There is an unprecedented change in the manufacturing industry. The manufacturing industry positions we have seen in decades will disappear, and technologies such as robotics, cloud computing and AI will become key players in the future manufacturing industry. These technologies will help more and more. Many companies improve their efficiency, produce higher quality products quickly, and do not rely on cheap labor. This kind of scenario is what we call smart manufacturing, and it is also the direction of upgrading of manufacturing companies around the world, which will make our products cheaper and cheaper.
So, what exactly is smart manufacturing? It combines information technology with industrial technology, monitors and manages products from the design, manufacture, sales, and transportation methods, and opens up all links in the manufacturing industry chain, changing the past information asymmetry. The problem is that the entire manufacturing process runs at peak efficiency.
After the industrial equipment is connected to the Internet, the manufacturer will get rich on-site data, but this is only the beginning. The key is how to use this data. This is a process of accumulating and understanding large data sets. Smart manufacturing is actually using big data analytics to improve complex processes and manage the supply chain. Then, the field data is varied, and manufacturers need to define these different types of data before they can perform comparative analysis, which ultimately helps to improve product line efficiency and performance.
In fact, the big data concept has existed for many years, and many manufacturers have realized that all the data that masters their business can be analyzed and gained important value. The new advantage of big data analytics is that it captures opportunities more quickly and accurately, by pooling data and analysing, potentially discovering useful information that can be used for future decisions, or finding insights for immediate decision making. This faster ability to work gives manufacturers a competitive advantage that they couldn't match in the past.
So, what kind of data analysis is good for manufacturers? The first is regular data analysis, which reveals the actions that should be taken, and the results of the analysis provide recommendations for the next steps. The second is predictive data analysis, which will show what might happen. The third is diagnostic data analysis, looking at past performance to reveal what happened and why. The last one is a descriptive analysis that is used to display on the real-time dashboard. With the collection and accumulation of data, manufacturers will be able to accurately assess and predict production, making the plant system more suitable for current business needs and maximizing benefits.
Robots have entered large quantities in the fields of automobiles, 3C electronics, etc., and continue to expand in the direction of medicine, security, and agriculture. At present, robots are still in a simple automation stage. However, with the development of artificial intelligence and the Internet of Things, the robot industry will soon enter the 2.0 era. At that time, the robot will have the same decision-making and logic analysis capabilities and can be used in more scenarios.
Robots of the 2.0 era are advanced robots, also known as smart machines, which are an important part of intelligent manufacturing. These robots can operate autonomously and communicate directly with the manufacturing system to evaluate physical inputs and differentiate between different product configurations. Intelligent machines can solve problems and make decisions without the help of others. They can not only realize the tasks that were originally prepared, but also have artificial intelligence, which can learn from experience and master new skills.
Intelligent robots have the flexibility to configure themselves and perform new tasks, and they can respond quickly to demand changes and product innovations, which is more advantageous than traditional manufacturing processes. With the improvement of robot cognitive ability, robots can work together beside people, becoming an indispensable tool for humans to work efficiently in the future.
After the combination of manufacturing and the Internet, information interaction will become more frequent, and there will be a large amount of data exchange between machines and machines. Manufacturers use the Internet to increase data storage, and by using cloud software, they can access highly configurable computing resources, enabling rapid creation of servers, networks, and other storage applications.
The connection between the manufacturing equipment and the network is achieved through an open communication protocol, including from the tablet to the automation equipment and sensors, and the command information entered by the external equipment can change the production process. In the connected world, the physical world becomes a physical object and information system embedded with sensors and actuators that are interconnected by wired or wireless Internet protocols.
In the manufacturing sector, this stage of industrialization is called Industry 4.0 and involves the integration of physical system (CPS) technology into manufacturing, logistics, and the use of the Internet of Things in industrial processes. Not only can CPS be networked to each other, but they can also create objects throughout the value chain and throughout the product lifecycle, such as ICT systems, smart products, and personal smart networks. Sensors and the Internet of Things enable machines to connect to factories, networks and workers.
Some people believe that smart manufacturing will fundamentally change their current business. Through advanced technology, intelligent manufacturing allows for the existence of multiple small production bases that are closer to the customer, reducing the time from the factory to the consumer and putting the recently developed products into the customer within a few hours. Despite some changes, smart manufacturing actually converts through the manufacturer's existing capabilities.
Future manufacturing will use new software, manufacturers can create and test situations in the virtual world, and determine the design process and production line before generating the actual product. For example, 3D printing offers manufacturers a variety of possibilities for part design, allowing seamless creation of tangible products using a single machine. In the manufacturing process, 3D printing can do the same thing without the need for additional programs.
With the support of IoT technology, manufacturers can get the right information at the right time, obtain and analyze the information that affects production through the software services provided by cloud computing, and make the right decisions. Big data analytics will have a major impact on research and development, providing customers with more demand and faster product services while reducing costs.
Smart factories will eliminate some of the old ways of working, using ERP, MES and IoT systems for paperless operations, and automation from creative design to manufacturing. Predictive and normative analysis capabilities facilitate the detection of awareness and increase productivity in the production floor. At the same time, the use of cloud computing eliminates IT overhead, eliminating the need to invest in expensive infrastructure and enabling manufacturers to access data from anywhere in the world.
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