At a glance, you will know the transformation road

2022-09-22
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At a glance, you will know the transformation road of Sany Heavy Industry

at a glance, you will know the transformation road of Sany Heavy Industry

China Construction machinery information

big data and intelligent manufacturing have brought great impact to traditional industries. Powerful industrial data analysis services will become an important part of the digitalization strategy of manufacturing enterprises, and industrial IOT will show greater strategic value

in 2014, Sany group started the construction of big data platform. Through independent research and development of big data storage and analysis platform, namely "ECC customer service platform", it can realize two-way interaction and remote control of equipment, and can transmit the data of real-time operation of more than 200000 customer equipment to the background through sensors for analysis and optimization. The ultimate goal is to achieve low-cost massive equipment data access and analysis, Sharp insight into user behavior and closed-loop feedback throughout the life cycle. Users can master the status of the machine in all aspects anytime and anywhere through the page or app. The "M2M remote data acquisition and monitoring platform" has been commercialized on a large scale, and has built the first domestic construction machinery IOT enterprise, striving to replace 2/3 of transfer bags with environmental protection bag industry control center by 2020

in fact, in order to make industrial data finally form business opportunities, we need to pay attention to four aspects:

1 communicate. That is, equipment environmental signal identification. The key point of signal recognition is that the real-time performance in the process of information collection is not enough, and the object of signal recognition is not complete and comprehensive, which is the first problem to be considered in establishing the ability of industrial big data

2. Integration and integration. That is, the data platform of big data. The so-called integration means that all touchable and non touchable data such as OA, knowledge base, ERP and procurement system should be connected in series. Our whole series work still has a very long way to go

3. Analysis and decision-making. Our big data modeling ability is not poor. What is missing is our investment in understanding the industry and the ability to form models, as well as the continuous investment in pushing down, reconstruction and adjustment, because it may take many years to make a good model, and we need to constantly revise it. This ability is not hair trigger, and we need to pay attention to it

4. Create a disruptive self-service culture. Machines can learn and adjust themselves. By shifting the focus to invisible factors, data gives us a new multi perspective to discover innovation, and ultimately leads to revolutionary business opportunities

industrial interconnection/IOT

the emergence of industrial IOT and industrial big data, as well as the related predictive analysis in the manufacturing industry, and the rise of asset intensive departments, make "asset performance management" or APM a focus of this round of information and intelligent construction

from the perspective of conservatives in a narrow sense, the focus of asset performance management should be the "control and decision-making skills" of asset performance. From the broad definition of management, we will also include the management of "the behavior of controlling asset performance"

although some differences between narrow sense and broad sense can also be used as a reference for methods and models to identify other types of recycled plastics, it helps to explain the evolution of asset performance management from a single point solution to a method to achieve operational excellence. This approach covers everything from raw data on the condition of assets and equipment to enterprise asset management applications for recording, planning and scheduling maintenance activities. Therefore, I believe that asset performance management is a business process that supports operational excellence

strengthen and attach great importance to big data application

the big data application carried out by Sany Heavy Industry is mainly in the following aspects: predicting the macro environment, analyzing the product structure, predicting equipment failure, and predicting the demand for accessories

in the future, intelligent devices must be able to independently evaluate health and degradation, actively prevent potential performance failures, and make maintenance decisions. To realize health condition assessment, we need to use data-driven algorithm to analyze the data from mechanical equipment and its surrounding environment. The real-time equipment condition information can be fed back to the mechanical controller to realize adaptive control, and the information will also be fed back to the equipment management personnel to facilitate timely maintenance. The operator can balance and adjust the workload and working pressure of each equipment according to the health conditions of each equipment, so as to optimize the production and equipment performance to the greatest extent, and realize the intelligent decision of active maintenance plan

in the long run, the value of hardware manufacturing end is declining, and the value of intelligent products will continue to increase. Big data and intelligent manufacturing have brought great impact to traditional industries. Powerful industrial data analysis services will become an important part of the digitalization strategy of manufacturing enterprises, and industrial IOT will show greater strategic value

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