example, and the optimal periodic inspection interval over a finite time horizon is obtained via minimization of the expected total cost. Finally, the correctness of the results is validated by conducting sensitivity analysis.

Planning an appropriate inspection policy over a finite time horizon becomes more complicated when considering a multi-component system because different units may experience different failure modes with stochastic dependence.

The four sections to this article have distinct but inter‐related objectives. Part I introduces the concepts, problems and tensions central to an understanding of the product liability debate. These issues recur throughout the article. Part II outlines the development of product liability law in Europe and assesses the impact of the European Directive on Product Liability. The “product liability crisis” in the United States is discussed in Part III, which looks at the law's development and proposals for reform. In Part IV the United States and European positions are compared and the case is made out for a global uniform product liability law which recognises the social responsibility of the producer towards those injured by his products.

A building deteriorates over time due to aging, wear and tear, and inadequate maintenance. Building diagnosis requires a sound knowledge of engineering, building defects, and detection tools to assess the condition of a building. The physical deterioration of a building reduces its ability to perform its intended function, while environmental deterioration influences the comfort and health of building occupants. This study presents a multi-tiered framework for the inspection of building elements and the environmental conditions of a building.

A three-tiered building inspection framework is proposed in this study, which consists of the following: Tier-I—a preliminary inspection, Tier-II—a detailed inspection, and Tier-III—an expert investigation. Each tier of inspection assesses the severity of building defects using different technologies for different levels of inspection.

Proposed multi-tier inspection framework is tested and implemented on a case study. Results were promising, with organized data management on a common platform for both physical and environmental condition inspection having the potential to save time.

The application program developed for the implementation of structured multi-tiered building inspection provides better documentation and data management for building inspection data that can save time involved in manual data operations in traditional paper-based processes.

This study aims to design and validate a theoretical model for capacitive imaging (CI) sensors that incorporates the interelectrode shielding and surrounding shielding electrodes. Through experimental verification, the effectiveness of the theoretical model in evaluating CI sensors equipped with shielding electrodes has been demonstrated.

The study begins by incorporating the interelectrode shielding and surrounding shielding electrodes of CI sensors into the theoretical model. A method for deriving the semianalytical model is proposed, using the renormalization group method and physical model. Based on random geometric parameters of CI sensors, capacitance values are calculated using both simulation models and theoretical models. Three different types of CI sensors with varying geometric parameters are designed and manufactured for experimental testing.

The study’s results indicate that the errors of the semianalytical model for the CI sensor are predominantly below 5%, with all errors falling below 10%. This suggests that the semianalytical model, derived using the renormalization group method, effectively evaluates CI sensors equipped with shielding electrodes. The experimental results demonstrate the efficacy of the theoretical model in accurately predicting the capacitance values of the CI sensors.

The theoretical model of CI sensors is described by incorporating the interelectrode shielding and surrounding shielding electrodes into the model. This comprehensive approach allows for a more accurate evaluation of the detecting capability of CI sensors, as well as optimization of their performance.

Detection of hidden defects of aluminum alloy plate with damping coating is a challenging problem. At present, only a few non-destructive testing methods exist to address this engineering problem. Without the restriction of skin effect, remote field eddy current (RFEC) overcomes the interference caused by the damping coating. The RFEC, which has potential advantages for detecting the hidden defects of aluminum plate with damping coating, can penetrate the metal plate to detect buried depth defects. This study aims to test how thick the RFEC sensor can penetrate the metal plate to detect the buried defects.

The magnetic field distribution characteristics are analyzed, the magnetic field intensity distribution is calculated, and the structure and parameters of the coil, magnetic circuit and shielding damping are determined through the two- and three-dimensional finite element simulation methods. Optimal excitation frequency is obtained, and the distance between the excitation coil and detection coil is determined by analyzing the relationship between excitation frequency and remote field points.

Simulation and experimental results verify the feasibility of applying the RFEC detection technology in detecting the hidden defects of aluminum alloy plate with damping coating.

In this paper, the RFEC testing model of hidden defects in aluminum plate sample with damping coating is established by using the finite element method.

In eddy current nondestructive testing, a probe with a ferrite core such as an E-core coil is usually used to detect and locate defects such as cracks and corrosion in conductive material. However, the E-core coil has some disadvantages, such as large volume and difficulty in the process of winding the coils. This paper aims to present a novel T-core probe and its analytical model used for evaluating hidden holes in a multi- layer conductor.

