Automation Glossary – In-Depth Definitions and Concepts

1. Automation

Automation is the deployment of technology to execute tasks, processes, or operations with minimal or no human intervention. This involves advanced control systems, sensors, actuators, communication networks, and software to perform actions once done manually. According to the International Society of Automation (ISA), automation encompasses the creation and application of technology to monitor and control the production and delivery of products and services.

In aviation, automation is vital for flight management systems, autopilot, air traffic control, and maintenance diagnostics. It drives innovation in manufacturing (Industry 4.0), smart infrastructure, and transportation, leveraging real-time data, IoT, and AI for performance, safety, and efficiency.

Key elements:

• Sensors for data collection
• Controllers for processing and command issuance
• Actuators for executing actions
• Communication networks (e.g., fieldbus, Ethernet)
• Human-Machine Interfaces (HMI) for monitoring and control

ICAO standards ensure automation in aviation is safe, reliable, and interoperable, requiring redundancy, fail-safes, and human oversight.

2. Automatic Operation

Automatic operation means a system or device completes a sequence of actions without continuous human input, following preset instructions or environmental triggers. Unlike broader automation, automatic operation usually implies fixed responses and lacks adaptive or learning abilities.

Aviation examples:

• Autopilots maintaining course, altitude, and speed
• Automatic landing systems guiding aircraft during approach and touchdown
• ADS-B, which transmits aircraft position and velocity

Automatic operations enhance safety, consistency, and reliability. ICAO guidelines require clear operation modes, operator feedback, and fail-safes.

Distinction:
Automatic systems execute predefined actions; automated systems can adapt and optimize based on data.

3. Automated System

An automated system integrates devices, software, and networks to execute complex operations with minimal human intervention, often including real-time sensing, feedback, and adaptive logic.

Components:

• Distributed control systems (DCS), programmable logic controllers (PLC)
• SCADA for monitoring and oversight
• Embedded software for real-time tasks
• Diagnostic/prognostic algorithms

Aviation examples:

• Flight management and navigation
• Engine monitoring and predictive maintenance

ICAO standards ensure software assurance, redundancy, and effective human-machine interface (HMI) design for operational safety.

4. Industrial Automation

Industrial automation uses control systems (computers, robots, IT) to manage machinery and processes, reducing human effort in sectors like manufacturing, chemical processing, and logistics.

Features:

• Programmable controllers
• Robotic arms for repetitive or hazardous tasks
• Machine vision for inspection
• Automated guided vehicles (AGVs)
• ERP integration

Aviation application:
Robotics in aircraft manufacturing (drilling, riveting, painting), automated diagnostics, and inventory management.

ICAO mandates industrial automation in aviation follow safety and quality assurance processes.

5. Robotic Process Automation (RPA)

RPA uses software bots to mimic human actions for rule-based, repetitive digital tasks, increasing speed and accuracy.

Aviation uses:

• Passenger data reconciliation
• Flight scheduling and crew rostering
• Maintenance record-keeping
• Invoice processing

RPA’s value is rapid deployment and legacy system integration. It is foundational to intelligent automation, incorporating AI and ML.

6. Intelligent Automation (IA) / Intelligent Process Automation (IPA)

Intelligent Automation combines RPA with AI, ML, natural language processing (NLP), and analytics. It enables automation of cognitive tasks—understanding unstructured data, decision-making, and learning.

Aviation transformation:

• Predictive maintenance using AI models
• Virtual assistants for customer service
• Flight route and fuel optimization
• Security screening with behavioral analytics

IA adoption requires strong governance and transparency for regulatory compliance.

7. Programmable Logic Controller (PLC)

PLCs are specialized digital computers for real-time automation of industrial processes, valued for reliability and programming flexibility (ladder logic, block diagrams).

Applications:

• Manufacturing assembly lines
• Baggage handling in airports
• Fuel farm and lighting management

PLCs are rugged, support redundancy, and are essential in aviation infrastructure for safety-critical automation.

8. Human-Machine Interface (HMI)

HMIs are the interfaces (graphical or physical) through which operators interact with automated systems, providing visualization, control, and data logging.

Aviation/industry examples:

• Touchscreen panels in control towers
• Cockpit multifunction displays
• Maintenance workstations

Good HMI design is critical for situational awareness, decision-making, and error prevention.

9. Fieldbus

Fieldbus is a set of industrial network protocols for real-time distributed control and communication between automation devices.

Aviation uses:

• Baggage handling
• Airfield lighting
• Fuel management
• Building automation

Fieldbus simplifies wiring, supports scalability, and enables remote diagnostics. Integration with industrial Ethernet and wireless is growing.

10. Artificial Intelligence (AI)

AI in automation refers to systems capable of tasks requiring human-like intelligence—reasoning, learning, decision-making.

Aviation AI:

• Machine learning for anomaly detection and predictive analytics
• NLP for virtual assistants and controls
• Computer vision for surveillance and inspection

ICAO emphasizes transparency, accountability, and validation for integrating AI into aviation systems.

11. Machine Learning (ML)

ML is a subset of AI focused on algorithms that learn from data and make predictions or decisions.

Aviation ML applications:

• Engine health monitoring
• Passenger flow/resource prediction
• Cybersecurity threat detection
• Air traffic flow optimization

ML transitions operations from reactive to proactive, enhancing safety and efficiency.

12. Hyperautomation

Hyperautomation combines RPA, AI, ML, and other technologies to automate complex processes end-to-end.

Aviation examples:

• Integrated flight operations management
• Airport resource optimization
• Regulatory compliance monitoring
• Passenger journey orchestration

Hyperautomation platforms discover, automate, and optimize both structured and unstructured tasks.

13. Sensors

Sensors detect and measure physical, chemical, or environmental variables, providing the data backbone for automation.

Types:

• Temperature, pressure, and proximity sensors
• Optical sensors (photodiodes, LIDAR)
• Accelerometers and gyroscopes

Aviation roles:

• Flight control
• Engine health monitoring
• Environmental and safety systems

ICAO requires rigorous testing of aviation sensors for accuracy and reliability.

14. Actuators

Actuators convert control signals into physical action, executing automation system commands.

Types:

• Electric motors
• Solenoid valves
• Hydraulic/pneumatic cylinders
• Servo actuators

Aviation applications:

• Flight control surfaces
• Landing gear
• Engine throttle/fuel control
• Cabin pressure regulation

Actuator reliability and response time are critical, with ICAO specifying redundancy for safety.

15. Communication Protocols and Fieldbus

Communication protocols standardize data exchange in automation. Fieldbus protocols are designed for real-time, distributed industrial control.

Common protocols:

• PROFIBUS/PROFINET
• CAN bus
• Modbus
• Ethernet/IP

Aviation infrastructure:

• Automated baggage handling
• Lighting control
• Building/security automation

ICAO standards require secure, redundant, and interoperable communication protocols.

16. Types of Automation

Automation can be categorized by adaptability and complexity:

Selection depends on process variability, volume, regulation, and integration needs.

17. Comparison: Automation vs. Automatic

For further details on each automation concept, consult ICAO documentation, ISA standards, and leading industry resources.