908 resultados para Process Control


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Porous poly(L-lactic acid) (PLA) scaffolds of 85 per cent and 90 per cent porosity are prepared using polymer sintering and porogen leaching method. Different weight fractions of 10 per cent, 30 per cent, and 50 per cent of hydroxyapatite (HA) are added to the PLA to control the acidity and degradation rate. The three-dimensional (3D) morphology and surface porosity are tested using micro-computer tomography (micro-CT), optical microscopy, and scanning electron microscopy (SEM). Results indicate that the surface porosity does not change on the addition of HA. The micro-CT examinations show a slight decrease in the pore size and increase in the wall thickness accompanied by reduced anisotropy for the scaffolds containing HA. Scanning electron micrographs show detectable interconnected pores for the scaffold with pure PLA. Addition of the HA results in agglomeration of the HA particles and reduced leaching of the porogen. Compression tests of the scaffold identify three stages in the stress-strain curve. The addition of HA results in a reduction in the modulus of the scaffold at the first stage of elastic bending of the wall, but this is reversed for the second and third stages of collapse of the wall and densification in the compression tests. In the scaffolds with 85 per cent porosity, the addition of a high percentage of HA could result in 70 per cent decrease in stiffness in the first stage, 200 per cent increase in stiffness in the second stage, and 20 per cent increase in stiffness in the third stage. The results of these tests are compared with the Gibson cellular material model that is proposed for prediction of the behaviour of cellular material under compression. The pH and molecular weight changes are tracked for the scaffolds within a period of 35 days. The addition of HA keeps the pH in the alkaline region, which results in higher rate of degradation at an early period of observation, followed by a reduced rate of degradation later in the process. The final molecular weight is higher for the scaffolds with HA than for scaffolds of pure PLA. The manufactured scaffolds offer acceptable properties in terms of the pore size range and interconnectivity of the pores and porosity for non-load-bearing bone graft substitute; however, improvement to the mixing of the phases of PLA and HA is required to achieve better integrity of the composite scaffolds. © 2008 IMechE.

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A low cost supercritical CO foaming rig with a novel design has been used to prepare fully interconnected and highly porous biodegradable scaffolds with controllable pore size and structure that can promote cancellous bone regeneration. Porous polymer scaffolds have been produced by plasticising the polymer with high pressure CO and by the formation of a porous structure following the escape of CO from the polymer. Although, control over pore size and structure has been previously reported as difficult with this process, the current study shows that control is possible. The effects of processing parameters such as CO saturation pressure, time and temperature and depressurisation rate on the morphological properties, namely porosity, pore interconnectivity, pore size and wall thickness- of the scaffolds have been investigated. Poly(d,l)lactic acid was used as the biodegradable polymer. The surfaces and internal morphologies of the poly(d,l)lactic acid scaffolds were examined using optical microscope and micro computed tomography. Preosteoblast human bone cells were seeded on the porous scaffolds in vitro to assess cell attachment and viability. The scaffolds showed a good support for cell attachment, and maintained cell viability throughout 7 days in culture. This study demonstrated that the morphology of the porous structure can be controlled by varying the foaming conditions, allowing the porous scaffolds to be used in various tissue engineering applications.

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Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

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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.

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Melt viscosity is one of the main factors affecting product quality in extrusion processes particularly with regard to recycled polymers. However, due to wide variability in the physical properties of recycled feedstock, it is difficult to maintain the melt viscosity during extrusion of polymer blends and obtain good quality product without generating scrap. This research investigates the application of ultrasound and temperature control in an automatic extruder controller, which has ability to maintain constant melt viscosity from variable recycled polymer feedstock during extrusion processing. An ultrasonic modulation system has been developed and fitted to the extruder prior to the die to convey ultrasonic energy from a high power ultrasonic generator to the polymer melt. Two separate control loops have been developed to run simultaneously in one controller: the first loop controls the ultrasonic energy or temperature to maintain constant die pressure, the second loop is used to control extruder screw speed to maintain constant throughput at the extruder die. Time response and energy consumption of the control methods in real-time experiments are also investigated and reported this paper.

