We will focus on sharing data analysis process systems and industry-related business scenarios.
1. Data analysis process system
First of all, we will introduce the process system of data analysis system, focusing on: data access, data processing, data set management, data analysis, indicator system, and labeling system.
1) Data access
Data access is the source point that supports data analysis, and the continuous data source of the data analysis system can be ensured through perfect data access capabilities. Data source management, including database data sources, file data sources, interface data sources, and information data sources. Data collection jobs support scheduling management and job access management functions. The data transmission log provides the function of recording the data acquisition operation process, which is convenient for users to monitor and deal with problems in the data acquisition process.
2) Data Processing
Data processing is an important support for data analysis, which can provide high-quality conversion from data resources to data assets and efficiently support data analysis. Data processing jobs support input from various data sources, including data cleaning, data association, data connection, expressions (mathematical, time, string, statistical, logical, analysis, and operators), aggregation, collection, filtering, sorting, unique identification, ordinal number, and row and column conversion. Job task configuration: supports the creation and configuration of data processing and data indicator job tasks, and supports the configuration of job execution rules and time conditions.
3) Dataset management
Dataset management is an important capability to support data analysis, and the core lies in supporting the direction of data analysis requirements and providing targeted data assets and data forms to meet the requirements of data analysis. Datasets: You can build datasets by dragging and dropping the fields of basic tables (including data sources, relationship diagrams, and basic tables under business topics) to meet the needs of data analysis in business scenarios based on the rapid support of datasets.
4) Data analysis
The large visual screen can provide support capabilities for enterprises in various forms, including: self-service dashboards, built-in rich components of independent dashboards, including chart components, indicator card components, filter components, tab components, table components, and rich text components; support for the basic components, components, title bars, axes, legends, advanced, graphics and other settings of the components; support for interactive design, including support for linkage, drilling, jumping, expanding/contracting, etc. Perspective analysis: Generate statistical reports through simple drag-and-drop operations, and select data dimensions and metrics for quick chart perspective analysis. Ad-hoc query allows users to flexibly configure filter conditions based on different scenarios to quickly present analysis data. Customized analysis to meet the customized analysis requirements of users for different business attributes, and carry out intelligent analysis.
5) Indicator system
The indicator system is an important experience solidification of data analysis, which precipitates the industry indicator system through data analysis capabilities, and directly provides data quantitative support for business scenarios through the indicator system. Indicator construction, including industry indicator template library and thematic indicator template library, can quickly build an enterprise indicator system through atomic indicators, derived indicators, and composite indicators. Indicator presentation clearly presents the lineage and historical data of the indicator, and the threshold and trigger conditions of the indicator alarm can be set. Metric monitoring: monitors key indicators and periodically refreshes metrics through configuration. Metric analysis, including indicator lineage analysis, model analysis, attribution analysis, and perspective analysis of indicator data. When a metric triggers a threshold, it can generate an alarm and push the alarm to users through email or other means.
6) Labeling system
Based on the basic capabilities of data analysis, a tagging system is built for business scenarios, and business scenario standards are carried out through tags, and the labeled scenarios are continuously analyzed. Label configuration, including object management, label management, and event management, to achieve intelligent marking. Group analysis realizes object grouping, group portrait analysis, and displays the label distribution and behavioral characteristics data of object groups in a visual way. In this way, the portrait information of the object group can be obtained in multiple dimensions and three-dimensional, and the portrait analysis of the object group can be realized.
2. Data analysis ability
Based on data analysis capabilities and related business scenario applications in the cement industry.
1) Intelligent production
Correlation analysis of big data in cement production. Based on the existing data basis, combined with the input and output parameters and control parameters of each link in the two grinding and one firing, the correlation between the two grinding and one firing was comprehensively analyzed, and the correlation between each link, the control parameters and the characteristics of the final product was found. Combined with expert experience, the precipitation is based on the empirical model of cement production.
Intervention in the cement production process based on good practice. Combined with the current production status in the accumulated data, find a regulation scheme suitable for the actual situation of the enterprise, provide data-based regulation and control suggestions for the cement production process, and combine human intervention to achieve the purpose of reducing costs and improving efficiency.
Intervention in the cement production process requires the establishment of a corresponding expert optimization system, which is completed by the operation of the operator instead of the automatic navigation method. Based on the expert optimization system's data analysis in the production process, the application of intelligent models and the continuous iterative optimization of production process control, the performance of the production system can be quickly carried out in an excellent operation mode, and such a model can be continuously extended to other production lines.
2) Smart devices
Digital twin shop floor equipment management. The digital twin workshop equipment management application system will provide real-time monitoring of equipment production lines and equipment, equipment data collection to monitor the real-time operation status of equipment in the cement production process, and detect equipment failures and equipment early warning and alarm conditions through equipment diagnosis and analysis, so as to form integrated equipment operation and maintenance measures and issue relevant operation and maintenance management measures.
