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Under the tide of intelligent manufacturing, how can enterprises determine their future
Publisher:z85329	Add time：2019/10/17	viewed：2102
Today's manufacturing industry has become increasingly intelligent, and factories have begun to use sensors, wireless networks and other technologies to capture various data in the production process and realize intelligent manufacturing through the use of data. Intelligent manufacturing can make production more efficient and realize sustainable profitability. Risks, such as expected delivery delays, can be identified by computationally simulated. The new generation of information technology, such as the Internet of things, big data, cloud computing, artificial intelligence and other technologies are bringing profound changes to traditional industries. In this round of development wave, there are huge opportunities and challenges. How can enterprises break through this opportunity? The new technology brings endless imagination, but it can also be a losing game if not used properly. Therefore, only a clear understanding of the mystery behind the new technology is possible to grasp the real opportunity. Modern manufacturing needs to take advantage of the new generation of information technology and be more responsive 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, which is the vision of intelligent manufacturing. Smart manufacturing is a big project. In order to promote the transformation and upgrading of factories with new technologies and transform technologies into production capacity, joint efforts of all parties are needed. Academia pushes the frontiers of technology, from artificial intelligence to deep learning, but doesn't think about how it will be applied. Manufacturers want to know what kind of data to collect and how to use it to make a difference. For this reason, the combination of academia and manufacturing can really apply knowledge to reality. Intelligent manufacturing is a mode to improve the level of production process through some advanced technologies so as to realize a higher overall value chain. In the intelligent manufacturing process, each part or product has digital information to follow, collecting more data for inspection of the production process, tracking the supply chain, assembly and testing process, and finally handing over to the user is a product or service that combines physical and digital. As the ageing scene deteriorates and manufacturing pushes for cheap Labour, replacement of machines is inevitable. Therefore, one of the goals of intelligent manufacturing is to save manpower and solve the problem of high labor costs and labor shortage. At the same time, the new production model can ensure that manufacturers shorten the delivery time, reduce business risks, and thus create more economic benefits. The ultimate goal of intelligent manufacturing is to improve production efficiency and reduce costs, so that enterprises can get more value return. But if only blindly invest in automation equipment, it is far from enough, enterprise managers also need to know how to operate your factory, otherwise, it may lead to more large cost waste. How should the enterprise do at present to let the factory play more benefits? Intelligent manufacturing design needs to follow certain principles so as not to waste time and manpower in the process of digitization. It is the primary task to realize intelligence to convert the production process into information. In this part, it is necessary to adopt the Internet of things program to collect data automatically as far as possible to reduce the manual input of data, because the efficiency of manual operation is too low and errors may occur. Establish distributed nodes for machine, plant, and enterprise level autonomous diagnostics and decisions, with information planned according to the needs of each machine, plant, and product unit. Allows universal use of the entire product value chain data information, including visibility into each product value chain, manufacturer to customer connections, and supplier networks. Automatic execution of daily tasks and decisions, but the process includes manual processing, manual adjustments, and complex analytical decision assistance. Optimize the plan, use all the data obtained from the production process, gain insight through advanced analysis and machine learning algorithm, and adjust the production plan reasonably. Adopt machine-to-machine (M2M), application-to-application (A2A), business-to-business (B2B) integration standards, integrate multiple high hardware and software Internet integration platforms, and 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 talent, and companies must help workers learn how to configure and maintain smart machines. Over the next few years, smart manufacturing will evolve to new levels of connectivity, and the resulting integrated value chain process will lead to revolutionary productivity growth that is exciting for manufacturing, enabling traditional devices to achieve greater efficiency.

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