The hottest IBM Internet of things 30 achieves ind

IBM: IOT 3.0 achieves industrial intelligence

what are the troubles of a traditional Snowboard manufacturer? They will complain bitterly about high production costs, long manufacturing cycles and high inventory pressure. Due to the strong seasonality of skiing, natural snow and artificial snow have different requirements for the material of skis. Manufacturers often have a headache about how much inventory they should prepare for skis in different seasons? IBM adopted the big data solution, which not only reduced the production cycle of skis from the past 16 days to 8 days, but also reduced the inventory by 80%. During production, it also installed sensors in each part process, and refined the quality control to each process flow by collecting and analyzing sensor data. This scene of smart manufacturing has been realized at Blizzard, an Austrian ski manufacturer

in Blizzard's case, IBM's intelligent manufacturing approach has shifted from static data focusing on manufacturing itself to interactive data focusing on social public opinion, and has used models to predict the weather and its impact on sales. This is what happened in the world of IOT 3.0. At the China IOT conference in May 2015, IBM analyzed the concept of IOT 3.0. In the era of IOT 1.0, people are committed to building systems that connect things, and data can be perceived, transmitted and processed in real time; In the era of 2.0, the data generated by the connection of objects has surpassed the traditional IT information processing architecture, and the processing, refining and analysis of massive data need better platform support. In the era of 3.0, the integration with big data and cloud computing creates a new ecological environment of IOT

this ecological environment runs through the whole process of industrial manufacturing, from product research and development, production and manufacturing, operation management, to product sales and service. This gives a broader extension to the concept of tangible industrial robots (industrial robot arms), 3D printers or intelligent machine tools produced in the factory. In the environment of IOT, big data has become an invisible intelligent robot, which is the result of the connection between things and people, and can even replace the human brain as the manufacturing command center

the combination of IOT 3.0, big data and cloud

the essence of its industrial 4.0 vision is to realize the concept of IOT, interconnection and intelligence, and it is the key driving force for industrial enterprises to achieve the development of the industrial 4.0 era. It can be seen that IOT plays an important supporting role

how does the technology processing ability of IOT 3.0 play a data-driven role? Dr. Sun Wei, director of IOT and service delivery research at IBM China Research Institute, believes that the role of the following three levels

first, mining patterns from historical data. People need to clearly understand the essence of the problem, whether to analyze the operation status and failure mode of industrial equipment through big data, or to analyze the customer's habit mode of using equipment. After knowing what needs to be solved, ask to find a method to solve this problem, clean up the data and extract effective data features on the basis of summarizing various data sources for data modeling

the second is to promote the analytical ability of cognitive computing through human-computer interaction. Cognitive computing simulates the human brain's processing, thinking and decision-making methods of external information to support more intelligent human-computer interaction. The cognitive computing ability based on big data can be applied to different fields, such as automatic driving. When the working temperature of the low-temperature thermostat is low, the choice of driving route in car driving can be obtained. Through the analysis of real-time information of traffic routes, as well as the analysis and prediction of road conditions and weather conditions data, a more comprehensive optimized driving route can be obtained than the judgment of human brain

the third is to realize physical modeling and working mechanism modeling. Different from the financial and service industries, the working mechanism of industrial equipment under different working conditions needs to be characterized by physical models. For example, wind turbine power generation requires not only monitoring the operating parameters and power generation of the wind turbine, but also referring to the real-time meteorological monitoring information around the wind farm and the large-scale meteorological data monitored by satellites, so as to provide the physical and working mechanism model of wind power generation, and improve the spatial accuracy of wind prediction to the range of each wind turbine, so as to optimize the operation of the wind turbine and the storage and control of electric energy

car service is to promote the development of highly intelligent industrial products with the help of cloud computing and big data. In the field of automatic driving, hundreds of sensors on a vehicle will generate and process vehicle operation data in real time. After these real-time processed data are transmitted back to the cloud platform as thousands of vehicles, with the support of car service cloud, information collaboration can be realized between vehicles and between vehicles and roads. Vehicles driving in the rear on the road can obtain the road information in front by means of real-time observation of vehicles in front, Car owners in place a can also know the road conditions of place B to support the timely adjustment of driving routes and vehicle control. These data can not only become the basis for urban intelligent transportation management, but also support various automobile related financial and insurance innovations and vehicle information service innovations

IOT 3.0 not only realizes the intellectualization of products and services, but also promotes the intellectualization of enterprise business processes and manufacturing processes. After the data collected through IOT and Internet for customers' use of products and services are processed and analyzed by the "implementation plan for the demonstration of the utilization of bio based materials products", taking the construction of regional clusters and the utilization of products as the development carrier, new insights into customers' needs continue to be formed, which can promote the intellectualization of the business process of product research and development. After the industrial manufacturing process monitoring data collected through IOT is processed and combined with the modeling and analysis of the physical model of the manufacturing process, the manufacturing process planning, material supply and equipment state control parameters can be dynamically adjusted in real time to support the intellectualization of the manufacturing process. This makes the collaboration of enterprise production and service process change from the collaboration between various departments within the enterprise and the traditional supply chain to the collaboration and optimization of the whole process, all directions and socialization of the enterprise supported by IOT and interconnected big data

how to empower made in China

SUN Wei believes that the deep integration of industrialization and informatization is the foundation of intellectualization

there are many ways for Chinese manufacturing enterprises to move towards intellectualization. In terms of internal skill cultivation, enterprises need to integrate the whole process data from production and manufacturing to customer service, supply chain and product maintenance, which is the core work. At the same time, we should also find valuable data insights from the information generated on the Internet, such as using Internet customer community media data to analyze the effect of enterprise marketing activities and consumers' evaluation of enterprises and products; Use the meteorological data provided by the Internet service to support the decision-making optimization of production and operation affected by the weather

in fact, intelligent production driven by big data is a process that can be large or small, and enterprises do not have to worry about the high investment of funds. Bruce A. Anderson, general manager of sales and distribution in IBM's global electronics industry, said. This small can be reflected in the optimization of only cutting into a certain production link, such as installing smart cameras on the assembly line, optimizing quality monitoring through image analysis in the production process, or establishing a version database with the help of physical version digital conversion, so as to quickly carry out the installation and replacement of version design, grading, fabric redundancy testing, and save the high cost of the version designer, From low-end garment processing to high value-added version service providers. The big one is reflected in the upgrading of the whole process

in the past, people often talked about the integration of industry and informatization. Now informatization has gone beyond the scope of traditional informatization, but integrates the new data sources provided by Internet of things and related ecosystems. Sun Wei said that this is a new change and an opportunity for future enterprise development to create new industrial value with big data