By using a cylindrical coordinate system, the solution domain is truncated in the radial direction. The magnetic vector potential of each region excited by a filamentary coil is derived, and the expansion coefficients of the solutions are obtained by matching the boundary and interface conditions between the regions. By using the truncated region eigenfunction expansion method, the final expression in closed form for the impedance of the multi-turn coil is worked out, and the impedance calculation is performed in Mathematica. For frequencies ranging from 100 Hz to 100 kHz, both the impedance changes of the T-core coil above the multi-layer conductor without a hidden hole and in the absence of the layered conductor were calculated, and the influence of a hidden hole in the multi-layer conducting structure on the impedance change was investigated.

The correctness of the analytical model of the T-core coil was verified by the finite element method and experiments. The proposed T-core coil has higher sensitivity than an air-core coil, and similar sensitivity and smaller size than an E-core coil.

A new T-core coil probe and its accurate theoretical model for defect evaluation of conductor were presented; probe and analytical model can be used in probe design, detection process simulation or can be directly used in defect evaluation of multi-layer conductor.

Active infrared (IR) thermography, because of its high productivity and illustrativeness, is a promising technique in nondestructive testing (NDT). The purpose of this paper is to discuss a concept and practical implementation of a portable experimental unit intended for IR thermographic NDT of corrosion in metallic shells.

The basic theory relates to the analysis of heat conduction in a plate with rear-surface material loss subjected to pulse, thermal wave or arbitrary heating.

The amplitude of temperature anomalies over defects and their characteristic observation times depend on material loss, size and shape of corrosion defects. A flexible architecture of the inspection unit is proposed to include flash tubes, halogen lamps and laser-emitting diode (LED) panels as sources of stimulating thermal radiation. In particular, LED heaters might be perspective due to their narrow spectral band, which is beyond a spectral sensitivity of modern IR imagers. It has been found that the IR thermographic technique is convenient for detecting material loss of up to 15–20 per cent in uniformly painted steel shells with thickness up to 8 mm. The concept of signal-to-noise ratio has been applied to evaluate efficiency of data processing techniques, such as Fourier transform and principal component analysis.

The developed equipment and inspection guidelines can be used for detecting hidden corrosion in metallic objects, such as above-ground tanks, pipes, containers, etc.

Despite the number of quality management procedures being currently applied, construction defects in the domestic sector are acknowledged to contribute to the energy performance gap of buildings. This paper investigates the limitations and challenges to the implementation of project quality plans (PQPs) and their impact on the achievement of expected thermal performance in the UK social housing projects.

A qualitative approach, guided by grounded theory, was used in this research. This methodology provided the structure for systematic data analysis iterations, enabling cross-case analysis. An analytic induction process was designed to seek the explanation of the targeted phenomenon and required data collection until no new ideas and concepts emerged from the research iterations. This study collected data from five social housing projects through interviews, site observations and project documentation.

Multiple limitations and challenges were identified in the implementation of PQP to deliver thermal efficient social housing. Generally, there is the need for more objective quality compliance procedures based on required evidence. When investigating the root of the challenges, it was concluded that the adoption of statutory approval as the main quality compliance procedure led to the dilution of the responsibility for prevention and appraisal of defects that compromised the effectiveness of PQP devised by housing associations (HA) and contractors.

This study identifies the shortcomings of PQP in addressing quality issues with potential to undermine the thermal performance of social housing projects. The findings could be used by HA, contractors and policymakers as steppingstones to improve the energy efficiency in the domestic sector.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

The goal of this work is to clarify seven useful DMAIC Analyze phase options for developing process improvement opportunities required for successful projects.

Using a scientific method problem solving structure, IO possibilities are shown to be predicted by rejecting a conceptual testable hypothesis.

Seven analysis paths are identified that enable learners to develop multiple IO discovery strategies and to narrow tool selection options. Four benefit areas for identifying analysis paths are given: improved training, continuous improvement foundation, leadership support and framework clarification.

Any starting list of analysis paths for developing IOs would be incomplete. The diversity of application experiences and tools will add to the current list.

Learners participating in LSS activities are aware of management's expectation that they will develop IOs to justify the LSS investment. Tool-focused training may leave some learners unclear about the multiple possible sources for IOs. Identifying useful analysis paths with associated tools for IO discovery will address any learner's Analyze phase uncertainty and facilitate expanded opportunities.

Any successful LSS project must discover IOs to develop improvement actions. Clarifying IO discovery alternatives will encourage team brainstorming on Analyze phase investigative options. This framework identifying LSS improvement paths will assist practitioners in training and communicating with leadership and learners the range of approaches for developing improvement actions.