Integrating real-time simulation models into a SCADA environment : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology at Massey University

Control system engineers have always envisaged the prospect of using the real-time models in an industrial setting. The inclusion of the real-time models can benefit industry in the following ways. 1. Operator Training - The operator can learn about how the various process react to control actions with the help of simulation models without affecting the real process itself. 2. Control Systems testing - The simulation models can be helpful in testing the control system software prior to trialing it on the real process. 3. Proccss Monitoring - Operators can compare the real process outputs with the simulation model outputs. This helps them in stopping the process when unusual conditions occur. 4. Testing for optimum operating conditions - Simulation models can be used to test for optimum operating conditions or for testing a certain operation at a new operating condition without affecting the real process. 5. Implementation of advanced control strategies - Advanced control strategics such as multivariable control, model predictive control and non linear control can be implemented as a real-time model without the development of separate real-time software. Even though using the real-time models can benefit the industry as mentioned modeling and real-time models have not found much favour in the industry. The reasons for this may be as follows: 1. Lack of awareness - Most of the plant managers/operators fail to understand what modeling results in and how it can improve the overall plant operation. 2. Lack of expertise - There is no expertise and/or tools in the company to develop the simulation models and implement it. 3. Cost of modeling - Producing a simulation model incurs significant costs. 4. Cost of implementation - Once the model is developed in the development environment it has to be transferred to the industrial platform. The cost of this transfer is high as the model software has to be more robust than the general purpose software. In order to produce real-time simulation models for an industrial setting there are two significant environments required. These are the development environment where the model is developed and secondly the implementation environment, where the model is used

COMPUTER CONTROL OF AN INDUSTRIAL PLANT

This report describes the objective, scope of study, problem identification, methodology and the experimentation of the project involves in the development of computer control for an industrial process plant. The project involves the development of computer control for industrial process plant. The objectives of the project are to design and tune a PID controller for the control of temperature in a Gaseous Pilot Plant via real-time using Matlab/Simulink. The Gaseous Pilot Plant in the Plant Process Laboratory, Universiti Teknologi PETRONAS is chosen as the case study. Specifically, the focus is on the monitoring and controlling the temperature of the gas medium in the Gaseous Pilot Plant. The PID controller will operate based on the characteristic and properties of the process. The response of the temperature can be controlled and monitored in real-time during the experimentation process. An extensive study to understand the process plant operation and obtaining its parameters for use in the PID controller have been conducted. Modelling and simulation involves the Matlab/Simulink modelling and the PID controller design. In the experimentation stage, the system's performance is conducted and the result is compared. The real-time PID control of the plant via Matlab/Simulink has been successfully demonstrated on the pilot plant and a number of key results obtained in the development process are presented

On neuro-fuzzy applications for automatic control, supervision, and fault diagnosis for water treatment plant

Water treatment includes many complex phenomena, such as coagulation and flocculation. These reactions are hard or even impossible to control satisfyingly by conventional methods. Biological water treatment systems are difficult to model because their performance is complex and varies significantly with different reactor configurations, influent characteristics, and operational conditions. Neuro-fuzzy ANFIS method, which is chosen as the method in this case, is a new intelligent method in this line of process industry. Although intelligent tools such as neural network, fuzzy logic and neuro-fuzzy methods have been applied in real time water treatment plant for some time, problems of monitoring water treatment processes and assessing uncertainty for the coagulant dosing rate represent a major challenged that need to be investigated. In this research, statistical methods are used to analyze nonstationary time series water treatment process where they are accrued from a neuro-fuzzy ANFIS model. The proposed scheme is evaluated in computer simulation studies using real process data before application to the real plant

