Advanced Process Control Applications Research Articles

Image restoration and analysis with application to quality variable prediction in flotation process

Flotation process is commonly used to separate valuable minerals from undesirable ones. Measurement of flotation froth concentration is essential for control applications. The concentration of froth is often evaluated visually by operators and through the laboratory analysis of collected samples over a long period of time. However, the latter suffers from significant time delays and the former is not very reliable. Computer vision is widely used in industry to analyze the froth concentration based on various froth image features. In this study, we propose a computer vision model to estimate the froth concentration. Important practical challenges including contaminated images with bright lighting spots, camera noise and outliers are addressed. First, the contaminated images are restored using a modified Kalman filter. The color, texture, and deep features of froth images are then extracted using gray-level co-occurrence matrix (GLCM) and a transfer learning-based convolutional neural network (CNN), respectively. Afterward, a regression model is built to estimate the froth concentration based on the integrated visual features. An expectation–maximization (EM) algorithm is then applied to determine the unknown parameters of the model, which is also robust against outliers by using a t-distribution to model the noise. Experiments conducted on a batch flotation column for tailings bitumen extraction show that the proposed algorithm is able to estimate the bitumen concentration with reasonable accuracy. The proposed algorithm is a time-saving alternative to time-consuming and costly laboratory analysis and is essential for advanced process control applications.

A systematical framework for process operational safety index design and synthesis

With the demand for improving production efficiency and the application of advanced process control, modern chemical production has increasingly attached importance to process operational safety. A systematical framework for process operational safety index (POSI) design and synthesis is proposed in this work. The notion of general operational safety is defined firstly, and safety critical variables are introduced for quantification. With the consideration of dynamics and robustness, the relationships between safety critical variables and POSI are discussed sufficiently. Based on these relationships and the frameworks of reachable set, flexibility index and control barrier function, the formula forms of POSI are further determined and summarized. Finally, the feed-forward neuron network is utilized as an approximator and classier to improve the continuity and usability of POSI.

A hybrid model for multipoint real time potency observation in continuous direct compression manufacturing operations

The ongoing transition from batch to continuous manufacturing offers both challenges and opportunities in the field of oral solid dosage form production. In turn, Process Analytical Technology (PAT) offers a path towards the successful deployment of continuous tablet manufacturing in rotary tablet presses. One promising PAT tool for this endeavour is the NIR-derived potency measurement. However, the high degree of noise in the data may hamper the extraction of useful information. For this reason, this work focused on the implementation of an adaptive Kalman filter algorithm that incorporates and reconciles the potency prediction given by one or more NIR probes with those of a semi-mechanistic compartmental model developed for the application at hand. This approach allowed for more robust concentration estimations. Furthermore, it was observed that potency levels in multiple locations in the studied tablet press (including those in the finished tablets) could be appropriately inferred using a single in-line measurement data stream. This methodology thus opens the door to advanced process control applications.

Temperature control of low density polyethylene (LDPE) tubular reactor using Model Predictive Control (MPC)

Application of advanced process control has become demanding in order to save energy and reduce operating cost, while attaining excellent controllability of the process. This situation can be achieved via better controller action performance compared to conventional control scheme such as PID controller. Model Predictive Control (MPC) has a wide application in the industry due to its ability to handle multivariable control and optimized process performance. In this study, a linear based MPC was implemented to control Low Density Polyethylene (LDPE) tubular reactor temperature. The control of LDPE tubular reactor is challenging due to the complexity of the polymerization process and the nature of the reactor itself. The steady state polymerization reactor model was simulated using Aspen Plus software. The validated steady state reactor model was then exported to Aspen Dynamic software for dynamic simulation. In order to implement online control of the process, the dynamic model was linked with Matlab Simulink environment. The linear model of the process was estimated using State-space model identification technique. Sequential Quadratic programming (SQP) method was adopted by the MPC to calculate the controller action. The performance of MPC was compared to a PID controller. Based on the results, MPC had overcome PID performance in set point tracking and disturbance rejection test despite its low accuracy process model. The linear model low accuracy drawback was compensated by proper tuning of the MPC. In overall, MPC had demonstrated its capability to control the process with optimized control action, which can lead to production cost saving in the long run.

