The term “Industry 4.0” which was first announced from the German government as one of the key initiatives and highlights a new industrial revolution. Industry 4.0 represents the fourth industrial revolution that has occurred in manufacturing industries. Industry 4.0 optimizes the computerization of Industry 3.0 where machines are digitally connected with one another and create and share information and communicate with one another to ultimately make decisions without human involvement.
In this Article You will learn:
- 1 What is Industry 4.0?
- 2 Eight Supportive technologies for Industry 4.o
- 2.1 Adaptive Robotics
- 2.2 Data Analytics & Artificial Intelligence
- 2.3 Simulation
- 2.4 Embedded systems (Cyber-physical infrastructure):
- 2.5 Industrial Internet of things (Communication and Networking)
- 2.6 Cloud Systems
- 2.7 Additive Manufacturing
- 2.8 Virtualization Technologies
- 2.9 Infrastructure for supportive technologies of Industry 4.0
- 3 Conclusion
What is Industry 4.0?
The term Industry 4.0 defined as “A combination of communication and networking (Industrial Internet), embedded systems (Cyber-Physical Systems), adaptive robotics, cybersecurity, data analytics, and artificial intelligence, and additive manufacturing make the smart factory. With the support of smart machines that get access to more data, factories become more efficient, productive and less wasteful.”
Industry 4.0 focuses on the establishment of intelligent and communicative systems including machine-to-machine communication and human-machine interaction. Industry 4.0 is comprised of the integration of production facilities, supply chains, and service systems to enable the establishment of value-added networks. Thus, emerging technologies such as big data analytics, autonomous (adaptive) robots, cyber-physical infrastructure, simulation, horizontal and vertical integration, Industrial Internet, cloud systems, additive manufacturing and augmented reality are necessary for a successful adaptation.
Industry 4.0 completely encounters a wide range of concepts including increments in mechanization and automation, digitalization, networking, and miniaturization. Moreover, Industry 4.0 relies on the integration of dynamic value-creation networks with regard to the integration of the physical basic system and the software system with other branches and economic sectors, and also, with other industries and industry types.
According to the concept of Industry 4.0, research and innovation, reference architecture, standardization and security of networked systems are the fundamentals for implementing Industry 4.0 infrastructure. These transformations can be possible by providing adequate substructures supported by sensors, machines, workplaces, and information technology systems that are communicating with each other first in a single enterprise and certainly with other communicative systems. These types of systems referred to as cyber-physical systems and coordination between these systems are provided by Internet-based protocols and standards.
Eight Supportive technologies for Industry 4.o
Since Industry 4.0 focuses on the establishment of intelligent and communication systems such as machine-to-machine communication and human-machine interaction, the industries have to deal with the establishment of effective data flow management that relies on the acquisition and assessment of data extracted from the interaction between intelligent and distributed systems. The main idea of data acquisition and processing is the installation of self-control systems that enable taking the precautions before system operation suffered.
The transformation to Industry 4.0 is based on eight foundational technologies as follows:
Adaptive Robotics may be distinguished from static automation due to its capacity to adapt to changing environmental conditions and material features while retaining a degree of predictability required for collaboration. Unlike static or factory robots, which have a pre-defined program, adaptable robots can function even if a component breaks, making them useful in cases like caring for the elderly, doing household tasks, and rescue work.
Adaptive and flexible robots with artificial intelligence provide easier manufacturing of different products by recognizing the lower segments of each part. This segmentation proposes to provide decreasing production costs, reducing production time and waiting time in operations. Additionally, adaptive robots are useful in manufacturing systems, especially in design, manufacturing and assembly phases.
Example: A robot called Yumi which is created for ABB manufacturing operations. Yumi has flexible handling, parts feeding mechanism, camera-based part location detection system and state-of-the-art motion control for the adaptation of ABB production processes.
