2018 China Intelligent Manufacturing Report

Introduction of Intelligent Manufacturing is supported by a system of things smart, smart manufacturing and smart service. It has become a global value chain restructuring and the international division of labor adjustment is important to select the next national background. Some countries have increased manufacturing reflux efforts to enhance the strategic position of the manufacturing sector in the national economy. Asia as an important regional manufacturing is also actively deploying automation and intelligence. With the rapid development of artificial intelligence, intelligence has become an important direction of industrial development. Intelligent manufacturing development and achieved remarkable results Control Engineering Copyright , to enter the high-speed growth. China Intelligent Manufacturing into the growth stage, mainly in three aspects: First, China’s industrial enterprises to enhance the quality of digital capabilities, laying the foundation for future analysis and forecasting and adaptive manufacturing systems. Second, the effectiveness of financial, intelligent manufacturing enterprise profit contribution rate has improved significantly. Third, typical applications, China has become the first industrial robot consumer, the strong growth in demand. Chinese industrial enterprises in the deployment of intelligent manufacturing five major focus , as follows: Digital Factory (63%), and user equipment worth digging (62%), industrial things (48%), weight business model configuration (36%) and AI (21%). (See Figure 1)
Figure 1: The deployment of intelligent manufacturing companies surveyed areas of focus
Digital Factory is a top priority. Intelligent Manufacturing manufacturing sector is at the core of intelligence to-end data stream based, digital as the core driving force, so the digital factory is intelligent manufacturing enterprises as the primary task of deployment. At present, enterprises deploy digital factory to open up the flow of production data to perform the main task, and the product stream and supply chain data stream large room for improvement. The depth of excavation equipment and customer value. Manufacturing enterprises are facing increasingly fierce market competition and increasingly transparent product pricing Control Engineering Copyright , have to find new sources of value. Deloitte intelligent manufacturing survey results show that users value the depth of excavation equipment and intelligent manufacturing enterprise deployment of the second area of ​​focus. 62% of respondents are actively deployed and the user equipment excavation depth value , 41% of the value of mining equipment business focus, 21% of corporate users focus value mining. Chinese manufacturers are not enthusiastic about cloud deployment. 53% of manufacturing companies surveyed have not yet deployed the cloud industry, 47% of industrial enterprise cloud deployments under way, 27% of companies deploy a private cloud, public cloud deployment by 14%, 6% hybrid cloud deployment. (See Figure 2)
Figure 2: Respondents industrial manufacturing enterprise cloud deployments
Reconstruction of future business models. Intelligent Manufacturing not only help manufacturing companies to achieve cost efficiency, but also gives a rethink of the value proposition and business model reconstruction opportunities. Deloitte survey results show that 30% of respondents to the company’s future business model as the core platform, 26% of companies take large-scale customization, 24% of “product + service” as the core of the transition to solution providers, 12% to intellectual property rights as the core. (See Figure 3)
Figure 3: Respondents positioning the company’s future business model
AI impact on the manufacturing sector, mainly from two aspects: one is the use of artificial intelligence to improve the quality and efficiency in manufacturing and management processes; second, It is a complete subversion of existing products and services. Intelligent Manufacturing Deloitte survey found that 51 percent of the companies surveyed use of artificial intelligence in manufacturing and management processes, 46% of the companies surveyed in the areas of goods and services have been or plan to deploy artificial intelligence. Three major tasks, the ability to span the gap. Reconstruction of the business model is a complex and difficult task, business model optimization, innovation management and capacity building for enterprise cloud deployments three key tasks. A breakthrough and growth of digital capabilities to enhance the quality of digital manufacturing enterprises the ability to significantly improve the quality, most companies are committed to vertical integration data.
Figure 4: respondents the stage (based on corporate self-assessment)
Intelligent Manufacturing profits contributed significantly improve the intelligent manufacturing profit contribution rate has improved significantly, the source of profits, including the production process efficiency improvement and enhance the value of goods and services .