Use of Advanced Process Control for Automating Conventional Oilfield Operations

Summary With the growth of Internet of Things technology and the industrial revolution 4.0 (IR4.0), digital information is becoming more integrated into our daily operations. Such a modality of operation allows all disciplines in an organization to collaboratively manage and operate their assets to achieve the maximum value of those assets. In this paper, we describe one of the initiatives under the company's digital transformation strategy. It is a simple yet innovative application of advanced process control (APC) that facilitates continuous optimization of the performance of electrical submersible pumps (ESPs), not only to comply with the assigned production targets but also to automatically meet the operational constraints. The successful implementation of this technology on multiple oil wells in an onshore oil field has demonstrated significant power savings of 10 to 20%, and is expected to minimize premature failures and extend pump life.

Advanced Process Control of an Ethylene Cracking Furnace

The ethylene production plant is one of the most important units in petrochemical industry, and the ethylene cracking furnace is the heart of the plant. The ethylene cracking furnace is a multivariable, strong coupling, and nonlinear process, and therefore, it is difficult to be manipulated by traditional proportional–integral–derivative controls. This paper reports a real application of advanced process control in five 470-kton/year SC-I tubular reactors. The advanced process control deployed includes cracking outlet temperature control and feed volume control. This control system has been operating since 2012. The variation of cracking outlet temperature has been reduced from ±5 to ±1 °C with a setting time less than a few minutes even under a large-scale disturbance. The variation of feed volume has been controlled within ±1%. As a result, the advanced process control system has achieved a total production increase by 0.3%.

English

English

Программно-алгоритмический комплекс прогностического управления «Матрица»

The article is devoted to APC (Advanced Process Control) applications in processes automated control. Developed program complex “Matrix” is offered to elaborate forecasting models and, in turn, to optimize multiple process control according to the chosen criterion of efficiency and available restrictions.

Why Some APC Applications Lose Performance Over Time And How You Can Avoid It

For a long time, companies in the Chemical Process Industry have turned to Advanced Process Control (APC) as a means to increase profitability and production capacity. Among the most widely used APC techniques is Model Predictive Control (MPC). Many service and software vendors have become knowledgeable in executing projects and delivering MPC applications throughout a diverse range of processes. The focus of this work is on what happens after project conclusion, when the project team is dismissed and the application is handed over to the customer operations.It has been observed in practice that without proper maintenance, APC applications will tend to progressively lose their ability to capture benefits. This work will present how we developed a program aimed at sustaining the value of our APC applications. The program reflects our experience in supporting APC applications from multiple vendors installed in 11 different polymerization lines in seven different sites. It will be presented which steps were taken in building such program starting with the cause-effect analysis, where we identify the causes for application malfunction, going through the identification of stakeholders, key performance indicators and assignment of roles and responsibilities.Although the outlined program was built based on the characteristics of the plants and APC applications found in the polymers business, it should be equally applicable to other industries. It is also interesting that the program does not depend on the choice of APC vendor.

Analysis of Advanced Process Control Technology and Economic Assessment Improvement

Advanced Process Control (APC) is considered for investment after the Distributed Control System (DCS) and Historian System of Industrial Automation and Control Systems (IACS) had been implemented. The benefits of APC application can be observed by economic assessment (EA), however the EA technique is still behind the development of APC technology. We review the literature on APC and EA and highlight the potential future development.

