901 resultados para on-line condition monitoring


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Developments in evaporator cleaning have accelerated in the past 10 years as a result of an extended period of research into scale formation and scale composition. Chemical cleaning still provides the most cost effective method of cleaning the evaporators. The paper describes a system that was designed to obtain on-line samples of evaporator scale negating the need to open up hot evaporator vessels for scale collection. This system was successfully implemented in a number of evaporators at a sugar mill. This paper also describes a recent experience in a sugar factory in which the cleaning procedure was slightly modified, resulting in effective removal of intractable scale.

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Developments in evaporator cleaning have accelerated in the past 10 years as a result of an extended period of research into scale formation and scale composition. Chemical cleaning still provides the most cost effective method of cleaning the evaporators. The paper describes a system that was designed to obtain on-line samples of evaporator scale negating the need to open up hot evaporator vessels for scale collection. This system was successfully implemented in a number of evaporators at a sugar mill. This paper also describes a recent experience in a sugar factory in which the cleaning procedure was slightly modified resulting in effective removal of intractable scale.

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The measurement of high speed laser beam parameters during processing is a topic that has seen growing attention over the last few years as quality assurance places greater demand on the monitoring of the manufacturing process. The targets for any monitoring system is to be non-intrusive, low cost, simple to operate, high speed and capable of operation in process. A new ISO compliant system is presented based on the integration of an imaging plate and camera located behind a proprietary mirror sampling device. The general layout of the device is presented along with the thermal and optical performance of the sampling optic. Diagnostic performance of the system is compared with industry standard devices, demonstrating the high quality high speed data which has been generated using this system.

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Geochemical processes in estuarine and coastal waters often occur on temporally and spatially small scales, resulting in variability of metal speciation and dissolved concentrations. Thus, surveys, which are aimed to improve our understanding of metal behaviour in such systems, benefit from high-resolution, interactive sampling campaigns. The present paper discusses a high-resolution approach to coastal monitoring, with the application of an automated voltammetric metal analyser for on-line measurements of dissolved trace metals in the Gulf of Cadiz, south-west Spain. This coastal sea receives metal-rich inputs from a metalliferous mining area, mainly via the Huelva estuary. On-line measurements of dissolved Cu, Zn, Ni and Co were carried out on-board ship during an eight-day sampling campaign in the study area in June 1997. A pumping system operated continuously underway and provided sampled water from a depth of ca. 4 m. Total dissolved metal concentrations measured on-line in the Gulf of Cadiz ranged between <5 nM Cu (<3 nM Ni) ca. 50 km off-shore and 60–90 nM Cu (5–13 nM Ni) in the vicinity of the Huelva estuary. The survey revealed steep gradients and strong tidal variability in the dissolved metal plume extending from the Huelva estuary into the Gulf of Cadiz. Further on-line measurements were carried out with the automatic metal monitor from the bank of the Odiel estuary over a full tidal cycle, at dissolved metal concentrations in the μM range. The application confirmed the suitability of the automated metal monitor for coastal sampling, and demonstrated its adaptability to a wide range of environmental conditions in the dynamic waters of estuaries and coastal seas. The near-real time acquisition of dissolved metal concentrations at high resolution enabled an interactive sampling campaign and therefore the close investigation of tidal variability in the development of the Huelva estuary metal plume.

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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.

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One of the most important objectives of cold metal forming research is to develop techniques that enable better manufacturing efficiencies. Within this monitoring of tooling condition is vital to providing high quality manufacturing. The objective of this research is to determine the signature derived from Acoustic Emission (AE) sensors, in order to establish the current condition of a machine tool, as applied to bolt-making. From here we aim to develop and implement an on-line condition monitoring tool for the cold forming process. A review of the literature has shown that much research into AE has been successfully applied in metal cutting operations; such as milling, drilling and turning, but little research has been done related to metal forming. This appears to be due to the complexity of obtaining consistent signals using Acoustic Emission systems, because the presence of noise in many forms. This paper will detail many of the AE signals acquired and analysed through our research. The extensive results indicate this form of condition monitoring is not suitable for metal forming in its current configuration. Further tests are proposed to enable such research to move forward, so a condition monitoring system can be established.

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A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. © 2012 Elsevier B.V.

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A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. (C) 2012 Elsevier B.V. All rights reserved.

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In this paper, a procedure for the on-line process control of variables is proposed. This procedure consists of inspecting the m-th item from every m produced items and deciding, at each inspection, whether the process is out-of-control. Two sets of limits, warning (µ0 ± W) and control (µ0 ± C), are used. If the value of the monitored statistic falls beyond the control limits or if a sequence of h observations falls between the warning limits and the control limits, the production is stopped for adjustment; otherwise, production goes on. The properties of an ergodic Markov chain are used to obtain an expression for the average cost per item. The parameters (the sampling interval m, the widths of the warning, the control limits W and C(W < C), and the sequence length (h) are optimized by minimizing the cost function. A numerical example illustrates the proposed procedure.