Digital intelligent transformation is a difficult, long-term and systematic project, if the traditional manufacturing enterprises want to achieve "number" to speed up, to "intelligence" to improve the quality, they need to be guided by intelligent technology.
For example, Sany Heavy Industry's No. 18 plant in Changsha. In order to cope with the cyclical fluctuations of the heavy industry market, the challenges of multi-variety and small-batch (263 categories) and heavy parts production, SANY Changsha No. 18 Factory has established a digital flexible heavy equipment manufacturing system by making full use of flexible automated production, artificial intelligence and large-scale IIoT. The result was a 123% increase in plant capacity, a 98% increase in productivity, and a 29% reduction in unit manufacturing costs.
In order to realize the intellectualization and digitalization of semiconductor display factories, Wuhan TCL has scientifically applied cutting-edge technologies such as 5G, industrial Internet, big data, and artificial intelligence to realize the interconnection of software and equipment, and the mutual awareness of equipment and environment.
It can be found that behind the intelligent transformation and upgrading of these manufacturing enterprises is the organic integration of the points and surfaces of the robot industry chain.
As an important part of the manufacturing industry, industrial robots play an important role in the transformation of enterprise data intelligence. After years of development, industrial robots have gradually changed from traditional "robotic arms" to intelligent robots with autonomous perception, learning and decision-making capabilities, which can quickly adjust the working mode through learning and optimization, perform complex tasks on the production line, and improve production efficiency and product quality.
Machine vision technology has been widely used in the manufacturing industry, which can help enterprises improve production efficiency and quality control in many links. For example, in the detection of coating parts on automotive production lines, machine vision can quickly detect defects such as color, gloss and surface smoothness. At the same time, machine vision can also provide accurate target guidance and position judgment for the operation of the robot, and improve the operation efficiency and accuracy of the robot.
In addition, with the rise of emerging technologies such as artificial intelligence (AI), cloud computing, big data and 5G, it is important for manufacturing enterprises to effectively use these Internet emerging technologies to open up the whole value chain of product research and development, sales, supply chain, manufacturing, logistics and customer service, and help enterprises achieve an agile, efficient and low-cost operation model. It is the driving force of domestic demand for enterprises to develop digital intelligence.
Manufacturing to new, manufacturing upward is an important driving force for China's transition. How to accelerate the application and promotion of digital technology in the manufacturing industry, drive the "revolution" with the "innovation", and promote the transformation of the development model of the manufacturing industry to intelligence is a required course for the development of manufacturing enterprises.
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