INCA MPC4Distillation: A Novel Industrial Solution for Cost-Efficient Non-Linear Distillation Column Modeling and Control

Distillation columns are one of the first unit processes to which MPC (Model-based Predictive Control) was successfully applied in an industrial context. The methodology that is used to execute such APC (Advanced Process Control) projects has not fundamentally changed in the decades that have passed since its inception. Linear black-box models are still the most commonly used type of models in such applications. However, obtaining black-box models by performing dedicated plant tests is often prohibitively time-consuming (and hence costly), which limits the cost-efficient application of APC. On the other hand, in several applications non-linear models offer significant benefits when combined with a high-performance non-linear APC controller.INCA MPC4Distillation employs a novel modeling approach, by combining physical knowledge and historical data in order to identify dynamic models that can be used for APC. This new technology results in accurate non-linear models and does not rely on dedicated step tests, which results in increased benefits to the customer and at a lower cost than existing methods. Experience shows that INCA MPC4Distillation models can typically be obtained in a matter of days, as opposed to several weeks when one would use the classical modeling approaches. The results are illustrated using results obtained on a high-purity binary distillation column.

Application of Advanced Process Control in Circulating Fluidized Bed Boiler

Circulating Fluidized Bed Boiler is a complicated control object with big delay, multi-variable and strong coupling, especially the combustion in it. It is too difficult to build an exact mathematic model to describe the combustion process. And it is hard to get ideal control effect with normal controller. This paper presents the overview of advanced control techniques in thermal process control of Circulating Fluidized Bed Boiler, such as decoupling control, predictive control and fuzzy control. The future of advanced control research and application is also discussed.

Advanced process control applied to distributed control systems

PurposeThe purpose of this paper is to explore concrete design methodology which can improve production technology.Design/methodology/approachAn application of advanced process control (APC) on distributed control systems (DCS) was designed by defining the project target, scope, and control strategy. Calculation is based on heat and mass conservation, such as RPID=FC 203×900×(DC 241 PV‐400)×1.06/500 DC 241 PV; CATRATE=LEVELRATE×0.22×3.14/4. The quality controller writes the control target on the density controller, which writes the initial value or output value onto the DCS.FindingsThe technique has dramatically increased the control quality of the DCS system: production capacity of the equipment has been improved and the aim of fecundity with little input is realized. The transit time of the product name is shortened and the excess stock is reduced.Originality/valueThe paper is aimed at operational researches and engineers.

Accuracy and Real-Time Considerations for Implementing Various Virtual Metrology Algorithms

In the semiconductor industry, run-to-run (R2R) control is an important technique to improve process capability and further enhance the production yield. As the dimension of electronic devices shrink increasingly, wafer-to-wafer (W2W) advanced process control (APC) becomes essential for the critical stages of production processes. W2W APC requires the metrology values of each wafer; however, it will be highly time and cost consuming to obtain actual metrology values from each wafer by physical measurement. Recently, an efficient and cost-effective approach denoted virtual metrology (VM) was proposed to substitute the actual metrology. To implement VM in W2W APC, both conjecture-accuracy and real-time requirements need to be considered. In this paper, various VM algorithms, including back-propagation neural networks (BPNN), simple recurrent neural networks (SRNN), and multiple regression (MR), are evaluated to see whether they can meet the accuracy and real-time requirements of W2W APC or not. The fifth generation TFT-LCD chemical-vapor deposition process is used to test and verify the requirements. Test results show that both one-hidden-layered BPNN and SRNN VM algorithms achieve acceptable conjecture accuracy and meet the real-time requirements of semiconductor and TFT-LCD W2W APC applications.

An Identification Method Based on the Improved NLJ Algorithm and Its Application

The accurate model is the most important and basic condition for the application of advanced process control, but the conventional methods do not provide satisfactory results in the case of unstable processes. To effectively control these processes, a novel identification method (Model Parameters and Initial States Identification simultaneously in closed loop —MPISI) is proposed. The model parameters and initial states of state equation can be simultaneously identified using this method. The results of simulation and application show that this method has the advantageous of disturbance-rejection and robustness. This method proposes a novel way for the optimization and the advanced control of the process systems.

