
Explore industrial automation and intelligent control systems through five modules covering production automation, TLC architecture and applications, SCADA, distributed control, human machine interface, and model-based advanced process control.
Explore the five levels of automation in industry—from device level to enterprise level—showing how sensors, machines, cells, and plant operations integrate under ERP-driven management.
Examine storage system performance and location strategies, comparing conventional bulk, rack, shelving, and drawer storage with automated ASRS and carousel systems, plus engineering analyses of capacity, density, throughput, and accessibility.
Explore material handling systems: movement, storage, and control of materials throughout manufacturing and distribution, with internal and external logistics, transport modes, and identification and tracking.
Discover automated guided vehicles, self-propelled and battery-powered, moving along predefined factory paths. Identify agv categories—driverless trains, pallet trucks, unit load carriers—and navigation, capacities, and key applications.
Explore advanced automation functions, including safety monitoring, maintenance and repair diagnostics, and error detection and recovery, with PLC, SCADA, HMI, and VFD integration.
Learn about programmable logic controllers (plcs): their architecture, applications, ladder diagram programming, input/output devices, and how series and parallel wiring realize and or logic in industrial automation.
Explore programming programmable controllers using ladder diagrams, including timer and counter functions, get/put word operations, and arithmetic and comparison blocks to enable sequential and event-driven control.
Explore series-parallel PLC circuits and and-or logic using input contacts, control relays, and not gates to drive safe motor interlocks and indicator lamps.
Examine manually and mechanically operated PLC switches, including push buttons, selector switches, limit switches, and temperature, pressure, and float level switches, plus latching relays, interlocks, and sequential relays.
Discover how timers and counters drive PLC programs, from on/off and retentive timers to up/down and up-down counters, with ladder logic applied to conveyors, traffic lights, and parking systems.
Explore arithmetic operations and interlocks in PLCs, including addition, subtraction, multiplication, division, modulus, trig, exponential and logarithmic functions and square roots, with ladder logic examples Fahrenheit to Celsius conversion.
Explore latching relays and sequential relays with PLCs, showing how a latch keeps a motor energized and how sequential start with timers reduces peak power.
Explore hands-on PLC gate design with the VLAB PLC simulator, building series and parallel circuits, testing inputs and outputs, and mastering tagging, compile, and run steps.
Engage in hands-on plc arithmetic with the VLAB simulator, configuring inputs A and B, performing addition, subtraction, multiplication, and division, and validating results via compile, run, and toggle.
Explore hands-on PLC timing and counting with the VLAB PLC simulator, configuring on-delay and off-delay timers using preset values, compile and run to observe enable and done bits.
Identify intelligent electronic devices (IED) as microprocessor-based regulators enabling real-time monitoring, protection, metering, fault recording, and interoperable Scada communication with RTUs.
Examine SCADA system security, PLC and RTU and IED architectures, and perimeter protections, detailing vulnerability taxonomy, severity charts, and secure coding practices to protect industrial processes.
Explore scada, it/ot technologies, and dms oms systems within industrial automation and intelligent control systems.
Explore how SCADA LAQS enables temperature monitoring across distributed plants with dashboards, reports, and graphs, including production, maintenance, and stop states, with tutorials and animated examples.
Discover the SCADA water treatment monitoring workflow in LAQS, including downloading the water treatment example and creating tag-based reports, with setup of historical databases, servers, and Modbus communications.
Explore the SCADA LAQS software to monitor three equipment units, view analog and digital alarms, generate graph-backed reports, and analyze alarms with time stamps and logs.
Explore industrial automation and intelligent control systems through an introduction to the distributed control system.
Learn to perform sensor signal conditioning in Python by applying moving average and Butterworth filters to noisy sensor data, reducing noise and preserving signal patterns.
Module 4 covers interfaces in DCS in industrial automation and intelligent control systems. Explore interfaces in DCS across industrial automation and intelligent control systems.
