Reduce Inspection Costs Research Articles

An Improved System of Skip-Lot Acceptance Sampling Plans for Highway Construction and Materials

The concept of acceptance sampling plans ensures the quality of products and materials used in highway construction. These acceptance sampling plans require the testing of each and every individual lot of products for the highway construction and materials. This approach of sampling is applicable and appropriate if the supplier or contractor is unreliable. If the contractor is consistent and reliable, then instead of inspecting each and every lot of products, skip-lot sampling system can be utilized where only a fraction of the lots are inspected after assuring the quality and after a certain number of conforming lots is obtained. Skip-lot sampling plan can be used for reducing the amount of inspection on product that has an excellent quality history. Thus, skip-lot sampling plans are designed to reduce inspection costs. Moreover, skip-lot concept is sound and useful and it is economically advantageous in the design of sampling plans. Hence, this paper presents an improved system of skip-lot sampling plans designated as SkSP-V plan for the application of highway construction and materials. Advantages of this plan over the existing skip-lot plan and AASHTO’s lot-by-lot sampling plan are also discussed. The efficiency of this new plan is also investigated.

High Resolution Modeling and Modeling of Connections in Pony-Truss Bridges

Pony-truss bridges are usually modeled using simplifying assumptions, such as pinned connections and analyzing the trusses separately from the rest of the structure. Pony-truss bridges are also generally designated as possessing many Fracture Critical Members (FCM), a characteristic that requires more rigorous inspections. Eliminating or reducing the number of FCM is desirable as it reduces inspection costs. A high-resolution model of a pony-truss bridge was assembled in ABAQUS CAE that explicitly models the behavior of the gusset plates in the connections and the angles in the framed stringer connections. This model indicated alternative load paths that are potential sources of redundancy useful for retrofit or reclassification of bridges with FCM designation. Higher-resolution models of framed stringer connections were also made in ABAQUS CAE using solid elements explicitly modeling the bolted connections. The connections were loaded in tension; what the stringers must hold if they supply an alternative load path for the truss in the event of fracture in the bottom chord. The primary objective of the work described is to provide high-resolution finite element analysis results that can be used to create general behavior for lower-resolution finite element models used in fracture critical analyses to reclassify FCM as non-fracture critical. The results of high-resolution modeling reveal the behavior that is necessary to include in these lower-resolution models, as well as potential alternative load paths. Lower-resolution models are assembled in SAP2000 and matched to the higher-resolution models.

A Fuzzy Logic method: Predicting pipeline external corrosion rate

Oil and gas pipelines are among the largest and most important infrastructures of the modern world. Although rare, pipeline breakdown or leakage exposes public and the environment to safety and health hazards. In this paper, a methodology to predict the external corrosion rate based on the combination of the measurement of six soil parameters and a reduced amount of inspection corrosion rate data is presented. The method provides a relatively user-friendly procedure that can be of use by the industry to focus the efforts towards optimizing the security and the continuity of the service. Furthermore, it reduces inspection costs, as a lesser number of in-situ inspections are required compared to the traditional inspection methods.

Wireless Charging Techniques for UAVs: A Review, Reconceptualization, and Extension

An important application in the growing field of unmanned aerial vehicles (UAVs) is in monitoring and inspection of high voltage power lines and electrical networks. The UAV-based monitoring method will save energy, simplify access to impassable or remote areas, reduce inspection cost, and automate the inspection process. However, the battery capacity of a medium scale drone limits their travel distance and mission duration. It is crucial to improve the energy feeding system of drones and overcome the battery capacity problem to foster the use of drones for routine monitoring operations. In this study, we focus on presenting wireless techniques available for drone mission duration improvement as well as discuss and practically examine the most feasible and reliable technique to charge UAV using power lines.