BAYER PROCESS CONTROL AT ALCAN VAUDREUIL WORKS

Alcan Vaudreuil Works is the only alumina plant in Canada. The plant produces about 1.4 milion tons of alumina per year, using the Bayer process to treat bauxite ore. In addition to regulatory control, this complex extraction process involves many applications of advanced process control. Techniques such as adaptative control, multivariable control (model based predictive control), fuzzy logic, on-line models and expert systems are used. This paper will first introduce the Bayer process and present the different types of control commonly used. Three examples of closed loop advanced process control applications will be presented.

Innovation in milk powder technology

Global trade in preserved milks is on the increase as new markets open up in regions of the world that have not been traditionally associated with milk consumption. Equally, a rise in world milk production is forecasted to continue, and the indications are that significant quantities of the extra milk produced will be converted to commodity products such as butter and powders. Consequently, on‐going investment in new spray drying capability is likely to track geographical shifts in milk production. Successful application of advanced process control to the operation of large scale drying plant is both a priority and a challenge. Meanwhile, opportunities for the exploitation of milk as a source of functional ingredients are being availed of by the dairy industry as it continues to achieve added value and unique key selling points. Recent research on the role of spray drying, along with other processes in the development of dairy ingredients for applications in chocolate and the preparation of microencapsulated powders, is reviewed.

Potential use of advanced process control for safety purposes during attack of a process plant

Many refineries and commodity chemical plants employ advanced process control (APC) systems to improve throughputs and yields. These APC systems utilize empirical process models for control purposes and enable operation closer to constraints than can be achieved with traditional PID regulatory feedback control. Substantial economic benefits are typically realized from the addition of APC systems. This paper considers leveraging the control capabilities of existing APC systems to minimize the potential impact of a terrorist attack on a process plant (e.g., petroleum refinery). Two potential uses of APC are described. The first is a conventional application of APC and involves automatically moving the process to a reduced operating rate when an attack first begins. The second is a non-conventional application and involves reconfiguring the APC system to optimize safety rather than economics. The underlying intent in both cases is to reduce the demands on the operator to allow focus on situation assessment and optimal response planning. An overview of APC is provided along with a brief description of the modifications required for the proposed new applications of the technology.

Thickness metrology and end point control in W chemical vapor deposition process from SiH4/WF6 using in situ mass spectrometry

Real-time, in situ chemical sensing has been applied to achieve reaction metrology and advanced process control in a low pressure tungsten chemical vapor deposition process based on WF6 and SiH4 reactants (silane reduction process). Using mass spectrometry as the sensor to detect both product generation (H2) and reactant depletion (SiH4) at wafer temperature of 200–250 °C, these signals provided a direct real-time measurement of deposited film thickness with an uncertainty less than 2%, and this thickness metrology signal was employed to achieve real-time process end point control. When reactant conversion rates are sufficient (∼20% in this case) as often occurs in manufacturing processes, the thickness metrology (1.0%–1.5%) and control (∼1.5%–2.0%) accuracies are in the regime needed for meaningful application of advanced process control. Since the in situ sensor delivers a metrology signal in real time, real-time process control is achieved, enabling compensation for random process disturbances during an individual process cycle as well as for systematic wafer-to-wafer process drifts. These results are promising for manufacturing from the standpoints of metrology accuracy and application in real-time control.

Advanced process control and on-line optimisation in shell refineries

Within the Shell Group, Advanced Process Control and On-line Optimisation have a growing number of applications. Use is made of Shell Multi-variable Optimising Control packages and the On-line Optimisation package, using reduced algorithm method. In particular, applications have been made for Crude Distillation units, Catalytic Cracking units, Catalytic Reformers and Gas Separation plants. Crude Distiller Advanced Process Control applications, as well as the On-line Optimisation of a Catalytic Cracking complex, at SHELL'S Stanlow refinery in the UK, will be addressed in the paper.