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Semiconductor fabrication involves several sequential processing steps with the result that critical production variables are often affected by a superposition of affects over multiple steps. In this paper a Virtual Metrology (VM) system for early stage measurement of such variables is presented; the VM system seeks to express the contribution to the output variability that is due to a defined observable part of the production line. The outputs of the processed system may be used for process monitoring and control purposes. A second contribution of this work is the introduction of Elastic Nets, a regularization and variable selection technique for the modelling of highly-correlated datasets, as a technique for the development of VM models. Elastic Nets and the proposed VM system are illustrated using real data from a multi-stage etch process used in the fabrication of disk drive read/write heads. © 2013 IEEE.

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Plasma etch is a key process in modern semiconductor manufacturing facilities as it offers process simplification and yet greater dimensional tolerances compared to wet chemical etch technology. The main challenge of operating plasma etchers is to maintain a consistent etch rate spatially and temporally for a given wafer and for successive wafers processed in the same etch tool. Etch rate measurements require expensive metrology steps and therefore in general only limited sampling is performed. Furthermore, the results of measurements are not accessible in real-time, limiting the options for run-to-run control. This paper investigates a Virtual Metrology (VM) enabled Dynamic Sampling (DS) methodology as an alternative paradigm for balancing the need to reduce costly metrology with the need to measure more frequently and in a timely fashion to enable wafer-to-wafer control. Using a Gaussian Process Regression (GPR) VM model for etch rate estimation of a plasma etch process, the proposed dynamic sampling methodology is demonstrated and evaluated for a number of different predictive dynamic sampling rules. © 2013 IEEE.

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The vulnerability of coastal areas to associated hazards is increasing due to population growth, development pressure and climate change. It is incumbent on coastal governance regimes to address the vulnerability of coastal inhabitants to these hazards. This is especially so at the local level where development planning and control has a direct impact on the vulnerability of coastal communities. To reduce the vulnerability of coastal populations, risk mitigation and adaptation strategies need to be built into local spatial planning processes. Local government, however, operates within a complex hierarchal governance framework which may promote or limit particular actions. It is important, therefore, to understand how local coastal planning practices are shaped by national and supranational entities. Local governments also have to respond to the demands of local populations. Consequently, it is important to understand local populations’ perceptions of coastal risk and its management. Adopting an in-depth study of coastal planning in County Mayo, Ireland, this paper evaluates: (a) how European and national policies and legislation shape coastal risk management at local level; (b) the incorporation of risk management strategies into local plans; and (c) local perception of coastal risks and risk management. Despite a strong steer from supranational and national legislation and policy, statutory local plans are found to be lacking in appropriate risk mitigation or adaptation strategies. Local residents appear to be lulled into a sense of complacency towards these risks because of the low level of attention afforded to them by the local planning authorities. To avoid potentially disastrous consequences for local residents and businesses, it is imperative that this situation is redressed urgently. Based on our analysis, we recommend: the development and implementation of a national ICZM strategy, supported by detailed local ICZM plans; and obliging local government to address known risks in their plans rather than defer them to project level decision making.

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Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

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Due to the variability of wind power, it is imperative to accurately and timely forecast the wind generation to enhance the flexibility and reliability of the operation and control of real-time power. Special events such as ramps, spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Gaussian Process model with hybrid training data taken from both the local time and historic dataset is proposed and applied to make short-term predictions from 10 minutes to one hour ahead. A key idea is that the similar pattern data in history are properly selected and embedded in Gaussian Process model to make predictions. The results of the proposed algorithms are compared to those of standard Gaussian Process model and the persistence model. It is shown that the proposed method not only reduces magnitude error but also phase error.