A Bayesian Virtual Metrology for Quality Inspection of Mobile Repeater Systems

Abstract The technology of wideband code division multiple access (WCDMA) has been applied to band selective interference cancellation system (ICS) repeaters. To inspect the telecommunication quality of the systems, quality engineers must check the shape of the signals at the corresponding frequency band of the repeaters. However, measuring the signal quality is a repetitive manual task which requires much inspection time and high costs. In the case of small-sized samples, such as the example of an ICS repeater system, Bayesian approaches have been employed to improve the estimation accuracy by incorporating prior information on the parameters of the model in consideration. This research proposes a virtual method of quality inspection for products using a correlation structure of measurement data, mainly in a Bayesian regression framework. The Bayesian regression model derives prior information from historical measurement data to predict measurements of other frequency bandwidths by exploiting the correlation structure of each measurement data. Empirical results show the potential for reducing inspection costs and time by predicting the values of adjoining frequency bandwidths through measured data of a frequency bandwidth in the course of quality inspections of ICS repeater systems.

Road Surface Mapping using Kinect Sensor for Road Maintenance

Japan currently faces the problem of deterioration of infrastructure such as roads and buildings that were constructed during a period of rapid growth after World War II. Decrepit infrastructure can lead to accidents and disasters. However, maintenance and repair of such infrastructure is expensive. This makes it important to reduce the cost of these operations. In addition, because of vehicle tra ffi c and changes in the environment temperature, roads expand / shrink and crack, leading to potholes. Without repair, potholes can expand gradually and may lead to accidents. To prevent such accidents, it is necessary that roads are inspected and diagnosed to detect cracks and potholes early and repair them. However, currently, road inspection is primarily a visual inspection method, which is time consuming and expensive to perform. If road inspection can be automated using a ff ordable sensors, time and money can be saved. Moreover, vehicles can be equipped with sensors to collect data of the road status, which can be used to create road surface maps that show the location and size of cracks and potholes. This paper focuses on applying a road inspection method using range image sensors to greatly reduce inspection costs. Specifically, the results of the map of a simulated road with features and the e ff ectiveness of the method are reported.

Improved Bayesian network configurations for random variable identification of concrete chlorination models

Relevant material and environmental parameters are required in modelling chloride ingress into concrete. They could be determined from experimental data (concrete cores taken during inspection) but in practice data availability is limited by time-consuming and expensive tests. Consequently, the main objective of this paper is to develop an approach based on Bayesian networks (BN) to improve the parameter identification when inspection data is limited. We aim at proposing appropriate inspection configurations that reduce inspection costs and identification errors for different exposure conditions and materials. It was found that it is possible to define an optimal number of inspection points in depth for allowed identification errors defined by decision makers. The optimal number of inspection points depends on both exposure and material properties. The random variables identified with the improved BN configurations are used to assess the probability of corrosion initiation. The results indicate that the improved BN configurations are useful to identify model parameters even from scarce inspection data.

Product inspection policy for an imperfect production system with inspection errors and warranty cost

During manufacturing of products, all produced items are considered as perfect in general. This viewpoint of taking all finished products are perfect is not correct always. Defective items may occur during the production process for several reasons. This paper describes a deteriorating production process which randomly shifts to out-of-control state from in-control state. In case of full inspection policy, expected total cost together with inspection cost results higher inventory cost. Therefore, product inspection policy is better to use for reducing inspection costs. During product inspection process, inspectors may choose falsely a defective item as non-defective and vice-versa. Type I and Type II errors are incorporated in this model to make more realistic rather than existing models. This model includes a warranty policy for some fixed time periods. Some numerical examples, sensitivity analysis, and graphical representations are given to illustrate this model.

