A new method for continuous quality control of nsm cfrp systems

In the last decade the near-surface mounted (NSM) strengthening technique using carbon fibre reinforced polymers (CFRP) has been increasingly used to improve the load carrying capacity of concrete members. Compared to externally bonded reinforcement (EBR), the NSM system presents considerable advantages. This technique consists in the insertion of carbon fibre reinforced polymer laminate strips into pre-cut slits opened in the concrete cover of the elements to be strengthened. CFRP reinforcement is bonded to concrete with an appropriate groove filler, typically epoxy adhesive or cement grout. Up to now, research efforts have been mainly focused on several structural aspects, such as: bond behaviour, flexural and/or shear strengthening effectiveness, and energy dissipation capacity of beam-column joints. In such research works, as well as in field applications, the most widespread adhesives that are used to bond reinforcements to concrete are epoxy resins. It is largely accepted that the performance of the whole application of NSM systems strongly depends on the mechanical properties of the epoxy resins, for which proper curing conditions must be assured. Therefore, the existence of non-destructive methods that allow monitoring the curing process of epoxy resins in the NSM CFRP system is desirable, in view of obtaining continuous information that can provide indication in regard to the effectiveness of curing and the expectable bond behaviour of CFRP/adhesive/concrete systems. The experimental research was developed at the Laboratory of the Structural Division of the Civil Engineering Department of the University of Minho in Guimar\~aes, Portugal (LEST). The main objective was to develop and propose a new method for continuous quality control of the curing of epoxy resins applied in NSM CFRP strengthening systems. This objective is pursued through the adaptation of an existing technique, termed EMM-ARM (Elasticity Modulus Monitoring through Ambient Response Method) that has been developed for monitoring the early stiffness evolution of cement-based materials. The experimental program was composed of two parts: (i) direct pull-out tests on concrete specimens strengthened with NSM CFRP laminate strips were conducted to assess the evolution of bond behaviour between CFRP and concrete since early ages; and, (ii) EMM-ARM tests were carried out for monitoring the progressive stiffness development of the structural adhesive used in CFRP applications. In order to verify the capability of the proposed method for evaluating the elastic modulus of the epoxy, static E-Modulus was determined through tension tests. The results of the two series of tests were then combined and compared to evaluate the possibility of implementation of a new method for the continuous monitoring and quality control of NSM CFRP applications.

Continuous monitoring of bovine spongiform encephalopathy rapid test performance by weak positive tissue controls and quality control charts

Bovine spongiform encephalopathy (BSE) rapid tests and routine BSE-testing laboratories underlie strict regulations for approval. Due to the lack of BSE-positive control samples, however, full assay validation at the level of individual test runs and continuous monitoring of test performance on-site is difficult. Most rapid tests use synthetic prion protein peptides, but it is not known to which extend they reflect the assay performance on field samples, and whether they are sufficient to indicate on-site assay quality problems. To address this question we compared the test scores of the provided kit peptide controls to those of standardized weak BSE-positive tissue samples in individual test runs as well as continuously over time by quality control charts in two widely used BSE rapid tests. Our results reveal only a weak correlation between the weak positive tissue control and the peptide control scores. We identified kit-lot related shifts in the assay performances that were not reflected by the peptide control scores. Vice versa, not all shifts indicated by the peptide control scores indeed reflected a shift in the assay performance. In conclusion these data highlight that the use of the kit peptide controls for continuous quality control purposes may result in unjustified rejection or acceptance of test runs. However, standardized weak positive tissue controls in combination with Shewhart-CUSUM control charts appear to be reliable in continuously monitoring assay performance on-site to identify undesired deviations.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

Development of a cost-effective and flexible vibration DAQ system for long-term continuous structural health monitoring

In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

Recent applications of Chemical Imaging to pharmaceutical process monitoring and quality control

Chemical Imaging (CI) is an emerging platform technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Vibrational spectroscopic methods, such as Near Infrared (NIR) and Raman spectroscopy, combined with imaging are particularly useful for analysis of biological/pharmaceutical forms. The rapid, non-destructive and non-invasive features of CI mark its potential suitability as a process analytical tool for the pharmaceutical industry, for both process monitoring and quality control in the many stages of drug production. This paper provides an overview of CI principles, instrumentation and analysis. Recent applications of Raman and NIR-CI to pharmaceutical quality and process control are presented; challenges facing Cl implementation and likely future developments in the technology are also discussed. (C) 2007 Elsevier B.V. All rights reserved.

Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

Bond behavior of NSM FRP strips between two adjacent cracks in concrete beams: A numerical study

Strengthening RC structures with near-surface mounted (NSM) fibre reinforced polymer (FRP) composites has a number of advantages compared with that with externally bonded (EB) FRP sheets/plates. As with EB FRP, the performance of the bond between NSM FRP and concrete is one of the key factors affecting the behaviour of the strengthened structure. This paper presents a numerical investigation into the behaviour of NSM FRP loaded at its both ends to simulate the NSM FRP-toconcrete bond between two adjacent cracks in RC members. The main objective of this study is to quantitatively clarify the effect of the bondline damage during slip reversal on the ultimate load (bond strength). The results show that the bondline damage has a significant effect on the load-carrying capacity of the NSM FRP-to-concrete bonded interface and should be considered in FE modeling of the interface.

