# Industry 4.0

> 4th Industrial revolution or current trend of automation and data exchange in manufacturing technologies 4.0

**Wikidata**: [Q1661989](https://www.wikidata.org/wiki/Q1661989)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Industry_4.0)  
**Source**: https://4ort.xyz/entity/industry-4-0

## Summary
Industry 4.0 is the fourth industrial revolution, defined as the current trend of automation and data exchange in manufacturing technologies. It represents a historical period and an academic discipline focused on the integration of physical and digital systems to optimize production.

## Key Facts
- **Also known as:** 4th Industrial Revolution, 4IR.
- **Classification:** Defined as a historical period, an academic discipline, and a field of study limited to a specific area of knowledge.
- **Timeline:** The start time is identified as the year 2000.
- **Predecessor:** Follows the Third Industrial Revolution, a phase of digitalization that began in the latter half of the 20th century.
- **Core Technologies:** Comprises the Internet of things, cyber-physical systems, internetworking, artificial intelligence, decentralization, big data, smart manufacturing, vertical integration, and horizontal integration.
- **Relationship with Smart Manufacturing:** Industry 4.0 lists smart manufacturing as both a subsidiary component and a parent entity.
- **Identifiers:** Associated with various structured data IDs including Wikidata ID Q11514315, Freebase ID /m/0w33bsj, and Library of Congress LCCN ph950056.
- **Sitelink Count:** Has 23 sitelinks across various knowledge bases.

## FAQs
**What is Industry 4.0?**
Industry 4.0 is the 4th Industrial Revolution, representing the current trend of automation and data exchange in manufacturing technologies. It is categorized as both a historical period and an academic discipline.

**What technologies are included in Industry 4.0?**
Key components include the Internet of things, cyber-physical systems, internetworking, artificial intelligence, decentralization, big data, smart manufacturing, vertical integration, and horizontal integration.

**How does Industry 4.0 relate to previous industrial revolutions?**
It is preceded by the Third Industrial Revolution, which was characterized by a phase of digitalization starting in the latter half of the 20th century.

**Is Industry 4.0 considered an academic field?**
Yes, it is classified as an academic discipline, a field of study, and a profession, as well as a specific segment of time in history.

**What is the connection between Industry 4.0 and Smart Manufacturing?**
The relationship is bidirectional; Industry 4.0 contains smart manufacturing as a subsidiary component, yet Industry 4.0 is also listed as a part of the smart manufacturing paradigm.

## Why It Matters
Industry 4.0 matters because it marks the transition to fully automated, interconnected manufacturing environments where physical machinery is integrated with digital computation. By leveraging technologies like the Internet of things and artificial intelligence, it enables the creation of "smart factories" that can analyze data to optimize performance in real-time. This shift addresses the need for increased efficiency, customization, and speed in production, fundamentally changing global supply chains through vertical and horizontal integration.

## Notable For
- **Integration of Artificial Intelligence:** Incorporates AI, a transformative field enabling machines to perform tasks requiring human cognition, such as visual perception and decision-making.
- **Cyber-Physical Systems:** Distinguished by the use of engineered systems that seamlessly integrate physical components with computation.
- **Big Data Utilization:** Relies on information assets characterized by high volume, velocity, and variety that require specific analytical methods.
- **Decentralization:** Notable for the process of redistributing functions and powers away from a central location or authority.
- **Internetworking:** Utilizes the concept of interconnecting different types of computer networks to facilitate communication.

## Body

### Definition and Classification
Industry 4.0, also referred to as the 4th Industrial Revolution or 4IR, is the current trend of automation and data exchange in manufacturing technologies. It is formally classified as a historical period, an academic discipline, and a field of study. As an academic discipline, it serves as a profession and a branch of learning limited to a specific area of knowledge. The structured properties associated with Industry 4.0 indicate a start time of January 1, 2000.

### Historical Context
This industrial revolution follows the Third Industrial Revolution, which was defined as a phase of digitalization beginning in the latter half of the 20th century. The transition to Industry 4.0 represents an evolution from simple digitalization to deep integration and automation.

