CN116681199A - Intelligent mine beneficiation system - Google Patents
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Abstract
The invention relates to an intelligent mine beneficiation system, which is characterized in that: the intelligent ore dressing production control system comprises a mine cloud platform, an ore dressing production command remote control center, an edge optimization control system and an ore dressing intelligent production control system; the mine cloud platform is respectively connected with the intelligent mine mineral separation production control system and the mineral separation production command remote control center in a communication manner; comprises an intelligent collaborative mineral separation production management and control system, a mineral separation energy management system, a mineral separation safety management system and a three-dimensional simulation system of an intelligent mineral separation plant. The invention establishes an enterprise intelligent manufacturing system architecture and implementation by using communication and information technology and artificial intelligence technology, realizes accurate sensing and accurate control of the whole production process, forms a collaborative management and control system based on standardization, lean, digitization, automation and intellectualization, and realizes the aim of improving the production efficiency of enterprises.
Description
Technical Field
The invention belongs to the technical field of mineral separation, and particularly relates to an intelligent mine mineral separation system.
Background
The intelligent mine is based on the premise of mine digitization and information, and is used for actively sensing, automatically analyzing and rapidly processing mine production, occupational health and safety, technical support, logistic guarantee and the like, so that the intelligent mine is built, and finally, the construction of a safe mine, an unmanned mine, a high-efficiency mine and a clean mine is realized. The intelligent mine mineral processing system is a system which is built on the basis of digitalization, informatization, virtualization, intelligence and integration, comprehensively considers various factors such as production, management, operation, safety, benefit, environment and resources, comprehensively and efficiently carries out mineral processing management on various information resources of mines by using technologies such as computers, networks, communication, virtual simulation, automatic control and monitoring, and the like, and covers the whole process of production and operation of mine enterprises. The system reduces the labor intensity of mine production and improves the working efficiency; resolving mine risk hidden danger and enhancing a safety system; resources are reasonably developed, and resource waste and environmental pollution are reduced.
The intelligent mine mineral separation system is built, so that the digitization of safety management can be realized, information guarantee is provided for the construction of intrinsically safe mine mineral separation, the refinement of production management can be realized, and decision basis and means are provided for the construction of high-yield and high-efficiency mineral separation production.
The framework system of the traditional intelligent mine mineral separation system framework lacks of interconnectivity, the overall operation efficiency is relatively low, and no modern intelligent mine mineral separation management method matched with the framework system is available.
Research and construction work related to automation, digital ore dressing and intelligent mine ore dressing are sequentially carried out by each research institution and production enterprises in China, but most of the research institutions start from a local link and do not penetrate through the whole process, and problems of different ideas, data obstruction, different standards, different methods and the like exist in the construction of an intelligent mine ore dressing system, so that the informatization and intelligent processes of mines are seriously hindered, and related research results cannot be comprehensively popularized.
Therefore, the intelligent mine mineral separation management system and method based on the intelligent mine management and control platform, which are safe, efficient, high in management, low in cost, high in interconnectivity, low in manpower resource cost and production cost, simple in method and easy to operate, have wide application prospects.
Disclosure of Invention
The invention aims to provide an intelligent mine mineral separation system which starts from the global production of the whole mineral separation plant, runs through the whole flow of the production process, is oriented to intelligent production management and control of 'ore flow', has less humanized and unmanned production of the whole flow, and is an intelligent factory which integrates intelligent decision based on industrial big data.
The object of the present invention is thus achieved.
The invention relates to an intelligent mine beneficiation system, which is characterized in that: the intelligent ore dressing production control system comprises a mine cloud platform, an ore dressing production command remote control center, an edge optimization control system and an ore dressing intelligent production control system; the mine cloud platform is respectively connected with the intelligent mine mineral separation production control system and the mineral separation production command remote control center in a communication manner;
the mine cloud platform is used for docking industrial equipment and facilities, comprehensively connecting machines, data and systems with people, and is an operating system of the intelligent production management and control system for mineral separation;
the edge optimization control system is oriented to production processes, a process optimization model is established by utilizing cloud big data analysis and edge calculation technology, a process optimization and adjustment strategy is output, and cooperative optimization in the processes and among the processes is realized through integration with the control system, so that support is provided for fine production management and control;
The intelligent mineral separation production management and control system establishes an enterprise intelligent manufacturing system architecture and implementation by using communication and information technology and artificial intelligence technology, realizes accurate sensing and accurate control of the whole production process, forms a cooperative management and control system based on standardization, lean, digitization, automation and intellectualization, and realizes the aim of improving the production efficiency of enterprises;
the remote control center for mineral processing production command is a vertical management system of the mineral processing production command center to a machine platform and a post, displays index information of mineral processing production flow in real time, provides technical support for mineral processing production decision, displays energy consumption statistics and analysis in real time, and finishes progress of yield plan, causes of production problems, finishes and trends of mineral processing production cost and mainly comprises the cost, realizes remote start and stop of equipment and production process adjustment through station operation, and monitors production process change in real time.