Data Analytics & Artificial Intelligence
Data analytics & Artificial Intelligence is the science of analyzing raw data in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into manufacturing processes and algorithms that work over raw data for human consumption. Data analytics and artificial intelligence use data science and advanced computing algorithms to automate and optimize.
Since a very huge amount of real-time accumulates from multiple sources such as R&D, production, operations and maintenance processes. This real-time data increases at exponential speed. This real-time data appears in large volume and need to be processed quickly in a very effective way to increase productivity.
Simulation modeling solves real-world problems safely and efficiently by 3D motion simulation software. The simulation is the process of mathematical modeling which is designed to predict the behavior of the outcome of a real-world or physical system. simulation can be performed in various cases to improve the product or process planning.
Simulation-based CAD integration ensures the working of multiple systems by changing critical parameters. Additionally, simulation can reflect what-if scenarios to improve the robustness of processes. Especially for smart factories, virtual simulation enables the evaluation of autonomous planning rules.
Embedded systems (Cyber-physical infrastructure):
Embedded systems generally integrate physical reality with respect to innovative functionalities including computing and communication infrastructure. Embedded systems, named Cyber-Physical Systems (CPS), can be explained as supportive technology for the organization and coordination of networking systems between its computational capabilities and physical infrastructure.
An embedded system obtains two main functional requirements:
- The advanced level of networking to provide both real-time data processing from the physical infrastructure and information feedback from the digital structure.
- Intelligent data processing, decision-making and computational capability that support the physical infrastructure.
Industrial Internet of things (Communication and Networking)
The Internet of Things, or IoT, refers to physical devices that are now connected to the internet, all collecting and sharing data. The machines can interact with embedding intelligent sensors in real-world environments and processes to achieve given targets using communication devices and tools. The aim of IIoT is to provide computers and machines to see and sense the real-world applications that can provide connectivity from any time, anywhere for
anyone for anything.
Requirements for communication and networking are as follows:
- Distributed and parallel computing for data processing
- Internet Protocol
- Communication technology
- Embedded devices including Radio frequency identification(RFID) or Wireless Sensor Networks (WSN)
- Communication application
Cloud Sytems means storing and accessing data and programs over the Internet instead of the computer’s hard drive so that every person or system can use that data whenever it required. The cloud is just a metaphor for the Internet.
Additive manufacturing, also known as 3D printing, is a transformative approach to industrial production that enables the creation of lighter, stronger parts and systems. The terms “3D printing” and “rapid prototyping” are generally used for additive manufacturing, each process is actually a subset of additive manufacturing. Additive manufacturing is a set of emerging technologies that produce 3D objects directly from digital models that grow three-dimensional objects one superfine layer at a time. Each successive layer bonds to the preceding layer of melted or partially melted polymers, ceramics, or metals.
Virtualization technologies are based on Augmented Reality (AR) and Virtual Reality (VR) tools that are entitled to the integration of computer-supported reflection of a real-world environment with additional and valuable information. In simple words, virtual information can be encompassed to real-world presentation considering human’s perception of reality with augmented objects.
Today, visualization technologies are mainly applied in diversified fields such as video gaming, tourism. Now Virtual technologies have started to be considered within the context of constructing quality management systems, assembly line planning and organizing logistics and supply chain actions for smart factories.
Infrastructure for supportive technologies of Industry 4.0
Supportive technologies can be implemented by infrastructures such as cybersecurity, sensors and actuators, RFID (Radio Frequency Identification) and RTLS ( Real-Time Location Sensors) technologies and mobile technologies.
Industry 4.0 requires strategic workforce planning, constructing the right organization structure developing partnerships and participating and sharing the technological standardization, which are essential factors to drive technological advancements. Although Everything is not perfect yet, Major implementation areas in manufacturing are real-time supply chain optimization, human-robot collaboration, smart energy consumption, digital performance management, waste management, industrial maintenance, and Safety.
With the adaptation of industry 4.0, Self-organized, self-motivated and self-learning systems will be developed by using more sophisticated artificial intelligence algorithms that will be encountered in the near future.