Secrets and techniques of the fourth generation of industries

Blog / Digital
We are in the midst of a major transformation in the way we make products thanks to digital transformation, this transformation has become so influential that it is called the fourth generation of industries, or Industry 4.0 to represent the fourth industrial revolution, although some reject the term Industry 4.0 as just A pretentious term for marketing, the massive digital transformations that occur in manufacturing under this term deserve our attention, and therefore we will present in this article 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 emergence of mechanization, steam power, and hydropower, and this was followed by the second industrial revolution that revolved around production lines and massive assembly using electricity, and then the third industrial revolution came with electronics, systems, and automation, which led to the fourth industrial revolution related to cyber-physical systems.
What are the technologies of the fourth generation of industries?
There are many fourth-generation technologies "Industry 4.0", 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 devices to communicate with other web-enabled devices. This automation and connectivity enable large amounts of valuable data to be collected, analyzed, and shared.
Cloud Computing
Cloud computing is known as the cornerstone of any strategy related to the fourth generation of industries, and the full realization of intelligent manufacturing requires the connectivity 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 identify 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 generated not just in the organization or factory, but across their business units, and even from partners and third-party sources.
Artificial intelligence and machine learning can provide insight, forecast, and automation of business processes, for example: industrial machines are prone to breakdown during the production process, and using data collected from these companies can help perform predictive maintenance based on machine learning algorithms, resulting in Increased uptime and increased efficiency.
edge computing
Edge computing shifts resources from central data centers and clouds to devices, and this reduces latency from the time of data production to the required response time, for example: Detecting a safety or quality issue may require the immediate return of the device, and the use of edge computing also means That data stays close to its source, reducing security risks.
cyber security
Manufacturers have not previously considered 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 pathways for attacks and malware. Its approach to cybersecurity includes IT 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. The digital twin is created by pulling data from IoT sensors, devices, PLCs, and other objects connected to the Internet.
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.
Analyze data for optimal decision making
Embedded sensors and interconnected machines produce a wealth of big data for manufacturers. Data analysis 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 extensive 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 and employee margins, and a full digital representation of operations can be created as a “digital twin.”
IT Integration
The architecture of the Intelligent Factory Network is interconnected, making it easy to instantly consume and use real-time data collected from sensors, devices, and machines in the factory, as well as share it across other components in the enterprise software package, including enterprise resource planning and business management. other.
Customized manufacturing
Smart factories can more cost-effectively produce customized goods that meet customers’ needs. Indeed, manufacturers in many industry sectors aspire to achieve “single lot size” economically, through the use of advanced simulation software applications and new materials and technologies such as 3D printing. While the first industrial revolution was all about mass production, fourth-generation industries are all about mass customization.
Industrial operations rely on a transparent supply chain

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