Preferably, the mine cloud platform comprises a mine industrial internet platform and a big data platform, wherein the mine industrial internet platform is a carrier for realizing intelligent factories and intelligent mines, the edge layer of the mine cloud platform is in butt joint with industrial equipment and facilities, the platform layer combines cloud computing, big data technology and actual experience of industrial production to form industrial data basic analysis capability, and a cloud open sharing development environment is constructed; the industrial internet APP of the application layer uniformly manages and controls the upper application system and provides consistent external service; the big data platform provides strong real-time stream processing capability and offline batch processing capability, and can conveniently process stream processing of data. The method has the advantages that the method provides strong data analysis and mining capability, can quickly perform visualization classification of data under a large data scale, performs deep mining on the data through the strong machine learning capability provided by a large data platform, builds a unified data storage, collection, analysis and management environment, and continuously integrates and distributes the environment, and realizes unified data storage, data collection, data analysis and management.
Preferably, the edge optimization control system consists of three modules, namely an edge integration module, an edge calculation module and a Bian Yun cooperative module,
the edge integration module is used for upwards butting an enterprise application system, downwards butting specific hardware equipment of a factory, enabling an upper layer application to realize the functions of monitoring, controlling and operating the bottom layer hardware equipment by calling a unified interface, automatically analyzing different communication protocols of different hardware equipment, and automatically converting binary data messages and available data with practical significance;
the edge computing module deploys an edge computing resource environment facing edge computing nodes, provides computing capability, realizes edge infrastructure management, provides reliable and efficient cloud side information synchronization, realizes persistence of local metadata, abstracts physical equipment, generates a mapping of equipment states at a cloud end, subscribes to equipment data, builds edge application with a micro-service architecture, and deploys according to a scene of an intelligent task;
the Bian Yun cooperation module is oriented to industrial intelligent control scenes and comprises two major categories of equipment optimization and process optimization, wherein the equipment optimization Bian Yun is cooperated, the health state and performance of the equipment are optimized by intelligent analysis on the acquired equipment data, and the process optimization Bian Yun is cooperated: mainly applied at the level of a process section or a production line, and flexibly deployed and adjusted according to the needs.
Preferably, the intelligent mineral separation production management and control system comprises an intelligent cooperative mineral separation production management and control system, an intelligent mineral separation energy management system, an intelligent mineral separation plant three-dimensional simulation system.
Preferably, the intelligent collaborative beneficiation production management and control system is used for factory modeling, plan management, production scheduling, quality management, process tracking, material consumption management, operation guidance management, production cockpit module index data management, basic management module and system integration;
the factory modeling takes the ore dressing process as a main line, comprises product material modeling, tissue structure modeling and production process modeling, realizes the digital description of core production elements of what is produced, what production resources are available and how to produce, and lays a foundation for the realization of other business functions;
the plan management realizes the decomposition of the month plan according to the annual and quaternary plans issued by the company, and then realizes the decomposition of the week plan and the day plan according to the mining and ore-distributing information; the planning production is optimized based on the ore-distributing raw ore property and the equipment inspection maintenance plan, the production is optimized towards the productivity consumption balance target, the equipment process preparation and the station time plan are formed, and the planning production is estimated; the yield statistics is based on the daily formation index statistics of actual production conditions, the steady state and trend of the productivity are estimated, the steady state and trend of the productivity are gradually fed back to a weekly plan and a monthly plan, and monthly production operation accounting is finally formed;
The production scheduling is characterized in that on the basis of planning and scheduling production, a mineral processing production planning target is converted into mineral processing production process requirements and actual production operation tasks to be decomposed into production operation areas, specific starting and time planning and operation instructions are formed and are issued to production equipment, and the operation scheduling is comprehensively optimized according to the capacity demand of bottleneck working procedures and the capacity allocation conditions, equipment maintenance and energy consumption conditions of other working procedures, so that balance of capacity, quality and consumption is realized;
the quality management system realizes the online collection, storage and sharing of quality inspection test data, realizes the non-landing of the quality data of the factory selection, and provides a reliable data source for an upper business system;
the process tracking realizes energy consumption tracking, production plan tracking and quality tracking by collecting energy consumption data, production index data and quality index data of the edge computing system, realizes material consumption tracking and on-site worker tracking by data generated by the material management subsystem and the production scheduling and operation execution subsystem, checks production plan and actual completion conditions in real time, and tracks quality index information, energy consumption information and material consumption information in real time;
The material consumption management is used for carrying out statistical analysis on the purchasing, inventory and receiving processes of materials such as bulk materials, production auxiliary materials, energy sources and the like, and the energy consumption, the material consumption, the yield and the cost;
the function module for electronically displaying the operation instruction of the factory selection performs unified management and centralized control on the operation instruction of each process of the factory selection, and the operation instruction is accurately issued to the operation terminal;
the production cockpit is used as a comprehensive data visualization system of an intelligent factory, and covers the visual display of statistical management data and execution process data of businesses, so that the visualization of multi-element data from an industrial interconnection platform is realized rapidly in a graphical configuration mode according to business scene requirements, and the factory selection realizes production management transparency and enterprise management cockpit;
the index data management is oriented to the ore dressing whole production flow, a multidimensional index system is established, the ore dressing technical economic index and the ore dressing production process index related to the ore dressing integrated management are covered, the correlation and the gradual decomposition among indexes are formed, the calculation and statistics methods of various indexes and direct data sources are clear, the automatic calculation and gradual summarization of the indexes can be realized according to the acquisition of the real-time process data of the system, the calculation, the aggregation and the statistics of the indexes at all levels are realized on the basis of the establishment of the index system, various personalized statistical forms and analysis results are output, and the index correlation analysis and the data mining are realized by utilizing the big data analysis technology;
The basic management, supporting the basic service of system operation, forming personalized function requirements for the intelligent collaborative production management and control system based on the whole basic service provided by the cloud platform, and realizing flexible configuration of user role management, resource authority management, message management and log management;
the system integration, the management and control system is a system facing the production site, and is also an information transmission system for connecting the operation layer and the site control layer, and the system and the upper business system and the bottom edge computing system form an enterprise nervous system, so that instructions of business planning are transmitted to the production site, and information of the production site is timely collected, uploaded and processed.
