Computer control of chemical process plants with special reference to distillation

A sieve plate distillation column has been constructed and interfaced to a minicomputer with the necessary instrumentation for dynamic, estimation and control studies with special bearing on low-cost and noise-free instrumentation. A dynamic simulation of the column with a binary liquid system has been compiled using deterministic models that include fluid dynamics via Brambilla's equation for tray liquid holdup calculations. The simulation predictions have been tested experimentally under steady-state and transient conditions. The simulator's predictions of the tray temperatures have shown reasonably close agreement with the measured values under steady-state conditions and in the face of a step change in the feed rate. A method of extending linear filtering theory to highly nonlinear systems with very nonlinear measurement functional relationships has been proposed and tested by simulation on binary distillation. The simulation results have proved that the proposed methodology can overcome the typical instability problems associated with the Kalman filters. Three extended Kalman filters have been formulated and tested by simulation. The filters have been used to refine a much simplified model sequentially and to estimate parameters such as the unmeasured feed composition using information from the column simulation. It is first assumed that corrupted tray composition measurements are made available to the filter and then corrupted tray temperature measurements are accessed instead. The simulation results have demonstrated the powerful capability of the Kalman filters to overcome the typical hardware problems associated with the operation of on-line analyzers in relation to distillation dynamics and control by, in effect, replacirig them. A method of implementing estimator-aided feedforward (EAFF) control schemes has been proposed and tested by simulation on binary distillation. The results have shown that the EAFF scheme provides much better control and energy conservation than the conventional feedback temperature control in the face of a sustained step change in the feed rate or multiple changes in the feed rate, composition and temperature. Further extensions of this work are recommended as regards simulation, estimation and EAFF control.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Growth and Characterization of III-V Semiconductor Materials for MOCVD Reactor Qualification and Process Control

Metalorganic chemical vapor deposition is examined as a technique for growing compound semiconductor structures. Material analysis techniques for characterizing the quality and properties of compound semiconductor material are explained and data from recent commissioning work on a newly installed reactor at the University of Illinois is presented.

Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi`s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is nonconforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure. (C) 2009 Elsevier B. V. All rights reserved.

Effects of the preventive and corrective adjustments in economical designs for online process control for attributes with misclassification errors

The procedure for online process control by attributes consists of inspecting a single item at every m produced items. It is decided on the basis of the inspection result whether the process is in-control (the conforming fraction is stable) or out-of-control (the conforming fraction is decreased, for example). Most articles about online process control have cited the stoppage of the production process for an adjustment when the inspected item is non-conforming (then the production is restarted in-control, here denominated as corrective adjustment). Moreover, the articles related to this subject do not present semi-economical designs (which may yield high quantities of non-conforming items), as they do not include a policy of preventive adjustments (in such case no item is inspected), which can be more economical, mainly if the inspected item can be misclassified. In this article, the possibility of preventive or corrective adjustments in the process is decided at every m produced item. If a preventive adjustment is decided upon, then no item is inspected. On the contrary, the m-th item is inspected; if it conforms, the production goes on, otherwise, an adjustment takes place and the process restarts in-control. This approach is economically feasible for some practical situations and the parameters of the proposed procedure are determined minimizing an average cost function subject to some statistical restrictions (for example, to assure a minimal levelfixed in advanceof conforming items in the production process). Numerical examples illustrate the proposal.

Sterilization of Medical Devices by Ethylene Oxide, Determination of the Dissipation of Residues, and Use of Green Fluorescent Protein as an Indicator of Process Control

Ethylene oxide (EO) is used to sterilize Oxygenator and Tubing applied to heart surgery. Residual levels of EO and its derivatives, ethylene chlorohydrin (ECH) and ethylene glycol (EG), may be hazardous to the patients. Therefore, it must be removed by the aeration process. This study aimed to estimate the minimum aeration time for these devices to attain safe limits for use (avoiding excessive aeration time) and to evaluate the Green Fluorescent Protein (GFP) as a biosensor capable of best indicating the distribution and penetration of EO gas throughout the sterilization chamber. Sterilization cycles of 2, 4, and 8 h were monitored by Bacillus atrophaeus ATCC 9372 as a biological indicator (131) and by the GFP. Residual levels of EO, ECH, and EG were determined by gas chromatography (GC), and the residual dissipation was studied. Safe limits were reached right after the sterilization process for Oxygenator and after 204 h of aeration for Tubing. In the 2 h cycle, the GFP concentration decreased from 4.8 (+/- 3.2)% to 7.5 (+/- 2.5)%. For the 4 h cycle, the GFP concentration decreased from 17.4 (+/- 3.0)% to 21.5 (+/- 6.8)%, and in the 8 h cycle, it decreased from 22.5 (+/- 3.2)% to 23.9 (+/- 3.9)%. This finding showed the potentiality for GFP applications as an EO biosensor. (C) 2009 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 9113: 626-630, 2009

The application of statistical process control charts to the detection and monitoring of hospital-acquired infections

The monitoring of infection control indicators including hospital-acquired infections is an established part of quality maintenance programmes in many health-care facilities. However, surveillance data use can be frustrated by the infrequent nature of many infections. Traditional methods of analysis often provide delayed identification of increasing infection occurrence, placing patients at preventable risk. The application of Shewhart, Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) statistical process control charts to the monitoring of indicator infections allows continuous real-time assessment. The Shewhart chart will detect large changes, while CUSUM and EWMA methods are more suited to recognition of small to moderate sustained change. When used together, Shewhart and EWMA methods are ideal for monitoring bacteraemia and multiresistant organism rates. Shewhart and CUSUM charts are suitable for surgical infection surveillance.