MONITORING AND CONTROLLING A PROCESS USING OVERRIDE CONTROLLER & ANTI WINDUP

The project involves the design and analysis and implementation of controller for industrial process plant. The objectives of the project are to design an override controller and anti windup for the control of pressure in a Gaseous Pilot Plant via real-time using Matlab/Simulink.. The Gaseous Pilot Plant in the Plant Process Laboratory, Universiti Teknologi PETRONAS is chosen as the case study. Specifically, the focus is on the monitoring and controlling the pressure of the gas medium in the Gaseous Pilot Plant. The PID and Override controllers operate based on the characteristic and properties of the process. The response of the pressure can be controlled and monitored in real-time during the experimentation process. These involved an extensive study to understand the process plant operation and obtaining its parameters for use in the PID controller have been conducted. Modeling and simulation involves the Matlab/Simulink modeling and the PID controller design. The external feedback is implemented to reduce the anti windup. The results indicate that the override control and anti-windup can be achieved for Pl control. In the case for PID, the responses are too fast, while very slow performance for the P control

A Method for Real-Time Aggregation of a Product Footprint during Manufacturing

To assess cost, time investment, energy consumption and carbon emission of manufacturing on a per-piece basis, a bottom-up approach for aggregating a real-time product footprint is proposed. This method allows the evaluation of the environmental impact of a batch or even single product using monitoring or simulation data. To analyze the infrastructure, the production plant is decomposed into modules that are in relation to each other via inputs and outputs. Distinguishing between modules for production, logistics, energy system, buildings and auxiliary systems, the different approaches for distributing resource consumption between the products are presented. Special attention is paid to typical scenarios that occur in production plants and problems that may arise from them. For example, the incorporation of standby-, setup- and ramp-up times, the energy consumption of the administration and the allocation of different products and by-products manufactured at a machine are taken into account

Collision Prevention In Operation-Synchronized Simulations Using Dynamic Prescheduling Of Simulation Parameters

The increasing use of simulation technologies, especially virtual commissioning, in the context of modern plant development for manufacturing discrete parts is driven by the pressure to shorten time-to-market cycles and overcome supply bottlenecks. The need for robust technologies to seamlessly integrate the digital and physical world is growing as machine data becomes more readily available. A challenge to this integration is presented by the need to continuously adjust the movement parameters, especially for event-discrete actuators based on live data, taking wear, ageing and process-time fluctuations into account. A lack of synchronization leads to discrepancies between the simulation and reality renders them useless. Related works in this field are discussed, which highlight the complexities of achieving synchronization between simulation and reality, particularly in event-discrete signals and systems. The aim of this article is to present a method for reusing virtual commissioning models for operation-synchronized simulations at actuator level. This approach includes introducing of a methodology called prescheduling in order to compensate process uncertainties and also defines the necessary requirements for the simulation tool and model. The method is validated using an industrial test system and a commercial virtual commissioning tool to confirm its suitability for real-life implementation in industrial plants, which suggests its suitability for improving production efficiency and reducing costs by means of machine monitoring and proactive control interventions

PERANCANGAN SIMULATOR SISTEM SCADA PUSAT LISTRIK TENAGA NUKLIR JENIS FAST BREEDER REACTOR

Simulator sistem SCADA (Supervisory Control and Data Acquisition) merupakan software berbasis Human Machine Interface yang mampu memvisualisasikan proses sebuah plant. Penelitian ini menjelaskan hasil dari perancangan simulator sistem SCADA yang bertujuan untuk memudahkan operator dalam melakukan pengawasan, pengendalian, penanganan alarm, akses ke historical data dan historical trend pada Pusat Listrik Tenaga Nuklir (PLTN) jenis Fast Breeder Reactor (FBR). Simulasi ini menggunakan data teknis PLTN Kalpakkam India. Simulator ini dikembangkan menggunakan software Wonderware Intouch 10 yang dilengkapi dengan main menu, plant overview, area graphics, control displays, setpoint display, alarm system, real-time trending, historical trending dan security system. Simulator ini dapat mensimulasikan secara baik prinsip dari aliran energi dan proses konversi energi pada PLTN jenis FBR. Simulator sistem SCADA dapat digunakan sebagai media pelatihan untuk operator plant.;--- SCADA (Supervisory Control and Data Acquisition) system simulator is a Human Machine Interface-based software that is able to visualize the process of a plant. This study describes the results of the process of designing a SCADA system simulator that aims to facilitate the operator in monitoring, controlling, handling the alarm, accessing historical data and historical trend in Nuclear Power Plant (NPP) type Fast Breeder Reactor (FBR). This simulation used technical data from NPP Kalpakkam, India. This simulator was developed using Wonderware Intouch software 10 and is equipped with main menu, plant overview, area graphics, control display, setpoint display, alarm system, real-time trending, historical trending and security system. This simulator can properly simulate the principle of energy flow and energy conversion process on NPP type FBR. This SCADA system simulator can be used as training media for plant operators