Preferably, the energy management system is used for instrument foundation management, instrument state management, energy data monitoring, energy information early warning, energy information prediction, energy information statistics and energy information analysis;
the instrument foundation management provides operation for instrument information, energy statistics is carried out on units where the instrument information is located by each operation area, statistical results are reported to an energy office, integration is carried out, numerical comparison is carried out on the integrated energy data and the total energy data of each production technical department, and energy balance is judged;
The instrument state management is characterized in that a main manager checks the instrument operation state of an operation area of the designated equipment, and when the instrument fails and a link problem occurs, alarm prompt of a designated level is carried out according to the specific problem, and log inquiry of the instrument is provided;
the energy data monitoring is used for monitoring regional energy and integrally monitoring the key energy utilization units at the regional level, a factory-level energy monitoring layout is provided firstly, the overall energy utilization condition of a main operation area included in a factory is displayed, and an energy monitoring interface of a corresponding operation area can be accessed; the operation area level comprises the overall use condition of specific energy, the energy use condition of specific energy utilization equipment, and real-time data monitoring is carried out on the instrument;
the energy information early warning is used for judging the instantaneous quantity, the cumulative quantity and the threshold value of energy in the production process, and further making corresponding early warning prompts, wherein the energy information early warning comprises instantaneous quantity early warning and cumulative quantity early warning;
the energy information prediction realizes characteristic analysis based on historical energy consumption data according to energy consumption information, and assists in forming functional plan assessment and prediction;
the energy information statistics is carried out by taking an operation area as a dividing limit and a team as a recording unit, and comprises various dosage information and product yield information of corresponding time periods, so that a team energy report of a daily operation area is formed, and an energy management center calculates energy information of the whole plant according to the daily energy report of each operation area;
The energy information analysis comprises energy balance analysis, energy behavior analysis and energy comparison analysis; the energy balance analysis is used for carrying out classification statistics on the supply quantity, conversion and consumption of energy in each operation area, and analyzing whether the net inflow and consumption of energy are consistent or not as a whole, wherein the difference is an instrument statistical error or an energy omission item; analyzing the process energy supply amount and the equipment energy consumption amount before and after the use of the energy from the process, and searching the unbalanced energy consumption reason from the process energy source; the energy behavior analysis is carried out, corresponding energy consumption guidance is given by counting the energy use time period, the energy consumption process and the use equipment of the factory selection and combining the equipment station time and the production process requirements of different processes, and an enterprise energy consumption behavior model is established so as to simulate the energy cost of the enterprise under different energy consumption behaviors; and (3) energy comparison analysis, namely, comparing the operation area and the energy utilization equipment according to items, including ring ratio, same ratio, historical best level and average level, and comparing the historical best level and average level with the standard in the industry, and finding out influencing factors of energy consumption change.
Preferably, the safety management system module is used for potential safety hazard management, staff safety training, staff safety assessment and key personal electronic files; the method is characterized in that big data analysis is used as a core operation platform, safety problems focused on by concentrating mills, including potential safety hazards, employee safety training and safety assessment are collected, stored and analyzed, a safety problem database of an enterprise is established, full-flow safety informatization and visual management are realized, safety responsibility is realized, safety executive force is enhanced, and scientific basis is provided for safety decision of the enterprise;
The potential safety hazard management: static potential safety hazards are input into the system for repeatability
Giving a prompt for static hidden danger;
the staff safety training comprises national laws, regulations, standards and specifications related to safety production, basic knowledge, methods and technologies for safety production management, major accident prevention, emergency rescue, typical accident cases and the like;
the staff safety assessment is carried out, when the staff is checked and found to have the first dynamic safety problem including illegal or nonstandard operation, the staff is assisted by a safety officer in an operation area to analyze the reason of the dynamic problem, safety training in a certain class is carried out, and after the training is finished, a training track and an assessment condition are input into the system to form a staff safety assessment record;
the security key person electronic file comprises a security check record, and for staff with secondary and above same-class dynamic problems, the security key person electronic file is listed, and the electronic file content can comprise key person names, security problem descriptions and problem occurrence frequency information.
