1.
Concept of Smart Manufacturing
Definition: Smart Manufacturing (SM) is a data-driven, technology-enabled production process where
information is available when and where needed to optimize tasks. It integrates advanced technologies to
enhance efficiency, flexibility, and quality in manufacturing.
Key Features:
- Utilizes cyber-physical systems (CPS) for real-time monitoring and control.
- Enables decentralized decision-making and self-organized tasks.
- Driven by connectivity and real-time data for agile production.
2. History of Industrial Revolution
The Industrial Revolution transformed production methods and societal structures through four phases:
Industry 1.0 (1750-1870):
- Marked by mechanization, water, and steam power.
- Key developments: Spinning jenny, power loom, and steam engines.
- Impact: Shift from manual labor to factories, rural-to-urban migration.
Industry 2.0 (1870-1960):
- Introduction of electricity and mass production.
- Key developments: Steel production, internal combustion engines, and assembly lines.
- Impact: Urbanization, improved transportation (trains, cars), and technological advancements.
Industry 3.0 (1960s-2000s):
- Focus on automation, computers, and electronics.
- Key developments: CNC machines, programmable logic controllers (PLCs), and rapid prototyping.
- Impact: Increased productivity, reduced human error, and the Green Revolution in agriculture.
Industry 4.0 (Present):
- Defined by the "Internet of Things and Services."
- Integrates physical, digital, and biological systems using advanced technologies.
- Impact: Smart factories, real-time data analytics, and sustainable production.
3. Nine Pillars of Industry 4.0
Industry 4.0 leverages interconnected technologies to create smart, efficient manufacturing systems. The
nine pillars are critical for understanding its framework:
1. Big Data and Analytics:
- Involves processing large volumes of structured/unstructured data from IoT devices, logs, and sensors.
- Purpose: Identify patterns, trends, and insights for real-time decision-making.
- Example: Predictive maintenance and process optimization.
2. Autonomous Robots:
- Smart robots with sensors and microprocessors for tasks like material handling and assembly.
- Features: Self-navigation, collaboration, and real-time adaptability.
- Example: Autonomous mobile robots (AMRs) for shop floor logistics.
3. Additive Manufacturing (AM):
- Involves 3D printing to create objects layer-by-layer using materials like liquid, powder, or sheets.
- Advantages: Complex geometries, reduced material waste, and rapid prototyping.
- Example: Custom parts production in aerospace and medical fields.
4. Simulation/Digital Twin:
- Digital twin: A virtual model of a physical system updated with real-time sensor data.
- Uses: Process control, product lifecycle management, and system simulation.
- Example: Simulating factory operations to optimize workflows.
5. Industrial Internet of Things (IIoT):
- Connects machines, sensors, and systems for data sharing and automation.
- Features: Machine-to-machine communication and data-driven intelligence.
- Example: Real-time monitoring of equipment health.
6. Augmented Reality (AR):
- Overlays digital information (images, videos) onto the physical world.
- Applications: Training, diagnostics, virtual factory planning, and product development.
- Example: AR-based maintenance guidance for technicians.
7. Cyber Security:
- Protects internet-connected systems from cyber threats like phishing, malware, and ransomware.
- Components: Application security, network security, operational security, information security, and
end-user education.
- Importance: Safeguards sensitive data, intellectual property, and national security.
8. Cloud Computing:
- Uses remote servers to store, manage, and process data.
- Types: Public and private clouds.
- Benefits: Scalability, real-time data access, and support for smart device functionality.
9. Horizontal and Vertical System Integration:
- Vertical Integration: Connects systems within a factory for agility and reconfigurability.
- Horizontal Integration: Links partners across the supply chain for optimized performance.
- Example: Cloud-based platforms for seamless data sharing among stakeholders.