Classification and fault detection methods for fuel cell monitoring and quality control

In this paper, various types of fault detection methods for fuel cells are compared. For example, those that use a model based approach or a data driven approach or a combination of the two. The potential advantages and drawbacks of each method are discussed and comparisons between methods are made. In particular, classification algorithms are investigated, which separate a data set into classes or clusters based on some prior knowledge or measure of similarity. In particular, the application of classification methods to vectors of reconstructed currents by magnetic tomography or to vectors of magnetic field measurements directly is explored. Bases are simulated using the finite integration technique (FIT) and regularization techniques are employed to overcome ill-posedness. Fisher's linear discriminant is used to illustrate these concepts. Numerical experiments show that the ill-posedness of the magnetic tomography problem is a part of the classification problem on magnetic field measurements as well. This is independent of the particular working mode of the cell but influenced by the type of faulty behavior that is studied. The numerical results demonstrate the ill-posedness by the exponential decay behavior of the singular values for three examples of fault classes.

Modelización tridimensional de ensayos de adherencia tipo viga del refuerzo NSM-FRP en hormigón

El uso de refuerzos NSM‐FRP en estructuras de hormigón armado se ha incrementado considerablemente en los últimos años como método de refuerzo estructural. Los ensayos de arrancamiento en viga de los refuerzos NSM‐FRP permiten el estudio del comportamiento de la unión pegada. El principal objetivo del presente trabajo aborda la simulación numérica de este tipo de ensayos, con el propósito de caracterizar correctamente la adherencia entre las barras de NSM‐FRP y el hormigón. En una fase inicial se simuló un modelo bidimensional para conseguir evaluar y verificar el comportamiento de los elementos cohesivos y ver su comportamiento primero ante diferentes modelos de material y segundo ante un modo mixto de fallo, debido a la aplicación simultanea de carga axial y carga cortante. En una segunda fase se creó un modelo tridimensional para estudiar el arrancamiento de una barra de material compuesto insertada en hormigón, creando un modelo de material de hormigón y viendo el comportamiento cualitativo del sistema ante variaciones en los parámetros de los diferentes materiales. En la tercera fase, la más importante del presente trabajo, se abordó la simulación numérica del ensayo de arrancamiento en viga. Se simularon todos los componentes del ensayo y se evaluaron diferentes alternativas para representar la interfase NSM‐FRP ‐ hormigón, usando elementos cohesivos y diferentes distribuciones de los mismos en la interfase. Para conseguir representar lo más fielmente posible las condiciones del ensayo, se diseñó también un controlador PID que permite realizar las simulaciones numéricas mediante un control en desplazamientos, lo cual permite capturar más correctamente el comportamiento de reblandecimiento de la unión pegada. El controlador PID aplica técnicas de ingeniería de control para conseguir calcular a priori la amplitud necesaria del desplazamiento impuesto que provoque una evolución establecida en una variable interna del sistema. La variable usada para correlacionar los ensayos es la diferencia en desplazamientos entre dos puntos y se escoge una evolución lineal de la misma, pero en la tesis también se exponen los resultados de escoger otras posibles variables internas con diferentes evoluciones. Se compararon las simulaciones numéricas con resultados de mediciones experimentales previamente publicadas. Los resultados carga‐deslizamiento obtenidos encajan bien con los datos experimentales. El modelo propuesto es también capaz de predecir el modo de fallo en la interfase NSM‐FRP ‐ hormigón. Finalmente, también se han llevado a cabo estudios paramétricos, para evaluar la influencia de cada parámetro en los resultados. También se realizó un estudio cualitativo de cómo se comporta la unión pegada en cada momento de la simulación, mediante el uso macros y gráficas tridimensionales, para conseguir una mejor visualización y facilitar el análisis de los resultados. ABSTRACT The use of near‐surface mounted FRP reinforcement in reinforced concrete structures has seen a considerable increase in recent years as a strengthening method. Beam pull‐out tests for near‐surface reinforcement allow obtaining the local bond‐slip behavior of a bonded joint. The main objective of the current work deals with the three‐dimensional modeling of this kind of test with the purpose of characterizing suitably the mechanics of bond between FRP rods and concrete. In an initial stage, a two bidimensional in order to evaluate and to verify the behavior of the cohesive elements. Its behavior was evaluated first testing different material models and second testing the behavior when mixed mode failure appears, due to simultaneous axial and shear load. In a second stage a tridimensional model was created in order to study the pull‐out of an inserted beam of composite material in concrete. A concrete material model was created and the influence of each material parameter was studied qualitatively. The third part, the most relevant of the present work, the numerical simulation of the Beam Pull‐Out test was faced. All the parts of the Beam Pull‐Out test were included inthe simulation and different alternatives to represent the FRP bar – concrete interface have been evaluated, using cohesive elements and different distributions of them. In order to reproduce the test conditions more reliably, a PID controller has also been designed to conduct suitably the numerical tests in order to properly capture the softening branch of the load‐slip behaviour. The PID controller applies control techniques to calculate a priori the necessary amplitude of the load in order to achieve a given evolution through the simulation of an internal variable previously chosen. The variable used in order to correlate the simulation with the test results is the difference in displacements between two points and a linear evolution was chosen, but in the thesis the results of choosing other possible internal variables with different evolutions are also shown. The numerical FE simulations were compared with experimental measurements previously published. Load‐slip predictions compare well with the corresponding experimental data. The proposed model is also able to predict the failure mode at the FRP‐concrete interface. Some parametric studies have also been carried out, in order to evaluate the influence of each material parameter in the results. A qualitative study of the behaviour of the joint was also performed, using the results of the numeric simulations and through the use of macros and 3D graphs, the tensional state of each point of the joint can be visualized in each moment of the simulation.