Preferably, the intelligent factory selection three-dimensional simulation system module comprises a basic functional module, a solid modeling and visualization module; based on the combination of the mineral separation equipment of the entity mineral separation plant and the production operation data of the plant infrastructure and the three-dimensional simulation system, the three-dimensional virtual mineral separation plant is presented, all units of the entity plant, the equipment operation information, the production process information, the image information and the three-dimensional model are linked, the dynamic simulation display is carried out on the three-dimensional model, the visual management and the omnibearing three-dimensional management and control of the production process are realized, the centralized optimization command and dispatch are realized,
The basic functional module comprises: user rights management, providing functions of user, role and rights management; scene management, 3D scene asset resources, management attribute modification of the scene of the physical place; model management, supporting built-in and externally imported model libraries; the data interface management adopts a universal data interface, is easy to integrate and expand, integrates various file formats, and meets the requirement of subsequent expansion of the system; the data display is used for monitoring the data collected by the entity concentrating plant in real time, restoring the running state/action of the field equipment and intuitively grasping the comprehensive running condition of the production/equipment; the video interface is in butt joint with the corresponding camera interface, and the real-time video picture is called by clicking the camera in the 3D scene; the roaming inspection, virtually simulating patrol concentrating mills through set routes in different view angles, and restoring all the scenes in the buildings and the factories one by one as if the scenes are on the scene;
the entity modeling is divided into two modules, namely infrastructure modeling and equipment personnel modeling, wherein the infrastructure modeling comprises factory layout, buildings (factory buildings), crushing stations, belt galleries, intermediate ore bins and other infrastructures; modeling equipment personnel, and accurately representing the working states and dynamic parameters of the personnel and the equipment;
The visual application module comprises: the dynamic data display module is used for sharing production data, equipment data, safety data and management data in the mineral processing system, collecting all real-time information collected and selected on a unified platform, and displaying the real-time information on a three-dimensional graph intuitively and dynamically; the whole 3D virtual mining area can be seen from the air through a bird's eye view and displayed in a 3D electronic sand table form; in order to view a specific working section or equipment in a short distance, certain key equipment or production flow which can enter a roaming mode can be dynamically displayed through animation; the abnormal information linkage module can share fault information and alarm information of each unit and module for ore dressing, automatically respond, draw to fault and alarm occurrence places, directly check information details and corresponding machine stations and process details, and call peripheral video monitoring to check site conditions;
the video system linkage module comprises a video monitoring unit and a three-dimensional simulation unit, wherein all cameras in the video monitoring unit are displayed on the three-dimensional simulation unit in the form of icons, and corresponding video information can be checked.
The invention has the advantages that: the intelligent mine beneficiation system is used for promoting the application of the front technologies such as the Internet of things, big data, artificial intelligence, edge calculation, virtual reality and the like in mines on the basis of automation and informatization construction, and is used for establishing digital management of resources, intelligent production management and control for 'ore flow', less humanized production in the whole process, safe and efficient intelligent factories integrating intelligent decision based on industrial big data, improving the construction level of green mines and intelligent mines and improving the production quality and economic benefits.
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Fig. 1 is a system block diagram of the present invention.
Description of the embodiments
The invention is further described below with reference to the accompanying drawings.
As shown in fig. 1, the intelligent mine beneficiation system of the present invention is characterized in that: the intelligent ore dressing production control system comprises a mine cloud platform, an ore dressing production command remote control center, an edge optimization control system and an ore dressing intelligent production control system; the mine cloud platform is respectively connected with the edge optimization control system, the intelligent mine mining production management control system and the mineral separation production command remote control center in a communication manner;
the mine cloud platform is used for docking industrial equipment and facilities, comprehensively connecting machines, data and systems with people, and is an operating system of the intelligent production management and control system for mineral separation;
The mine cloud platform comprises a mine industrial internet platform and a big data platform, and is a carrier for realizing intelligent factories and intelligent mines, wherein the edge layer of the mine cloud platform is in butt joint with industrial equipment and facilities, and the connection of machines, data and systems with people is comprehensively opened; the platform layer combines cloud computing, big data technology and actual experience of industrial production to form industrial data basic analysis capability, and the resources such as technology, knowledge, experience and the like are fixed into transplantable and reusable software tools and development tools such as a professional software library, an application model library, an expert knowledge library and the like, so that a cloud open shared development environment is constructed; the industrial Internet APP of the application layer is based on the industrial Internet, is oriented to the scene requirements of related business (design, production, experiment, use, guarantee, transaction, service and the like) of the whole life cycle of the industrial product, and encapsulates knowledge and best practices in the industrial product and related technical processes into application software. And the upper application system is uniformly controlled, so that basic resources are saved, and consistent external service is provided. Four modules are included: cloud infrastructure service system, operation management system, cloud application management system, operation maintenance management system.
The big data platform provides strong real-time stream processing capability and off-line batch processing capability, and can conveniently carry out stream processing such as real-time cleaning on data. The method provides powerful data analysis and mining capability, and a user can quickly perform visual analysis of data under the large data scale of PB level. Users can further explore unlimited value stored in mass data through the powerful machine learning capability provided by the big data platform. And constructing a unified data storage, collection, analysis and management environment and a continuous integration and release environment, guaranteeing the system quality, stability and continuous iterative update of a large data platform, and realizing unified data storage, data collection, data analysis and management capability. Comprising the following steps: the system comprises a data acquisition module, a data storage module, a data processing module, a data analysis module, a data mining module, a data visualization module and a data treatment module.
