Today's manufacturing industry has become more and more intelligent. Factories have begun to use sensors, wireless networks and other technologies to capture various data in the production process of products and realize intelligent manufacturing through data application.
Intelligent manufacturing can make production more efficient and achieve sustainable profits.
Risks can be identified through simulation through calculation, such as expected delivery delay, etc. New generation information technology--
Technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence are bringing profound changes to traditional industries. In this round of development, there are huge opportunities and challenges, how can enterprises break through this opportunity?
The new technology has brought infinite reverie, but if it is not used properly, it will cause loss.
Therefore, only by clearly understanding the mystery behind the new technology can we grasp the real opportunity.
Changes in market demand often surprise people. Modern manufacturing should make good use of the new generation of information technology and increase its ability to respond quickly to the market.
This market-oriented economic model solves the problem of unstable orders.
Only by improving the efficiency and flexibility of production, can we produce any product anytime and anywhere, this is the vision of intelligent manufacturing.
Intelligent manufacturing is a big project. To promote the transformation and upgrading of new technologies in factories and transform technologies into production capacity, all parties need to work together.
Academia promotes the forefront of science and technology, from artificial intelligence to deep learning, but does not consider how to apply it.
However, manufacturers want to know what type of data should be collected and how to use these data to produce effects.
Because of this, the combination of academic and manufacturing can truly apply knowledge to reality.
Intelligent manufacturing is a mode of improving the level of production process through some advanced technologies, thus realizing a higher overall value chain.
In the intelligent manufacturing process, each piece or product has the following digital information, collecting more data for inspecting the production process, tracking the supply chain, assembly and testing process, the final delivery to users is a product or service bundled with physical and digital.
With the deterioration of the aging scene, the manufacturing industry is promoting cheap labor, and the replacement of machines is imperative.
Therefore, one of the purposes of intelligent manufacturing is to save manpower and solve the expensive labor cost and labor shortage problems.
At the same time, the new production mode can ensure that manufacturers can shorten the delivery time and reduce commercial risks, thus creating more economic benefits.
The ultimate goal of intelligent manufacturing is to improve production efficiency and reduce costs, thus enabling enterprises to obtain more value returns.
However, it is far from enough to blindly invest automation equipment. Enterprise managers also need to know how to operate your factory. Otherwise, it may lead to more cost waste.
What should enterprises do at this stage to make factories play more benefits?
Intelligent manufacturing design needs to abide by certain principles so as not to waste time and manpower in the digital process.
Converting the production process into the number of information is the primary task to realize intelligence. This part should be automatically collected by internet of things programs as much as possible to reduce manual data entry, because the efficiency of manual operation is too low, there may also be problems such as errors.
Establish distributed nodes for machines, factories and enterprise-level autonomous diagnosis and decision-making. Information is planned according to the requirements of each machine equipment, Factory Floor and product unit.
Allows widespread use of data information across the entire product value chain, including visibility of each product value chain, manufacturer-to-customer connectivity, and supplier networks.
Automatic execution of daily tasks and decisions, but the process includes manual processing, manual adjustment and complex analysis to assist decisions.
The optimization of the implementation plan uses all the data obtained from the production process to gain insight through advanced analysis and machine learning algorithms and rationally adjust the production plan. Using machine-to-machine (M2M), Application to application (A2A), Business-to-business (B2B)
Integration standards, an Internet integration platform that integrates hardware and software from multiple factories, learn to establish and promote data exchange standards between assets, production processes and supply chains.
Establish a learning and training mechanism to enable automation personnel to understand new skills and knowledge.
The introduction of new technologies requires more high-end talents. Enterprises must help workers learn how to configure and maintain intelligent machines.
In the next few years, intelligent manufacturing will develop to a new level in connectivity, and the resulting comprehensive value chain process will bring revolutionary productivity growth, which is exciting for manufacturing, make traditional equipment more efficient. NJPE-
The leading domestic mold processing factory has advanced equipment capability, innovative research and development strength, strong financial strength and strong production capacity.
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