Novel manually made NSM FRP (MMFRP) bars for shear strengthening of RC beams

This paper presents an experimental study evaluating the effectiveness of the Near Surface Mounted (NSM) technique with innovative manually made FRP bars (MMFRP) for shear strengthening of RC beams. RC beams designed to fail in shear were tested in three-point bending. To delay the onset of MMFRP bar debonding, a new anchorage is also developed and tested. This paper reports the results of a series of tests on simply supported rectangular RC beams, strengthened in shear with MMFRP bar either with or without the proposed anchorage. The load-deflection responses of all test beams are plotted, in addition to selected strain results. Performance and the failure modes of the test beams are presented and discussed in this paper. The proposed MMFRP bars and end anchorage enhanced the shear capacity between 25 to 48% over the control specimen. Furthermore, the adoption of the proposed end anchorage of MMFRP bars significantly enhanced the ductility of the test specimens.

Analytical Methods Employed at Quality Control of Fuel Ethanol

The existence of organic and inorganic contaminants present in both fossil and biomass fuels and the fact that they can provide undesirable effects (environmental problems, corrosion processes, lead to storage instability, and others) implies a rigorous quality control of these fuels, although these contaminants make up a small part of the final fuel composition. Considering the rising importance of fuel ethanol in the worldwide panorama, this review aims at reporting the use of successful alternative analytical methods in the monitoring of organic and inorganic contaminants at trace levels, used to determine and to quantify these substances in fuel ethanol and also presenting all official norms for quality control of fuel ethanol employed by ABNT (Brazilian Association of Technical Norms), ASTM (American Society for Testing and Materials), and ECS (European Committee for Standardization).

Quality Control in the Healthcare Industry: An Analysis of Surgery Turnover Times

For virtually all hospitals, utilization rates are a critical managerial indicator of efficiency and are determined in part by turnover time. Turnover time is defined as the time elapsed between surgeries, during which the operating room is cleaned and preparedfor the next surgery. Lengthier turnover times result in lower utilization rates, thereby hindering hospitals’ ability to maximize the numbers of patients that can be attended to. In this thesis, we analyze operating room data from a two year period provided byEvangelical Community Hospital in Lewisburg, Pennsylvania, to understand the variability of the turnover process. From the recorded data provided, we derive our best estimation of turnover time. Recognizing the importance of being able to properly modelturnover times in order to improve the accuracy of scheduling, we seek to fit distributions to the set of turnover times. We find that log-normal and log-logistic distributions are well-suited to turnover times, although further research must validate this finding. Wepropose that the choice of distribution depends on the hospital and, as a result, a hospital must choose whether to use the log-normal or the log-logistic distribution. Next, we use statistical tests to identify variables that may potentially influence turnover time. We find that there does not appear to be a correlation between surgerytime and turnover time across doctors. However, there are statistically significant differences between the mean turnover times across doctors. The final component of our research entails analyzing and explaining the benefits of introducing control charts as a quality control mechanism for monitoring turnover times in hospitals. Although widely instituted in other industries, control charts are notwidely adopted in healthcare environments, despite their potential benefits. A major component of our work is the development of control charts to monitor the stability of turnover times. These charts can be easily instituted in hospitals to reduce the variabilityof turnover times. Overall, our analysis uses operations research techniques to analyze turnover times and identify manners for improvement in lowering the mean turnover time and thevariability in turnover times. We provide valuable insight into a component of the surgery process that has received little attention, but can significantly affect utilization rates in hospitals. Most critically, an ability to more accurately predict turnover timesand a better understanding of the sources of variability can result in improved scheduling and heightened hospital staff and patient satisfaction. We hope that our findings can apply to many other hospital settings.