The edge optimization control system is oriented to production procedures, a process optimization model is established by utilizing cloud big data analysis and edge calculation technology, a process optimization and adjustment strategy is output, and cooperative optimization in the procedures and among the procedures is realized through integration with the control system, so that support is provided for fine production management and control;
The edge optimization control system consists of three modules, namely an edge integration module, an edge calculation module and a Bian Yun cooperative module,
the edge integration module is used for upwards butting an enterprise application system, downwards butting specific hardware equipment of a factory, enabling an upper layer application to realize the functions of monitoring, controlling and operating the bottom layer hardware equipment by calling a unified interface, automatically analyzing different communication protocols of different hardware equipment, and automatically converting binary data messages and available data with practical significance;
the edge computing module deploys an edge computing resource environment facing edge computing nodes, provides computing capability, realizes edge infrastructure management, provides reliable and efficient cloud side information synchronization, realizes persistence of local metadata, abstracts physical equipment, generates a mapping of equipment states at a cloud end, subscribes to equipment data, builds edge application with a micro-service architecture, and deploys according to a scene of an intelligent task;
the edge optimization control system of the invention consists of three modules, namely an edge integration module, an edge calculation module and a Bian Yun cooperative module,
the edge integration module is used for upwards butting an enterprise application system, downwards butting specific hardware equipment of a factory, enabling an upper layer application to realize the functions of monitoring, controlling and operating the bottom layer hardware equipment by calling a unified interface, automatically analyzing different communication protocols of different hardware equipment, and automatically converting binary data messages and available data with practical significance;
The Bian Yun cooperation module is oriented to industrial intelligent control scenes and comprises two major categories of equipment optimization and process optimization, wherein the equipment optimization Bian Yun is cooperated, the health state and performance of the equipment are optimized by intelligent analysis on the acquired equipment data, and the process optimization Bian Yun is cooperated: mainly applied at the level of a process section or a production line, and flexibly deployed and adjusted according to the needs.
The intelligent mineral separation production management and control system comprises an intelligent mineral separation cooperative mineral separation production management and control system, a mineral separation energy management system, a mineral separation safety management system and a three-dimensional simulation system of an intelligent mineral separation plant, wherein an intelligent manufacturing system architecture and implementation of an enterprise are established by using communication and information technology and artificial intelligent technology, so that accurate perception and accurate control of the whole production process are realized, and a cooperative management and control system based on standardization, lean, digitization, automation and intelligence is formed, so that the aim of improving the production efficiency of the enterprise is fulfilled;
the intelligent collaborative beneficiation production management and control system is used for factory modeling, plan management, production scheduling, quality management, process tracking, material consumption management, operation guidance management, production cockpit module index data management, basic management module and system integration;
The factory modeling takes the ore dressing process as a main line, comprises product material modeling, tissue structure modeling and production process modeling, realizes the digital description of core production elements of what is produced, what production resources are available and how to produce, and lays a foundation for the realization of other business functions;
1.1 modeling of the product materials of the invention: the method mainly surrounds the ore dressing process flow, establishes a full-flow product, intermediate product and related material definition and association from ore dressing raw ore input, and processes through various process links until finished product concentrate is produced, forms an ore product flow model main line of raw ore-mixed magnetic concentrate, tailings-flotation concentrate, tailings-filter pressing concentrate and tailings, and simultaneously forms a production process consumable model containing ball-milling steel ball proportion, flotation reagent and components and proportion of the concentrate reagent, a production equipment spare part consumable model containing a crusher, a ball mill lining plate, filter press filter cloth and the like, and an energy consumption model containing flotation steam, water and electricity for various links and the like. The main attributes of the model include: material coding/name, physical form, composition property, specification model, measurement index, measurement unit, etc.
1.2 modeling of the tissue structure of the present invention: the method is characterized in that a model is built around key manufacturing resources and capabilities of a factory, the equipment layer is embodied as a hierarchy relationship of a production operation area, a production area, an equipment unit, a single machine, equipment and key parts, and the personnel layer is embodied as a hierarchy relationship of a production operation area, a post role, a production team and personnel.
1.3 modeling the production process of the invention: realizing the model construction of the technological process, the technological control standard, the process and the finished product quality inspection standard related to the mineral separation technology. The mineral separation production pursues stable production of the process under the condition of high-efficiency and continuous operation of equipment, and the process flow and the standard need to form an accurate dynamic association relation with the process equipment so as to support flexible process adjustment under the condition of changing properties such as mineral proportioning quantity, mineral phase, grade and the like. The main attributes of the production process model include: raw ore species and grade, process-procedure flow, process control parameters and standards of each stage, test indexes and standards of each stage, and the like.
According to annual and quaternary plans issued by a company, decomposing a monthly plan is realized, and then according to mining and ore-distributing information, decomposing a weekly plan and a daily plan is realized; the planning production is optimized based on the ore-distributing raw ore property and the equipment inspection maintenance plan, the production is optimized towards the productivity consumption balance target, the equipment process preparation and the station time plan are formed, and the planning production is estimated; the yield statistics is based on the daily formation index statistics of actual production conditions, the steady state and trend of the productivity are estimated, the steady state and trend of the productivity are gradually fed back to a weekly plan and a monthly plan, and monthly production operation accounting is finally formed;
And (3) index statistics: according to the planned production scheduling indexes and the actual production completion conditions, statistics, comparison and analysis of various production indexes are realized, and the execution progress, capacity fluctuation and completion quality of the production plan are evaluated. Comprising the following steps: and (5) operation index statistics and index analysis and evaluation.