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Background: Nursing homes for older people provide an environment likely to promote the acquisition and spread of meticillin-resistant Staphylococcus aureus (MRSA), putting residents at increased risk of colonisation and infection. It is recognised that infection prevention and control strategies are important in preventing and controlling MRSA transmission.

Objectives: To determine the effects of infection prevention and control strategies for preventing the transmission of MRSA in nursing homes for older people.

Search methods: In August 2013, for this third update, we searched the Cochrane Wounds Group Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library), Database of Abstracts of Reviews of Effects (DARE, The Cochrane Library), Ovid MEDLINE, OVID MEDLINE (In-process and Other Non-Indexed Citations), Ovid EMBASE, EBSCO CINAHL, Web of Science and the Health Technology Assessment (HTA) website. Research in progress was sought through Current Clinical Trials, Gateway to Reseach, and HSRProj (Health Services Research Projects in Progress).

Selection criteria: All randomised and controlled clinical trials, controlled before and after studies and interrupted time series studies of infection prevention and control interventions in nursing homes for older people were eligible for inclusion.

Data collection and analysis: Two review authors independently reviewed the results of the searches. Another review author appraised identified papers and undertook data extraction which was checked by a second review author.

Main results: For this third update only one study was identified, therefore it was not possible to undertake a meta-analysis. A cluster randomised controlled trial in 32 nursing homes evaluated the effect of an infection control education and training programme on MRSA prevalence. The primary outcome was MRSA prevalence in residents and staff, and a change in infection control audit scores which measured adherence to infection control standards. At the end of the 12 month study, there was no change in MRSA prevalence between intervention and control sites, while mean infection control audit scores were significantly higher in the intervention homes compared with control homes.

Authors' conclusions: There is a lack of research evaluating the effects on MRSA transmission of infection prevention and control strategies in nursing homes. Rigorous studies should be conducted in nursing homes, involving residents and staff to test interventions that have been specifically designed for this unique environment.

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In this paper, a multiloop robust control strategy is proposed based on H∞ control and a partial least squares (PLS) model (H∞_PLS) for multivariable chemical processes. It is developed especially for multivariable systems in ill-conditioned plants and non-square systems. The advantage of PLS is to extract the strongest relationship between the input and the output variables in the reduced space of the latent variable model rather than in the original space of the highly dimensional variables. Without conventional decouplers, the dynamic PLS framework automatically decomposes the MIMO process into multiple single-loop systems in the PLS subspace so that the controller design can be simplified. Since plant/model mismatch is almost inevitable in practical applications, to enhance the robustness of this control system, the controllers based on the H∞ mixed sensitivity problem are designed in the PLS latent subspace. The feasibility and the effectiveness of the proposed approach are illustrated by the simulation results of a distillation column and a mixing tank process. Comparisons between H∞_PLS control and conventional individual control (either H∞ control or PLS control only) are also made

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Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.

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There is an increasing interest in the biomedical field to create implantable medical devices to provide a temporary mechanical function for use inside the human body. In many of these applications bioresorbable polymer composites using PLLA with β-TCP , are increasingly being used due to their biocompatability, biodegradability and mechanical strength.1,3 These medical devices can be manufactured using conventional plastics processing methods such as injection moulding and extrusion, however there is great need to understand and control the process due to a lack of knowledge on the influence of processing on material properties. With the addition of biocompatible additives there is also a requirement to be able to predict the quality and level of dispersion within the polymer matrix. On-line UV-Vis spectroscopy has been shown to monitor the quality of fillers in polymers. This can eliminate time consuming and costly post-process evaluation of additive dispersion. The aim of this work was to identify process and performance relationships of PLLA/β-TCP composites with respect to melt-extrusion conditions. This is part of a wider study into on-line process monitoring of bioresorbable polymers as used in the medical industry.
These results show that final properties of the PLLA/ β-TCP composite are highly influenced by the particle size and loading. UV-Vis spectroscopy can be used on-line to monitor the final product and this can be utilised as a valuable tool for quality control in an application where consistent performance is of paramount importance.