Predictive maintenance of equipment. Realize the intelligent analysis and diagnosis of the running status of the equipment through online sensor detection and background software, including the key rotating equipment, and display the contents including: the operation data of the equipment, the alarm information of the equipment, the operation status of the system, etc. Through the rational layout, the platform can concisely and beautifully display the important monitoring information required, and the parameters of equipment monitoring can be displayed in two-dimensional plane mode through the visual customization function of the platform
3) Intelligent warehousing
Warehouse portrait model. The warehouse portrait model system first has the ability of warehouse management, including the measurement and statistics of raw material input, product consumption, raw material entry, product delivery, and the input and output of each device generated in the production process of the enterprise, as well as the functions of material storage inventory information, so as to realize the measurement of production performance as the basis, and calculate, count and track the production situation of the space (team, workshop, region, branch, group) and time (shift, day, week, ten, month, year) granularity range, and the functions include production measurement, Incoming and outgoing metering, material statistics, and material tracking. So as to realize the establishment of warehouse portraits.
Intelligent warehousing scheduling. According to the actual needs, the intelligent command and dispatch system of warehousing provides professional customized warehousing statistical analysis, provides multi-dimensional and different forms of warehousing reports, obtains real-time production process, equipment and energy consumption data, and dynamically displays some of the screens through the process screen, which can be customized to improve the convenience of software use; and mentions important production process information such as scheduling logs, production accidents, and production plans to online operation for easy management and maintenance. Through scheduling kanban, obtain information such as production process, equipment, energy consumption, etc., and fully control the production status of the front-line; Improve work efficiency;Real-time access to front-line production status information, so that the warehousing collaboration problems in the production process can be communicated to the management personnel in the first time, so that the problems can be dealt with in a timely and efficient manner;Realize the online operation of the production plan, combined with historical information and corresponding quality and other data, provide data support for the dispatcher to implement the new production plan;Mention the management of scheduling logs and production accidents online, which is convenient for query and traceability.
4) Smart energy
The purpose of the smart energy system is to comprehensively monitor the energy usage status of the entire cement plant, and to monitor each energy consumption unit in real time by automatically collecting various energy medium data (water, electricity, gas, steam, compressed air), etc., and to analyze and optimize the database storage and energy consumption data in real time, so as to realize the transparency and visualization of process energy consumption. It can also carry out the trend analysis of energy consumption indicators and the comparative analysis of various conditions, so as to discover the unreasonable energy use in the production process in time, set rules for key energy consumption units, and give immediate warning if the rules are violated. Based on the energy flow network model, energy balance method and system energy saving theory, the energy flow monitoring, energy efficiency diagnosis and analysis model, energy supply and demand prediction and scheduling model are established to achieve accurate prediction of energy supply and demand, so as to achieve the balance of energy supply and marketing from both static and dynamic aspects, so as to achieve the goal of improving the level of energy utilization.
5) Intelligent safety and environmental protection
Relying on intelligent terminals and edge intelligence, it automatically collects risk sources, identifies potential safety hazards, and realizes the integration, intelligence and collaborative management of automatic identification of hazards, risk classification and control, closed-loop management of hidden dangers and plant security. A set of intelligent safety and environmental protection models of collaborative identification, alarming, simulation, processing, and reporting can be embedded behind the back to ensure the closed-loop management of the safety and environmental protection system.
6) Smart management
Dynamic overall planning and optimization of production resources. As a high-energy-consuming industry, how to coordinate various production factors, continuously optimize the regional layout, and carry out construction work from enterprise production and operation management to the environment, pollution and environmental index of the production process under the current dual carbon policy is an important consideration to comply with the current trend of improving the total factor productivity of high-energy-consuming industries in mainland China based on the environment. By incorporating production and operation management, energy consumption and environmental pollution into the capacity balance analysis framework, the dynamic overall planning and optimization of production resources is realized. Based on production control and environmental protection requirements, the on-demand regulation of production capacity in different regions is realized.
Production and operation, production and marketing balance sand table. The production and operation production and sales balance sand table mainly helps to realize the transparency of the operation and management of cement enterprises, whether the business results are compared with the annual targets and historical data to maintain sustainable and steady development, and whether the business activities are predicted, simulated, and assisted in optimization suggestions. On the basis of the overall resource optimization model, the production and sales balance will be combined with the current raw material cost (limestone, coal, electricity, etc.), price information (including the price of its own products and the price of competing products), historical profit information, market demand, etc., to further optimize the model, evaluate the shutdown of the kiln line, output the production and operation plan, and achieve the regional profit target.
To sum up, the data analysis support capability of the cement industry should ensure the full life cycle service for business scenarios. There is a lot of potential for data analysis and data mining in business scenarios such as production, equipment, warehousing, energy, safety and environmental protection, and production and operation control in the cement industry.
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