The production scheduling is characterized in that on the basis of planning and scheduling production, a mineral processing production planning target is converted into mineral processing production process requirements and actual production operation tasks to be decomposed into production operation areas, specific starting and time planning and operation instructions are formed and are issued to production equipment, and the operation scheduling is comprehensively optimized according to the capacity demand of bottleneck working procedures and the capacity allocation conditions, equipment maintenance and energy consumption conditions of other working procedures, so that balance of capacity, quality and consumption is realized;
the production schedule includes:
3.1, planning and scheduling management: and (3) carrying out process decomposition on the daily schedule according to the process requirements of each process, and determining various material input and output plans related to each process. And according to factors such as the configuration condition of the production capacity of each process equipment, the running state of the equipment, the energy consumption cost and the like, the number of equipment opening and the corresponding time of the equipment are comprehensively calculated, and the balance of the productivity efficiency and the consumption cost is optimized. The optimal scheduling of the mineral processing procedure is based on a planning target, a multi-target optimal scheduling model is established by combining various factors of quality, energy consumption and equipment, and different optimization strategies are used for carrying out target solving. The scheduling strategy adopts surplus energy production working procedures to optimize energy consumption cost as a target, and bottleneck working procedures to optimize operation scheduling with equipment operation load and comprehensive station time optimization as targets.
3.2, job execution management: and issuing equipment control instructions and process control parameters to an equipment control system according to the production scheduling plans of each process. Comprising the following steps: and the equipment instruction issuing and controlling, production monitoring and abnormal alarming, production process recording and process statistical analysis module.
The quality management system realizes the online collection, storage and sharing of quality inspection test data, realizes the non-landing of the quality data of the factory selection, and provides a reliable data source for an upper business system; comprising the following steps: quality process management, assay management, quality data analysis.
4.1, quality process management: real-time monitoring data of online quality detection instruments such as a particle analyzer and a grade analyzer are collected in real time, and process technical indexes of the production process are analyzed, and the trend of index control is oriented. By summarizing the data (overflow granularity, mixed magnetic concentrate pulp grade and the like) collected on line and manually inputting the data, various indexes and influence factors in the production process are analyzed, the influence degree of various influence factors is quantified, and timely early warning is carried out on the data exceeding standard and abnormal trend. Comprising the following steps: and (5) analyzing local process quality and global process quality.
4.2, assay data management: and (3) performing test data management on important nodes in the production process, establishing various attribute information aiming at different sample types, and realizing real-time transmission of test data by the attribute information established by the sampling department and the data butt joint of the test data of the test department, so that each department can master and transmit the test data more real-time and accurate. Comprising the following steps: assay data acquisition, assay result inquiry, assay data analysis.
4.3, analyzing quality data: the data is not landed through automatic acquisition and online transmission of the quality data, deviation and artificial modification in the data transmission process are prevented, and the stability of the quality data is ensured. Based on the data, a data analysis function is provided, quality management staff and production organization management staff can conduct quality data correlation analysis through a quality analysis tool, and a source of quality problems is found. And automatically outputting a quality check result through quality data statistics. Comprising the following steps: and (5) checking, analyzing and managing and synthesizing a quality report.
The process tracking realizes energy consumption tracking, production plan tracking and quality tracking by collecting energy consumption data, production index data and quality index data of the edge computing system, realizes material consumption tracking and on-site worker tracking by data generated by the material management subsystem and the production scheduling and operation execution subsystem, checks production plan and actual completion conditions in real time, and tracks quality index information, energy consumption information and material consumption information in real time; comprising the following steps: production plan tracking, quality tracking, energy consumption tracking, material consumption tracking, production worker tracking and mine warehouse storage tracking modules.
5.1, production plan tracking: and comparing the production month plan with the production quarter plan according to the data information fed back by the on-site production, so that a manager can know the production progress state in real time.
5.2, quality tracking: and the production quality information of each working procedure operation area fed back by on-site production is displayed in real time, so that a manager can know the quality state of each working procedure in real time.
5.3, energy consumption tracking: and the production energy consumption information of each working procedure operation area fed back by the on-site production is displayed in real time, so that a manager can know the energy consumption state of each working procedure in real time.
5.4, tracking material consumption: and the material consumption information of each working procedure operation area fed back by the on-site production is displayed in real time, so that a manager can know the material consumption state of each working procedure in real time.
5.5, production worker tracking: the electronic operation board for the workers is designed, and the position information of the workers is displayed on an application system in real time, so that management staff can know the position information of each worker in real time.
5.6, storage and tracking of ore bins: and inputting car dumper information during crushing and unloading, and displaying dynamic data including relevant time and space dimension information such as grade, ferrous index, ore discharging position and the like in ore bin storage according to ore deceleration in the ore bin by the system.
The material consumption management is used for carrying out statistical analysis on the purchasing, inventory and receiving processes of materials such as bulk materials, production auxiliary materials, energy sources and the like, and the energy consumption, the material consumption, the yield and the cost; comprising the following steps: and the online library management, yield management, cost analysis and material balance management module.
6.1, managing a line side library: and establishing an operation area side-line library management module, realizing the business of warehouse warehousing, material taking, inventory checking, inventory accounting and the like, forming corresponding operation and inventory records, and providing data support for statistical analysis and consumption accounting. Comprising the following steps: material warehouse-in management, material warehouse-out management and material balance management.