Development of process control strategies exploiting knowledge from systems biology: application to MDCK suspension cells

Madine Darby Canine Kidney (MDCK) cell lines have been extensively evaluated for their potential as host cells for influenza vaccine production. Recent studies allowed the cultivation of these cells in a fully defined medium and in suspension. However, reaching high cell densities in animal cell cultures still remains a challenge. To address this shortcoming, a combined methodology allied with knowledge from systems biology was reported to study the impact of the cell environment on the flux distribution. An optimization of the medium composition was proposed for both a batch and a continuous system in order to reach higher cell densities. To obtain insight into the metabolic activity of these cells, a detailed metabolic model previously developed by Wahl A. et. al was used. The experimental data of four cultivations of MDCK suspension cells, grown under different conditions and used in this work came from the Max Planck Institute, Magdeburg, Germany. Classical metabolic flux analysis (MFA) was used to estimate the intracellular flux distribution of each cultivation and then combined with partial least squares (PLS) method to establish a link between the estimated metabolic state and the cell environment. The validation of the MFA model was made and its consistency checked. The resulted PLS model explained almost 70% of the variance present in the flux distribution. The medium optimization for the continuous system and for the batch system resulted in higher biomass growth rates than the ones obtained experimentally, 0.034 h-1 and 0.030 h-1, respectively, thus reducing in almost 10 hours the duplication time. Additionally, the optimal medium obtained for the continuous system almost did not consider pyruvate. Overall the proposed methodology seems to be effective and both proposed medium optimizations seem to be promising to reach high cell densities.

Application of multivariate statistical process control to fuel cell manufacturing

Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.

Electron Beam Welding In-Process Control and Monitoring

This work presents the results of an investigation of processes in the melting zone during Electron Beam Welding(EBW) through analysis of the secondary current in the plasma.The studies show that the spectrum of the secondary emission signal during steel welding has a pronounced periodic component at a frequency of around 15–25 kHz. The signal contains quasi-periodic sharp peaks (impulses). These impulses have stochastically varying amplitude and follow each other inseries, at random intervals between series. The impulses have a considerable current (up to 0.5 A). It was established that during electron-beam welding with the focal spot scanning these impulses follow each other almost periodically. It was shown that the probability of occurrence of these high-frequency perturbation increases with the concentration of energy in the interaction zone. The paper also presents hypotheses for the mechanism of the formation of the high-frequency oscillations in the secondary current signal in the plasma.

Selectivity of chemical weed control systems in conventional cotton

Cotton is highly susceptible to the interference imposed by weed community, being therefore essential to adopt control measures ensuring the crop yield. Herbicides are the primary method of weed control in large-scale areas of production, and usually more than one herbicide application is necessary due to the extensive crop cycle. This study aimed to evaluate the selectivity of different chemical weed control systems for conventional cotton. The experiment took place in the field in a randomized block design, with twenty nine treatments and four replications in a split plot layout (adjacent double check). Results showed that triple mixtures in pre-emergence increased the chance of observing reductions in the cotton yield. To avoid reductions in crop yield, users should proceed to a maximum mixture of two herbicides in pre-emergence, followed by S-metolachlor over the top, followed by one post-emergence mixture application of pyrithiobac-sodium + trifloxysulfuron-sodium.

Press forming of paperboard – advancement of converting tools and process control

Press forming is nowadays one of the most common industrial methods in use for producing deeper trays from paperboard. Demands for material properties like recyclability and sustainability have increased also in the packaging industry, but there are still limitations related to the formability of paperboard. A majority of recent studies have focused on material development, but the potential of the package manufacturing process can also be improved by the development of tooling and process control. In this study, advanced converting tools (die cutting tools and the press forming mould) are created for production scale paperboard tray manufacturing. Also monitoring methods that enable the production of paperboard trays with enhanced quality, and can be utilized in process control are developed. The principles for tray blank preparation, including creasing pattern and die cutting tool design are introduced. The mould heating arrangement and determination of mould clearance are investigated to improve the quality of the press formed trays. The effect of the spring back of the tray walls on the tray dimensions can be managed by adjusting the heat-related process parameters and estimating it at the mould design stage. This enables production speed optimization as the process parameters can be adjusted more freely. Real-time monitoring of pressing force by using multiple force sensors embedded in the mould structure can be utilized in the evaluation of material characteristics on a modified production machinery. Comprehensive process control can be achieved with a combination of measurement of the outer dimensions of the trays and pressing force monitoring. The control method enables detection of defects and tracking changes in the material properties. The optimized converting tools provide a basis for effective operation of the control system.

STUDIES ON THE QUALITY AND PROCESS CONTROL FACTORS DURING THE PRODUCTION AND STORAGE OF SALTED DRIED FISH PRODUCTS

In this study the quality and process control factors during the production and storage of salted dried fish products. The study reveals that quantity of dry fish production in the state is decreasing and dry fish processing industry should be encouraged by central and state governments. The dry and wet salting may be carried out to a period of 4 to 8 hours respectively and time may depend on temperature, size, and concentration of medium. Demand is an unavoidable factor for sale of fish. The packed dry salted lots kept at room temperature are useful only for 20 days. The refrigerator- stored lots had more storage life and nutritional content are good up to 3 months. The cold storage stored dry salted lot had more storage life than the wet salted lot. The use of preservatives in salting is encouraged to reduce pH. The low temperature preservation maintains the nutritional value and quality for long period. It further encourages the labeling of nutritional value of dry fish as in tinned products.