Figure 5: intelligent manufacturing products and services significantly improve the profit contribution rate
application market potential in China for six consecutive years for the first industrial robot consuming country, its unique advantages: First, the current boom in artificial intelligence behind the machine learning techniques extremely dependent, is the amount of data, the second Chinese manufacturing enterprise hardware equipment and plant relative European companies generally newer, relatively easy to implement device connectivity and plant transformation.
Figure 6: Global Industrial robot sales in major markets
Second, Chinese enterprises focus on the deployment of intelligent manufacturing intelligent manufacturing five major departmentKey Agency, as follows: Digital Factory (63%), and user equipment worth digging (62%), industrial things (48%), remodeling business model (36%), artificial intelligence (21%). Respondents related technologies of interest include industrial software, sensor technology, communications technology, artificial intelligence, networking, big data analysis.
Figure 7: intelligent manufacturing companies surveyed deploy key areas
Figure 8: Technical respondents concerned
a Digital Factory Digital Factory is listed as the primary task of intelligent manufacturing enterprise deployment. Open communication data stream includes three types of data, i.e., production process data, product data, and supply chain data.
Figure 9: production of the main types of data stream
B and a user equipment survey results show the value of the depth of excavation, excavation depth value of the user equipment and intelligent manufacturing enterprise deployment of the second focal area. 62% of respondents are actively deployed and the user equipment excavation depth value , 41% of the value of mining equipment business focus, 21% of corporate users focus value mining. c. Industrial IOT intelligent manufacturing requirements manufacturing system includes sensing, analysis, decision, and ability to perform, while the core of these capabilities are directed to the related art of things, such as for sensing the object-linking techniques (sensors, RFID, chip), Oriented Analysis the major industrial application platform for data analysis and decision-making and services. The results show that Chinese manufacturers were aware networking applications to focus on analysis and service blend will be the focus of future construction of things.
Figure 10: respondents typical things related to technology application
much of the future will come from value-added business activities across the enterprise, in the long run CONTROL ENGINEERING China Copyright , public cloud, hybrid cloud is the trend, because the only way to achieve data exchange and sharing of resources. Although private cloud security, but is likely to be isolated in the new business models and new ecosystem outside. Things in the field of intelligent manufacturing scenarios divided into three categories: equipment and asset management, product and service innovation insight. d. Reconstruction of future intelligent manufacturing business model will not only help manufacturing companies to achieve cost efficiency, but also gives a rethink of the value proposition and remodeling businessOpportunity for industry model. At the same time, new entrants are constantly challenging the status of the traditional market participants, many technology-based companies to join the battlefield on the promotion of industrial enterprises explore new and innovative business models. Business Planning for the future business model of roughly four categories: 30% of respondents future business model will be the platform as the core, 26% of companies take large-scale customization, 24% of “product + service” as the core of the solution business transformation, 12% of intellectual property rights as the core.
Figure 11: Respondents positioning the company’s future business model
e AI Artificial Intelligence impact on the manufacturing sector, mainly from two aspects: one is the use of artificial intelligence in manufacturing and management processes to improve product quality and production efficiency; the second is to overturn the existing products and services.
Figure 12: Respondents enterprise applications and the deployment of artificial intelligence (as a whole)
Figure 13: respondents artificial intelligence has not been the main reason for the deployment of
AI is rapidly penetrated into all walks of life. Motor vehicles and parts manufacturing, high-end equipment manufacturing, electronic and electrical industry uses three robots in the manufacturing process with the proportion of fruit. Motor vehicles and parts manufacturing industry companies use robots proportion reached 80%, indicating that future incremental market for industrial robots will come from non-automotive industries. In the field of goods and services have been deployed or industry of artificial intelligence is more evenly distributed, the higher the proportion of high-end equipment manufacturing and pharmaceuticals, other industries such as new materials, automobiles and auto parts, aerospace, electronics and electrical appliances are also planning to deploy or artificial intelligence .
Figure 14: Respondents enterprise applications and the deployment of artificial intelligence (by industry)
understanding of the industry with the development of artificial intelligence algorithm has been, technologies and applications, more and more deepened. For businesses, should only be out of artificial intelligence “machine substitutions,” the established thinking, many deploy lean manufacturing, product quality and user experience.
Figure 15: AI application scenario Industry


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