6.2, yield management: the method comprises the steps of each working procedure output and concentrate output in each working area, and the statistical analysis of the output of the whole process is realized. Including concentrate yield management, crushing yield management, grinding yield management, and flotation yield management.
6.3, cost analysis: the method comprises the steps of raw ore consumption statistics, energy consumption statistics, material balance, warehouse entry and exit conditions and other data of each process, making corresponding chart analysis, and displaying cost related data to a user according to classification such as month, material category, energy medium category and the like. Comprising the following steps: material consumption statistical analysis, yield statistical analysis and energy consumption statistical analysis.
And 6.4, material balance management: the material balance was evaluated from the metal recovery rate of the whole plant to the actual recovery rate of each process.
The function module for electronically displaying the operation instruction of the factory selection performs unified management and centralized control on the operation instruction of each process of the factory selection, and the operation instruction is accurately issued to the operation terminal; comprising the following steps: site management, instruction document management, instruction distribution management and instruction checking,
7.1, site management: the method comprises the steps of defining positions to be displayed by operation instruction books of all working procedure operation areas of a factory, wherein the positions comprise functions of adding sites, editing sites, deleting sites, inquiring sites and the like. The number of sites can be expanded according to actual needs. The upper level attribute of the site is a job area, and the upper level attribute of the job area is a process.
7.2, managing the instruction book file: after each operation instruction is ready to be started, the operation instruction needs to go through a management business process, including the definition, uploading, auditing and publishing of the instruction.
7.3, instruction assignment management: the operation instruction book seen by each process site of the factory is different, the process manager distributes the operation instruction book to the site defined by each process operation area, and one site can bind a plurality of operation instruction books. The record operation instruction book distributes records, so that the later inquiry is facilitated.
7.4, checking the instruction book: when a field worker performs a certain procedure operation, clicking a work instruction checking button at a station terminal of a station to check the content of the instruction, or starting up to directly switch a work instruction display interface to guide the field production operation. Recording the operation instruction book to check the record, and facilitating the post statistics and evaluation of the operation difficulty and the instruction effect of each working procedure.
The production cockpit is used as a comprehensive data visualization system of an intelligent factory, and covers the visual display of statistical management data and execution process data of businesses, and the visual business construction of the multi-element data from an industrial interconnection platform is realized in a graphical configuration mode according to business scene requirements of a remote control center, an operation area operation room and key procedures, so that personalized display requirements are met, and the factory selection is supported to realize the production management transparency and business targets of an enterprise management cockpit, thereby ensuring the safety, the continuity and the stability in the production process.
The index data management is oriented to the whole ore dressing production flow, a multi-dimensional index system oriented to productivity, equipment, cost, quality and personnel is established from an ore dressing inlet to the output of the refined tailings after each production process, the index data management covers the ore dressing technical economic index and the ore dressing production process index related to the integrated management of the mining and selecting, the correlation and the gradual decomposition among the indexes are formed, the calculation and statistics methods and the direct data sources of various indexes are clarified, and the automatic calculation and gradual summarization of the indexes can be realized according to the acquisition of the real-time process data of the system. Based on the index system, the calculation, aggregation and statistics of indexes at all levels are realized, various personalized statistical forms and analysis results are output, and the personalized statistical forms and analysis results are actively and timely pushed to different analysis managers through a theme subscription mode. And by utilizing a big data analysis technology, index association analysis and data mining are realized, and support is provided for continuous improvement of production management.
8.1, index system management: and establishing a multi-dimensional index system oriented to the topics of efficiency, quality, consumption, personnel and the like, realizing the gradual decomposition of the comprehensive index, and defining the calculation and statistics methods of index data of each level. The index system needs to ensure the integrity of the index system and the accuracy of the association relation between indexes according to the operation statistics index of the company and the control index requirement of the factory production process.
8.2, statistical report management: based on the establishment of the comprehensive index system, according to an index data source, a calculation formula and an index convergence statistical method, automatically calculating index values in a statistical period to form an index data set. According to the personalized requirements of enterprises, a report template of various statistical topics is defined, the style, the printing specification and the like of the report are defined, the association between the report template and dynamic data is realized through screening and inquiring of the combination condition of the system, and a corresponding report is automatically generated according to the template definition, so that online printing and export are supported. For the report of the homologous data, the dynamic adjustment of the report style based on the visual component is supported, so that the reusability of the report template is improved. And establishing a factory-level report library according to the statistical theme, supporting the automatic archiving of historical daily, monthly and annual reports, forming a multi-level classification organization of process equipment level, operation area level and factory level, and supporting the dynamic updating of the report library. And supporting report subscription facing report subjects, configuring report display style, statistical period and pushing conditions, and realizing personalized automatic report pushing.
8.3, index analysis management: and by combining a comprehensive index system, analyzing mass production process data by utilizing a big data analysis technology, analyzing potential association relations among indexes, evaluating the degree of mutual influence among indexes, and providing an analysis decision means for tracing and continuously improving abnormal indexes. The process indexes and control parameters of the factory production process are numerous, the association relationship between the process indexes and the control parameters is complex, the interaction mechanism of the indexes is unclear, and a model needs to be built for analysis. The relevance of the process indexes refers to the mutual influence relationship and influence degree of the process indexes, and the relevance of the process indexes is analyzed to analyze the influence relationship and the influence strength. The main index association analysis methods comprise causal relation matrix (C & E matrix), failure mode and result analysis (FEMA), regression analysis, orthogonal analysis and the like.