COMPUTER CONTROL OF AN INDUSTRIAL PLANT

This report describes the objective, scope of study, problem identification, methodology and the experimentation of the project involves in the development of computer control for an industrial process plant. The project involves the development of computer control for industrial process plant. The objectives of the project are to design and tune a PID controller for the control of temperature in a Gaseous Pilot Plant via real-time using Matlab/Simulink. The Gaseous Pilot Plant in the Plant Process Laboratory, Universiti Teknologi PETRONAS is chosen as the case study. Specifically, the focus is on the monitoring and controlling the temperature of the gas medium in the Gaseous Pilot Plant. The PID controller will operate based on the characteristic and properties of the process. The response of the temperature can be controlled and monitored in real-time during the experimentation process. An extensive study to understand the process plant operation and obtaining its parameters for use in the PID controller have been conducted. Modelling and simulation involves the Matlab/Simulink modelling and the PID controller design. In the experimentation stage, the system's performance is conducted and the result is compared. The real-time PID control of the plant via Matlab/Simulink has been successfully demonstrated on the pilot plant and a number of key results obtained in the development process are presented

A Modeling and Analysis Framework To Support Monitoring, Assessment, and Control of Manufacturing Systems Using Hybrid Models

The manufacturing industry has constantly been challenged to improve productivity, adapt to continuous changes in demand, and reduce cost. The need for a competitive advantage has motivated research for new modeling and control strategies able to support reconfiguration considering the coupling between different aspects of plant floor operations. However, models of manufacturing systems usually capture the process flow and machine capabilities while neglecting the machine dynamics. The disjoint analysis of system-level interactions and machine-level dynamics limits the effectiveness of performance assessment and control strategies. This dissertation addresses the enhancement of productivity and adaptability of manufacturing systems by monitoring and controlling both the behavior of independent machines and their interactions. A novel control framework is introduced to support performance monitoring and decision making using real-time simulation, anomaly detection, and multi-objective optimization. The intellectual merit of this dissertation lies in (1) the development a mathematical framework to create hybrid models of both machines and systems capable of running in real-time, (2) the algorithms to improve anomaly detection and diagnosis using context-sensitive adaptive threshold limits combined with context-specific classification models, and (3) the construction of a simulation-based optimization strategy to support decision making considering the inherent trade-offs between productivity, quality, reliability, and energy usage. The result is a framework that transforms the state-of-the-art of manufacturing by enabling real-time performance monitoring, assessment, and control of plant floor operations. The control strategy aims to improve the productivity and sustainability of manufacturing systems using multi-objective optimization. The outcomes of this dissertation were implemented in an experimental testbed. Results demonstrate the potential to support maintenance actions, productivity analysis, and decision making in manufacturing systems. Furthermore, the proposed framework lays the foundation for a seamless integration of real systems and virtual models. The broader impact of this dissertation is the advancement of manufacturing science that is crucial to support economic growth. The implementation of the framework proposed in this dissertation can result in higher productivity, lower downtime, and energy savings. Although the project focuses on discrete manufacturing with a flow shop configuration, the control framework, modeling strategy, and optimization approach can be translated to job shop configurations or batch processes. Moreover, the algorithms and infrastructure implemented in the testbed at the University of Michigan can be integrated into automation and control products for wide availability.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147657/1/migsae_1.pd