Fare evasion in proof-of-payment transit systems: Deriving the optimum inspection level

In proof-of-payment systems, fare evasion represents a crucial topic for public transport companies (PTCs) due to lost fare revenues, damaged corporate image, and increased levels of violence on public transport, which might also have negative economic repercussions on PTCs. Therefore, there is a need to establish the level of inspection (i.e. the number of inspectors) to tackle fare dodgers as a possible option. By building on previous models, this paper develops a formal economic framework to derive the optimum inspection level in a long time window, based on system-wide profit maximization when fare evasion exists. The framework takes into account: (i) the refined segmentation of passengers and potential fare evaders, (ii) the variability of perceived inspection level by passengers, and (iii) the fact that an inspector cannot fine every passenger caught evading. Its implementation is illustrated by using three years of real data from an Italian PTC. Based on 27,514 stop-level inspections and 10,586 on-board personal interviews, the results show that the optimum inspection level is 3.8%. Put differently, it is sufficient to check 38 passengers out of every 1000 to maximize profit in the presence of fare evasion. This outcome is very useful, because it improves the one obtained in previous formulations. Indeed, profit maximization is achieved with a lower number of inspectors, thus reducing inspection costs, which are relevant determinants in proficient PTCs. Finally, the framework is flexible and may be applied to public transport modes other than buses as long as proof-of-payment systems are in use.

I-Kaz<sup>TM</sup>-Based Analysis of Cutting Force Signals for Tool Condition Monitoring in Turning Process

Cutting force is an important signal in machining process and has been widely used for tool condition monitoring. Monitoring the condition of the cutting tool in the machining process is very important to maintain the machined surface quality and consequently reduce inspection costs and increase productivity. This paper utilizes I-kaz-based analysis of cutting force signal to monitor the status of tool wear. The cutting force signals are measured by two channels of strain gauge that were mounted on the surface of tool holder. Experiments were carried out by turning hardened carbon steel and cutting force signals were analyzed using I-kazTM technique by integrating two component of signals (I-kaz 2D, Z2), I-kaz of cutting force (Z of Fy), and I-kaz of feed force (Z of Fx). The results show that I-kaz of feed force can be effectively used to monitor tool wear progression during turning operation.

Online tool wear prediction system in the turning process using an adaptive neuro-fuzzy inference system

Tool wear is a detrimental factor that affects the quality and tolerance of machined parts. Having an accurate prediction of tool wear is important for machining industries to maintain the machined surface quality and can consequently reduce inspection costs and increase productivity. Online and real-time tool wear prediction is possible due to developments in sensor technology. Recently, various sensors and methods have been proposed for the development of tool wear monitoring systems. In this study, an online tool wear monitoring system was proposed using a strain gauge-type sensor due to its simplicity and low cost. A model, based on the adaptive network-based fuzzy inference system (ANFIS), and a new statistical signal analysis method, the I-kaz method, were used to predict tool wear during a turning process. In order to develop the ANFIS model, the cutting speed, depth of cut, feed rate and I-kaz coefficient from the signals of each turning process were taken as inputs, and the flank wear value for the cutting edge was an output of the model. It was found that the prediction usually accurate if the correlation of coefficients and the average errors were in the range of 0.989–0.995 and 2.30–5.08% respectively for the developed model. The proposed model is efficient and low-cost which can be used in the machining industry for online prediction of the cutting tool wear progression, but the accuracy of the model depends upon the training and testing data.

Analysis of Quality Crisis and Recovery Model of Regional Brand Market

Because of the different influencing factors, the defective market of regional brand would be contrary to Akerlof adverse selection model, it will still exist. Therefore, this paper establishes the consumer incentive model and local government regulation model. Models shows: Defective market will gradually revert to genuine market by raising prices, improving product information penetration, increasing penalties and reducing inspection costs. Using the adulteration scandal about Wuchang "rice flower" as a case sample enhances the credibility of theoretical research findings.