### Core Technologies and Components
Industry 4.0 is composed of several critical technologies and concepts that function as its subsidiaries or parts:

*   **Internet of Things (IoT):** An Internet-like structure connecting everyday physical objects.
*   **Cyber-Physical Systems:** Engineered systems built and operated with the seamless integration between physical components and computation.
*   **Internetworking:** The concept of interconnecting different types of computer networks.
*   **Decentralization:** The process of redistributing or dispersing functions, powers, people, or things away from a central location or authority.
*   **Big Data:** Information assets characterized by such a high volume, velocity, and variety that they require specific technology and analytical methods for transformation into value.
*   **Vertical Integration:** A business arrangement in which the supply chain of a company is owned by that company.
*   **Horizontal Integration:** Increasing production at the same level of the supply chain through acquisition, merger, or internal expansion.

### Artificial Intelligence in Industry 4.0
A central component of Industry 4.0 is Artificial Intelligence (AI), a field of computer science that develops and studies software enabling machines to exhibit intelligent behavior. AI is considered a transformative field focused on creating intelligent systems capable of performing tasks typically requiring human cognition.

**Overview of AI**
Artificial Intelligence involves the development and study of computer systems capable of performing tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. The field encompasses techniques ranging from rule-based expert systems to advanced machine learning models that learn and adapt from data.

**History and Background of AI**
The modern field of AI emerged in the 1950s, with early pioneers like Alan Turing laying the theoretical groundwork. The term "artificial intelligence" was coined in 1956 at the Dartmouth Conference. The field has experienced cycles of optimism and disappointment ("AI winters") before seeing rapid progress in the 21st century due to breakthroughs in machine learning and deep learning.

**Key AI Concepts**
*   **Machine Learning (ML):** A subset of AI enabling systems to learn from data and improve performance without explicit programming.
*   **Deep Learning:** A specialized form of ML using neural networks with many layers to analyze complex data like images and sound.
*   **Natural Language Processing (NLP):** The branch of AI focused on enabling machines to understand, interpret, and generate human language.
*   **Computer Vision:** AI systems that interpret and analyze visual information.
*   **Expert Systems:** Early AI programs designed to mimic the decision-making ability of human experts.
*   **Reinforcement Learning:** A type of ML where agents learn by interacting with an environment and receiving feedback.

**Applications of AI**
AI is utilized across various sectors including:
*   **Healthcare:** Diagnostics, drug discovery, and personalized treatment.
*   **Finance:** Fraud detection, algorithmic trading, and credit scoring.
*   **Retail:** Recommendation engines and inventory management.
*   **Manufacturing:** Predictive maintenance and quality control.
*   **Transportation:** Autonomous vehicles and route optimization.
*   **Entertainment:** Content curation and personalization.
*   **Education:** Adaptive learning platforms.
*   **Marketing:** Audience segmentation and campaign optimization.

**Market Trends and Challenges**
The adoption of AI is accelerating due to advances in computing power and data availability. Trends include the democratization of AI tools through cloud services and open-source frameworks. However, AI faces challenges regarding data privacy, bias and fairness, transparency ("black box" models), job displacement, and the need for regulation and governance.

### Smart Manufacturing and Integration
Industry 4.0 has a complex relationship with smart manufacturing. Smart manufacturing is defined as a paradigm where a technology-driven approach utilizes Internet-connected machinery to monitor the production process, aiming to identify opportunities for automation and use data analytics to improve performance. In the context of Industry 4.0, smart manufacturing is listed both as a parent entity (Industry 4.0 is part of it) and as a subsidiary (it is contained within Industry 4.0). This highlights the symbiotic nature of the concepts, where the broader revolution (Industry 4.0) is realized through specific paradigms (smart manufacturing).

## References

1. Quora
2. [OpenAlex](https://docs.openalex.org/download-snapshot/snapshot-data-format)