Secrets and techniques of the fourth generation of industries

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Secrets and techniques of the fourth generation of industries
Secrets and techniques of the fourth generation of industries
We are in the midst of a major shift in the way we make products thanks to digital transformation. This transformation has become so influential that it is called Industry 4.0 to represent the fourth industrial revolution, although some dismiss the term Industry 4.0 as mere. A pretentious term for marketing, but the massive digital transformations that occur in manufacturing under this term deserve our attention, and therefore, in this article, we will present the concept of the fourth generation of industries, and its importance in the industry.
What is the Fourth Industrial Revolution?
The first industrial revolution came with the advent of mechanization, steam power, and water power. This was followed by the second industrial revolution that revolved around production lines and mass assembly using electricity. Then came the third industrial revolution with electronics, systems, and automation, which led to the fourth industrial revolution associated with cyber-physical systems.
What are the technologies of the fourth generation of industries?
There are many technologies of the fourth generation of “Industry 4.0” industries, which are:
Internet of Things (IoT)
The Internet of Things (IoT) is a key component of smart factories. Machines in those organizations are equipped with “IP” sensors that allow the devices to communicate with other web-enabled devices. This automation and connectivity enables large amounts of valuable data to be collected, analyzed and exchanged.
Cloud Computing
Cloud computing is known as the cornerstone of any strategy related to the fourth generation of industries. The full realization of smart manufacturing requires the connection and integration of engineering, supply chain, production, sales, distribution and service, and cloud computing helps make this possible.
In addition, the large amount of data that is stored and analyzed can be processed more efficiently and effectively, and cloud computing can also reduce start-up costs for small and medium-sized manufacturers who can scale and scale their needs as their business grows.
Artificial intelligence and machine learning
Artificial intelligence and machine learning allow companies to take full advantage of the volume of information that is generated not just in the organization or plant, but across their business units, and even from partners and third-party sources.
Artificial intelligence and machine learning can provide insight, forecasting, and automation of business processes, for example: industrial machines are prone to breakdown during the production process, and the use of data collected from these companies can help perform predictive maintenance based on machine learning algorithms, leading to Increase uptime and increase efficiency.
Edge computing
Edge computing shifts resources from centralized data centers and clouds to devices, this reduces response time from when data is produced to required response time, for example: detecting a safety or quality issue may require immediate device return, edge computing also means using edge computing That data stays close to its source, which reduces security risks.
Electronic security
Previously, manufacturing companies did not consider the importance of cybersecurity or cyber-physical systems, but connecting to operational equipment in a factory or field that enables more efficient manufacturing processes also reveals new entry paths for attacks and malware. When making a digital transformation to Industry 4.0, it is essential that you consider In an approach to cyber security that includes information technology equipment and operational technology.
digital twin
The digital transformation provided by the fourth generation of industries has allowed manufacturers to create digital twins that are virtual replicas of processes, production lines, factories, and supply chains. Digital twins are created by pulling data from IoT sensors, devices, PLCs, and other Internet-connected objects.
Manufacturers can use digital twins to help increase productivity, improve workflow, and design new products, by simulating the production process, for example: Manufacturers can test changes to the process to find ways to reduce downtime or improve capacity.
Data analysis to make the best decision
Embedded sensors and interconnected machines generate a large amount of big data for manufacturing companies, analyzing the data can help manufacturers explore historical trends, identify patterns and make better decisions.
Smart factories can also use data from other sectors of the organization and its extended system of suppliers and distributors. To create deeper insights, by looking at data from human resources, sales, or warehousing, manufacturers can make production decisions based on sales margins and employees, and an entire digital representation of operations can be created as a "digital twin."
IT integration
The smart factory network architecture is based on interconnection, whereby real-time data collected from sensors, devices, and machines in the factory can be easily consumed and used immediately, as well as shared across other components in the enterprise software stack, including enterprise resource planning and business management. other.
Smart factories can produce customized goods that meet customer needs more cost-effectively. In fact, manufacturers in many industry sectors aspire to achieve “one lot size” in an economical way, through the use of advanced simulation software applications, new materials and technologies such as 3D printing. Manufacturers can easily create small batches of specialized items for specific customers. While the first industrial revolution was about mass production, the fourth generation of industries is about mass customization.
Industrial processes are based on the Toe Series

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