New technology for inspecting critical in‐plant piping systems

AbstractInspection and fitness‐for‐service (FFS) of critical in‐plant piping systems remains an ongoing concern for the chemical industry. Recent failures in the US indicate that there is a present and severe risk in piping systems. Historically, unpiggable in‐plant piping can now be inspected with advanced smart pigging technology for complete ultrasonic inspection. High‐resolution inspection data is analyzed to identify the locations and degree of corrosion and piping deformations. This article discusses current industry experience with the inspection and assessment of in‐plant piping systems using advanced smart pigging technology.Utilizing more advanced inline inspection and assessment technology helps operators reduce inspection costs associated with difficult‐to‐inspect pipelines and piping systems; reduce maintenance costs by more accurately pinpointing anomalies and assessing FFS conditions; and accurately determine the actual conditions for lines previously deemed unpiggable. © 2011 American Institute of Chemical Engineers Process Saf Prog, 2011

Monitoreo de Salud Estructural

Non-destructive methods for damage detection in civil structures have recently gained the attention of researchers throughout the world due to the advances in instrumentation technology and digital signal processing. Structural Health Monitoring techniques allows the presence, location and magnitude of damage to be detected due to changes in the static and dynamic characteristics of the structure. These techniques can be implemented remotely and in real-time, which can significantly reduce inspection costs and provide an instantaneous alert signal due to damage in the structure. The School of Civil Engineering and Geomatics of the Universidad del Valle has a Structural Health Monitoring research project that includes real-time monitoring of the Hormiguero bridge and an agreement with the Universidad Tecnológica de Pereira for joint monitoring of the Pereira-Dos Quebradas Viaduct.

Phased array ultrasonic inspection of low-pressure steam turbine rotors - curved axial entry fir tree roots

The last stage blades of low-pressure steam turbine rotors are among the most highly-stressed components in modern power generating plants. The ongoing drive for increased efficiency has seen a proliferation in the number of designs incorporating larger last stage blades with curved axial entry fir tree roots (CAEFTR); the curvature of the root attachment allows more flexibility in the aerodynamic design of the aerofoil with improved inter-blade spacing. The tendency of CAEFTRs to suffer failure induced by stress corrosion cracking, high-cycle fatigue cracking or low-cycle high-strain fatigue is well documented and can be shown to be most likely to occur in the first two serrations of the blade root. Finite element analysis and actual failures confirm the regions under highest risk and have driven developments in ultrasonic phased array techniques to achieve detection of defects in these regions whilst in situ, in turn avoiding the huge costs associated in decommissioning and dismantling rotors to perform alternative NDE surface inspections. Due to the complexity of the root geometry, there are many difficulties in applying ultrasonic techniques due to limited scanning surfaces, inter-blade spacing and disorientation of the active ultrasound trajectory and the region under test. In this presentation the author will show that the application of novel phased array techniques and unique inspection design has led to increased sensitivity to smaller defects and comprehensive coverage of CAEFTR rotor designs in situ. It will also be shown how the application of these techniques has negated the need to upgrade both equipment and resources to the use of2D arrays, thereby reducing inspection costs significantly whilst achieving higher repeatability and sensitivity. Novel inspection design has led to the ability to reduce the number of scans required, enabled single scan encoded data recording over the whole blade root, increased sensitivity, improved detectability and increased coverage, whilst reducing inspection costs and time.

Revealing latent quality information hidden within inspection reports of curtailed tests

The desire to accelerate inspection procedures and reduce inspection costs often results in tests being curtailed. Even though every item is meant to undergo a number of independent/dependent tests, once an item, e.g., item #XXX fails to pass a test, further tests/inspections are terminated. Thus, the empirical data existing at the end of the inspection procedure does not contain information about item #XXX’s ability to pass the cancelled tests. Information mining statistical tools can be used to uncover the latent quality information hidden within these data. This paper proposes altering curtailed testing procedures (e.g., changing the order of the tests or detectability levels), in order to estimate the theoretical joint probabilities (latent quality information) concerning an item’s ability to pass a part of, or the entire sequence of tests. The effectiveness of the proposed procedures is then evaluated using simulated data.

