Virtual instrumentation: A practical approach to control and supervision process

This work describes a control and supervision application takes into account the virtual instrumentation advantages to control and supervision industrial manufacturing stations belonging to the modular production system MPS® by Festo. These stations integrate sensors, actuators, conveyor belt and other industrial elements. The focus in this approach was to replace the use of programmable logic controllers by a computer equipped with a software application based on Labview and, together, performs the functions of traditional instruments and PLCs. The manufacturing stations had their processes modeled and simulated in Petri nets. After the models were implemented in Labview environment. Tests and previous similar works in MPS® installed in Automation Laboratory, at UNESP Sorocaba campus, showed the materials and methods used in this work allow the successful use of virtual instrumentation. The results indicate the technology as an advantageous approach for the automation of industrial processes, with gains in flexibility and reduction in project cost. © 2011 IEEE.

Joint economic design of X̄ and R control charts for processes subject to two independent assignable causes

A model for the joint economic design of X̄ and R control charts is developed. This model assumes that the process is subject to two assignable causes. One assignable cause shifts the process mean; the other shifts the process variance. The occurrence of the assignable cause of one kind does not block the occurrence of the assignable cause of another kind. Consequently, a second process parameter can go out-of-control after the first process parameter has gone out-of-control. A numerical study of the cost surface to the model considered has revealed that it is convex, at least in the interest region.

Control estadístico de calidad en bibliotecología : Aplicación de gráficos de control en los procesos técnicos

A partir de la aceptación de la biblioteca como parte del ciclo de creación, organización y diseminación del conocimiento cambió el concepto de la misma de una entidad cerrada hacia un sistema dinámico en constante interacción con su entorno. Así se la reconoció como una institución social más que como una colección de documentos. Desde entonces se percibió a la biblioteca como una entidad en la que se podía aplicar los principios de gestión. Desde entonces se utilizaron distintas herramientas de gestión para la toma de decisiones en el ámbito de las bibliotecas. Entre estas herramientas son de gran importancia en el control estadístico de procesos los gráficos de control, utilizados para medir la estabilidad de un proceso a través del tiempo. Han tenido amplia aplicación en el control estadístico de la calidad, comenzando en el ámbito industrial. Hoy su aplicación se ha extendido a una gran variedad de disciplinas incluyen empresas de servicios y unidades administrativas. Aquí se presentan a los gráficos de control como una importante herramienta de gestión aplicada a los procesos técnicos permitiendo su evaluación y el monitoreo de su desempeño a partir de la utilización de indicadores y otros datos de carácter diagnóstico

Control estadístico de calidad en bibliotecología : Aplicación de gráficos de control en los procesos técnicos

A partir de la aceptación de la biblioteca como parte del ciclo de creación, organización y diseminación del conocimiento cambió el concepto de la misma de una entidad cerrada hacia un sistema dinámico en constante interacción con su entorno. Así se la reconoció como una institución social más que como una colección de documentos. Desde entonces se percibió a la biblioteca como una entidad en la que se podía aplicar los principios de gestión. Desde entonces se utilizaron distintas herramientas de gestión para la toma de decisiones en el ámbito de las bibliotecas. Entre estas herramientas son de gran importancia en el control estadístico de procesos los gráficos de control, utilizados para medir la estabilidad de un proceso a través del tiempo. Han tenido amplia aplicación en el control estadístico de la calidad, comenzando en el ámbito industrial. Hoy su aplicación se ha extendido a una gran variedad de disciplinas incluyen empresas de servicios y unidades administrativas. Aquí se presentan a los gráficos de control como una importante herramienta de gestión aplicada a los procesos técnicos permitiendo su evaluación y el monitoreo de su desempeño a partir de la utilización de indicadores y otros datos de carácter diagnóstico

Control estadístico de calidad en bibliotecología : Aplicación de gráficos de control en los procesos técnicos

A partir de la aceptación de la biblioteca como parte del ciclo de creación, organización y diseminación del conocimiento cambió el concepto de la misma de una entidad cerrada hacia un sistema dinámico en constante interacción con su entorno. Así se la reconoció como una institución social más que como una colección de documentos. Desde entonces se percibió a la biblioteca como una entidad en la que se podía aplicar los principios de gestión. Desde entonces se utilizaron distintas herramientas de gestión para la toma de decisiones en el ámbito de las bibliotecas. Entre estas herramientas son de gran importancia en el control estadístico de procesos los gráficos de control, utilizados para medir la estabilidad de un proceso a través del tiempo. Han tenido amplia aplicación en el control estadístico de la calidad, comenzando en el ámbito industrial. Hoy su aplicación se ha extendido a una gran variedad de disciplinas incluyen empresas de servicios y unidades administrativas. Aquí se presentan a los gráficos de control como una importante herramienta de gestión aplicada a los procesos técnicos permitiendo su evaluación y el monitoreo de su desempeño a partir de la utilización de indicadores y otros datos de carácter diagnóstico