Explore hands-on Python in industrial automation by building a low-level human interface (llhi) to control a tank valve, simulate inflow and outflow, and plot the tank level history.
Explore a python hands-on session on changing setpoints via a high level interface and using a proportional controller to drive the manipulator variable and plot the process variable with matplotlib.
Explore how to manage DCS operator interfaces with Python, including low level and high level interfaces, alarm management, and valve control in manual and automatic modes.
Explore engineering interfaces within industrial automation and intelligent control systems, examining how interfaces enable integration across automation components and control architectures.
Explore a hands-on Python implementation of the sugar plant crystallization using the vacuum pan (PAN), Briggs value, and supersaturation within a DCS architecture for batch operation and trend logging.
simulate a paper plant DCS in Python, acquire data, detect disturbances, and trigger alarms; visualize four sections with bar gauges and trends, showing set points and limits for control concepts.
Explore the different types of plant automation and their roles within industrial automation and intelligent control systems.
Explore module 5 steel plant within industrial automation and intelligent control systems, highlighting automation approaches for steel production and the role of intelligent control in optimizing processes.
Apply a model-based systems engineering approach to a Python-simulated bottle filling line, using random data, time sequencing, and CSV logging to analyze efficiency.
Explore a Python hands-on neural network controller, covering sigmoid activation, forward and backward passes, weight updates, and McCulloch-Pitts models.
Explore hands-on model predictive control with Python, comparing PID and MPC performance using a plant model, set points, and disturbances, and learn to simulate, optimize, and visualize results.
Explore pid controllers, detailing proportional, integral, and derivative actions, their transfer functions, and parallel, series, and expanded forms for robust industrial control.
Explore hands-on PID control in Python, comparing parallel and series structures to regulate a water tank level with set point 1 meter and kp ki kd gains.
Explore fuzzy logic based control, translating vague data into rules and using linguistic variables, membership functions, fuzzification, inference, and defuzzification to drive actuators.
Apply fuzzy logic to a water tank: fuzzify the water level (0–10), evaluate rules, and defuzzify via centroid to a crisp valve opening.
Demonstrate building a fuzzy logic water level controller in Python using scikit-fuzzy, numpy, and matplotlib, including membership functions, rules, and valve opening simulations.
This in-depth course on Industrial Automation & Intelligent Control Systems provides a complete understanding of how modern industries achieve high efficiency, precision, and reliability through automation. The course bridges theory and practical applications, making it ideal for engineers, students, and professionals aiming to build or upgrade their skills in industrial automation and intelligent control technologies.
The curriculum begins with the fundamentals of control systems, sensors, transducers, actuators, and signal conditioning, progressing toward programmable control using PLCs, DCS, and SCADA systems. Learners will develop the ability to design ladder logic, implement PID control, and interface sensors and drives with automation hardware. Real-world simulation tools and examples are used to provide hands-on exposure to automation project design.
As industries evolve toward Industry 4.0, the course introduces intelligent and adaptive control methods using artificial intelligence (AI), fuzzy logic, and neural networks. It also covers machine learning-based predictive maintenance, IoT-enabled smart factories, and digital twin concepts. Special attention is given to industrial communication protocols such as Modbus, Profibus, and Ethernet/IP, along with cybersecurity aspects in automation.
Practical case studies from manufacturing, robotics, process plants, and renewable energy systems illustrate the integration of intelligent control systems in real industrial settings. By the end of the course, learners will be proficient in designing and managing automated systems, optimizing performance, and deploying intelligent control strategies for next-generation industrial environments.
Key Highlights:
Comprehensive understanding of PLC, DCS, and SCADA systems
Intelligent control techniques: fuzzy logic, neural networks, and AI integration
Industrial IoT (IIoT) and digital transformation concepts
Real-world case studies and hands-on simulations
Focus on industrial communication, safety, and cybersecurity
Ideal for automation engineers, process control professionals, and engineering students