SECTION A
(Attempt all – 2 × 10 = 20 marks)
(a) Computerized Process Control
Computerized Process Control is the use of digital computers to monitor, control, and regulate industrial processes automatically by processing sensor data and sending control signals to actuators.
(b) Concept of Aided Process Control
Aided Process Control is a semi-automatic control system where computers assist human operators by providing calculations, monitoring, and decision support, while final control actions are taken manually.
(c) Industrial Communication System
An industrial communication system is a network that enables data exchange between sensors, controllers, computers, and actuators in industrial automation for monitoring and control.
(d) Need of Communication Networking
Communication networking is needed to ensure fast, reliable, and accurate data transfer between field devices, controllers, and supervisory systems for effective process control.
(e) Process Modelling
Process modelling is the mathematical representation of a physical process that describes the relationship between inputs, outputs, and system variables.
(f) Need of Process Model
Process models are required for system analysis, controller design, simulation, prediction of system behavior, and performance improvement.
(g) Cascade Control
Cascade control is a control strategy where one controller’s output sets the reference for another controller, improving response speed and disturbance rejection.
(h) Predictive Control
Predictive control uses a mathematical model to predict future process behavior and computes control actions in advance to optimize system performance.
(i) Electric Oven Temperature Control
Electric oven temperature control maintains desired temperature using sensors, controllers, and heaters to ensure uniform heating and energy efficiency.
(j) Furnace Temperature Control
Furnace temperature control regulates high-temperature industrial furnaces using feedback control to maintain consistent temperature for safe and efficient operation.
SECTION B
(Attempt any three – 10 × 3 = 30 marks)
2(a) Thickness and Flatness Control System in Metal Rolling
In metal rolling industries, thickness and flatness control ensure uniform sheet quality. Sensors measure strip thickness and shape, while computers adjust roll gap, pressure, and speed in real time. Computerized control improves product quality, reduces waste, and increases productivity.
2(b) Data Transfer Techniques in Industrial Communication System
Industrial data transfer techniques include serial communication, parallel communication, fieldbus systems, Ethernet-based protocols, and wireless communication. These techniques ensure reliable, noise-free, and real-time data exchange between devices in harsh industrial environments.
2(c) Physical Model, Control Model, and Process Modelling
A physical model represents the actual system using physical laws.
A control model focuses on input-output relationships for controller design.
Process modelling combines mathematical equations and system behavior to simulate and optimize industrial processes.
2(d) Need and Advantages of Advanced Strategies in Computerized Process Control
Advanced strategies like adaptive, predictive, and inferential control are required for complex processes. They improve accuracy, reduce energy consumption, handle disturbances, and optimize overall system performance.
2(e) Role of Computers in Process Control
Computers perform data acquisition, real-time monitoring, control calculations, optimization, alarm handling, and data storage. They improve precision, reliability, safety, and efficiency of industrial processes.
SECTION C
(Attempt any one part from each question – 10 × 5 = 50 marks)
3(a) Computer-Aided Control of Electric Power Generation Plant
Computer-aided control in power plants monitors boiler pressure, turbine speed, voltage, and frequency. Computers ensure efficient load sharing, fault detection, safety interlocks, and optimal power generation with minimum losses.
4(a) Elements of Computer-Aided Process Control System
The main elements include sensors, signal conditioners, data acquisition systems, computers, control algorithms, actuators, communication networks, and human-machine interfaces. Together they provide automated and efficient process control.
5(a) Adaptive Control and Inferential Control
Adaptive control adjusts controller parameters automatically when process conditions change.
Inferential control estimates difficult-to-measure variables using easily measured signals and process models to improve control accuracy.
6(b) Types of Computer Control Process Software
Computer control software includes real-time operating systems, SCADA software, DCS software, PLC programming tools, and simulation software used for monitoring, control, and analysis of industrial processes.
7(a) Model Formulation, Solution Finding, and Results Analysis
Model formulation defines mathematical equations of the process.
Solution finding involves solving these equations using numerical or analytical methods.
Results analysis evaluates system performance and validates the model for control applications.