High-throughput manufacturing of size-tuned liposomes by a new microfluidics method using enhanced statistical tools for characterization

Microfluidics has recently emerged as a new method of manufacturing liposomes, which allows for reproducible mixing in miliseconds on the nanoliter scale. Here we investigate microfluidics-based manufacturing of liposomes. The aim of these studies was to assess the parameters in a microfluidic process by varying the total flow rate (TFR) and the flow rate ratio (FRR) of the solvent and aqueous phases. Design of experiment and multivariate data analysis were used for increased process understanding and development of predictive and correlative models. High FRR lead to the bottom-up synthesis of liposomes, with a strong correlation with vesicle size, demonstrating the ability to in-process control liposomes size; the resulting liposome size correlated with the FRR in the microfluidics process, with liposomes of 50 nm being reproducibly manufactured. Furthermore, we demonstrate the potential of a high throughput manufacturing of liposomes using microfluidics with a four-fold increase in the volumetric flow rate, maintaining liposome characteristics. The efficacy of these liposomes was demonstrated in transfection studies and was modelled using predictive modeling. Mathematical modelling identified FRR as the key variable in the microfluidic process, with the highest impact on liposome size, polydispersity and transfection efficiency. This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes. Furthermore, the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.

Residence Time Distribution (Rtd) Associated with Statistical Weighted Moments to Fit Mathematical Models Using In Industrial Systems Diagnosis

This work presents a computational, called MOMENTS, code developed to be used in process control to determine a characteristic transfer function to industrial units when radiotracer techniques were been applied to study the unit´s performance. The methodology is based on the measuring the residence time distribution function (RTD) and calculate the first and second temporal moments of the tracer data obtained by two scintillators detectors NaI positioned to register a complete tracer movement inside the unit. Non linear regression technique has been used to fit various mathematical models and a statistical test was used to select the best result to the transfer function. Using the code MOMENTS, twelve different models can be used to fit a curve and calculate technical parameters to the unit.

Object-Oriented Modeling Simulation and Control of Activated Sludge Process

Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.

A stable MPC with zone control

Several MPC applications implement a control strategy in which some of the system outputs are controlled within specified ranges or zones, rather than at fixed set points [J.M. Maciejowski, Predictive Control with Constraints, Prentice Hall, New Jersey, 2002]. This means that these outputs will be treated as controlled variables only when the predicted future values lie outside the boundary of their corresponding zones. The zone control is usually implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When an output prediction is inside its zone, the corresponding weight is zeroed, so that the controller ignores this output. When the output prediction lies outside the zone, the error weight is made equal to a specified value and the distance between the output prediction and the boundary of the zone is minimized. The main problem of this approach, as long as stability of the closed loop is concerned, is that each time an output is switched from the status of non-controlled to the status of controlled, or vice versa, a different linear controller is activated. Thus, throughout the continuous operation of the process, the control system keeps switching from one controller to another. Even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. Here, a stable M PC is developed for the zone control of open-loop stable systems. Focusing on the practical application of the proposed controller, it is assumed that in the control structure of the process system there is an upper optimization layer that defines optimal targets to the system inputs. The performance of the proposed strategy is illustrated by simulation of a subsystem of an industrial FCC system. (C) 2008 Elsevier Ltd. All rights reserved.

Valve friction and nonlinear process model closed-loop identification

Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

Economic design of an X chart for short-run production

The aim of this paper is to present an economical design of an X chart for a short-run production. The process mean starts equal to mu(0) (in-control, State I) and in a random time it shifts to mu(1) > mu(0) (out-of-control, State II). The monitoring procedure consists of inspecting a single item at every m produced ones. If the measurement of the quality characteristic does not meet the control limits, the process is stopped, adjusted, and additional (r - 1) items are inspected retrospectively. The probabilistic model was developed considering only shifts in the process mean. A direct search technique is applied to find the optimum parameters which minimizes the expected cost function. Numerical examples illustrate the proposed procedure. (C) 2009 Elsevier B.V. All rights reserved.