A new system of skip-lot sampling plans having a provision for reducing normal inspection

The skip-lot sampling program can be used for reducing the amount of inspection on a product that has excellent quality history. Thus skip-lot sampling plans are designed to reduce inspection costs. Moreover, the skip-lot concept is sound and useful and is economically advantageous to use in the design of sampling plans. Hence, a new system of skip-lot sampling plans designated as the SkSP-V plan is developed in this paper. The proposed plan requires a return to normal inspection whenever a lot is rejected during sampling inspection, but has a provision for a reduced normal inspection upon demonstration of superior product quality. A Markov chain formulation and derivation of performance measures for this new plan are presented. The properties of SkSP-V plan are studied with single sampling plan as the reference plan. Advantages of this new plan are also discussed. Finally, certain cost models are given for the economic design of the SkSP-V plan. Copyright © 2010 John Wiley & Sons, Ltd.

교량점검을 위한 비전 기반의 균열검출 알고리즘 개발

We have developed a vision based crack detection system and algorithm to inspect base side of bridges. After human operator decides from vision images captured if lines on base side are cracks or dirt, our algorithm finds automatically the length, the width and the shape of cracks. The system has been tested with a robot extender on a truck in real environment and has been proved to be very useful to reduce inspection cost as well as the data management.

Minimizing retail shrinkage due to employee theft

PurposeEmployee theft is a major component of retail shrinkage. The purpose of this paper is to analyze the use of two methods, internal control and random inspections of the locations at which employees work, to deter employee theft. An inspection strategy is designed in which retailers try to minimize their costs while trying to prevent employees from stealing.Design/methodology/approachWe employ an analytical approach. The employees are assumed to be strategic, i.e. they respond to the decisions made by the retailer, and likewise the retailer is strategic. Consequently, game theory is used to model their interaction, and to obtain the best decisions for both the retailer and employee after taking into consideration the other's actions.FindingsThe solution of the game depends upon various parameters such as the cost and effectiveness of random inspections and of the internal control system. The paper determines the optimal frequency of inspections, the total budget to be spent on inspections and the total expected retail shrinkage due to employee theft. The paper also shows the extent to which an effective internal control system and the recruitment of honest employees can benefit retail organizations in preventing losses due to employee theft.Practical implicationsThe paper provides normative guidelines for decisions such as the frequency of inspections. Retailers can limit employee theft but eliminating theft altogether turns out to be too expensive if the goal is to minimize organizational losses. The retailer should try to reduce inspection costs and increase their effectiveness. Adding honest employees helps the retailer, but note that adding just a few is not beneficial because organizational losses remain unchanged, but adding a larger number qualitatively affects the equilibrium outcome and lowers organizational losses. The paper describes when investing in better internal control systems is appropriate.Originality/valueThe underlying assumption is of strategic retailers and employees. This gaming analysis brings a new perspective to examining retail crime problems than has been hitherto the case. This work follows in the tradition of the economics of crime literature, which views crime as a rational choice decision made by potential offenders. The study examines employee crime in the context of retail organizations, and provides several new insights. Although the idea of random inspections is not new, features of the retail environment such as internal control system, employee dissatisfaction and the ability to recruit honest employees have no direct parallels in the economics of crime literature, and are being touched upon for the first time.

A design advisor for the optimal inspection of circularity tolerance

In the wake of growing importance for quality and the need to reduce inspection costs simultaneously, the need for a scientific method of selecting an optimum inspection strategy for coordinate measuring machine (CMM) based inspection has become very important. The inspection error resulting from CMM inspection is greatly affected by the profile irregularities and the sampling strategy, which includes sample size, sampling methods, and algorithms used for form evaluation. This paper describes a system that can recommend an optimal inspection plan based on the needs of the user. A design of experiments (DOE) based approach is used to relate the inspection error with sampling strategies. Surface irregularities are included in the form of lobes formed on the profile. A new two-way model is proposed that works in both directions between the sampling strategy and the performance metrics. The results indicate that the number of lobes and the sampling method used have little impact on the inspection error, while the sample size and form evaluation algorithms have a significant influence. An inspection plan advisor is presented, which provides an inspection plan based on the estimated shape and acceptable measurement error.