The main analysis process includes:
counting the distribution condition of the index, determining the index value and the confidence interval,
a 5M1E method is adopted to determine the potential influence factor range of the index,
combining the index potential influencing factors, determining key influencing factors by utilizing a causal relation matrix, a failure mode and result analysis,
on the basis of key factors, analysis of significance level of index influence is performed by using analysis of variance, regression and orthogonal analysis.
The basic management, supporting the basic service of system operation, forming personalized function requirements for the intelligent collaborative production management and control system based on the whole basic service provided by the cloud platform, and realizing flexible configuration of user role management, resource authority management, message management and log management; the system realizes the basic service function of supporting system operation, forms personalized function requirements aiming at an intelligent collaborative production management and control system based on the whole basic service provided by the cloud platform, and realizes flexible configuration of user role management, resource authority management, message management and log management. The system comprises a user role management module, a resource authority management module, a message notification management module and a system log management module.
9.1, a user role management module: based on a cloud platform unified service architecture, platform users and role management services are called, user management in independent tenants of factory selection is achieved, and corresponding user roles are dynamically established according to set operation authorities of all functional modules of the system and actual service positions of the factory selection. The roles and the users can be mapped, one user can belong to one or a plurality of roles, hierarchical authorization under a unified identity authentication mechanism is supported, and a role authorization mode of a user group is supported.
9.2, resource authority management module: the system is used for managing user resources of the whole system, and the resources are various, such as user interface resources, user operation resources, derived resources and the like, and each resource has a certain authority which is composed of an instance of a specific resource and a behavior of the instance. For a particular resource, there are: the rights of adding, deleting, modifying, checking, confirming, viewing, signing and the like can be classified and arranged for each user-oriented function in the system through system resource management, a resource table is generated, and a unique identifier is allocated for each resource.
On the basis, binding of resource rights is performed based on roles. The resource specified by the grant also includes all sub-resources under the resource unless its sub-resources have a separate grant definition to cover it. The authorization mode supports permission authorization and refusal authorization, and the permission authorization allows authorization of a certain authority of a designated role, namely, the permission authorization sets a behavior of a certain role on a certain resource; the refusal of the authority refuses the authority of a specific character, namely, the authority refuses the action of the character on a resource.
9.3, message notification management module: the message communication mechanism based on various production events is one of important functions of the system, and specifically comprises:
9.3.1, message subscription: according to different user roles, message subscription based on different topics of production notification, abnormality, quality and the like can be realized;
9.3.2, message publishing: the message bus classifies messages to be published according to topics, and publishes the messages based on a message subscription list, wherein the publishing modes comprise WeChat, short message, mail, mobile terminal APP, PC client, large screen billboard and the like;
9.3.3, message time window timeliness: and starting timing after the message bus receives the message, enabling the message to enter a time window, and carrying out processes such as priority improvement, persistent storage and the like on the message exceeding timeliness through timing scanning.
9.4, a system log management module: key operation information of all login personnel accessing the system and system update information are recorded, such as adding, modifying, deleting records and system update time, updaters, updated versions and the like. For all data updated by the system, a standard system log is kept, information such as who changes the data from what to what, date and time of data change and the like is recorded, and all actions of attempting to enter the application system are tracked, whether login is successful or failed. The system log has an archiving mechanism, and can access the archiving record of the log when needed, and the archiving log is convenient for inquiring and generating a report.
The system log inquiry according to various conditions such as personnel, functional operation, time and the like is provided, and classification, screening and maximum efficiency storage of different log formats are supported. The log supports log management functions such as automatic export, import, deletion, backup, recovery, etc. The method and the system provide various and flexible log information inquiry, simultaneously support related inquiry of different logs according to the conditions set by the user, and help an administrator to realize more comprehensive and deep analysis of the events.
The system integration, the management and control system is a system facing the production site, and is also an information transmission system for connecting the operation layer and the site control layer, and the system and the upper business system and the bottom edge computing system form an enterprise nervous system, so that instructions of business planning are transmitted to the production site, and information of the production site is timely collected, uploaded and processed.
The management and control system login realizes integration with the unified identity authentication and single sign-on system through a company internet platform.
The management and control system needs to integrate data with a plurality of external systems, and the data integration modes comprise a plurality of modes of intermediate file conversion, data replication, data aggregation and API interfaces:
10.1 integration with SAP-ERP System: the integrated main content includes production plan information, material purchase information, quality information and the like. The integration mode can adopt an API interface, intermediate file conversion and the like.
10.2 integration with edge computing System: the integrated main contents include on-site production control parameters, quality detection information, equipment running state and other edge calculation information. The integration mode is based on an edge cloud cooperative mechanism and follows a company industrial interconnection platform data transmission protocol.
10.3 integration with EAM system: the integrated main contents include equipment account information, equipment maintenance plan information, equipment technical precision information and the like. The integration mode can adopt an API interface, intermediate file conversion and the like.
10.4 integration with Main data System: the integrated main content comprises personnel basic information, product basic information, material basic information and the like. The integration mode can adopt an API interface, intermediate file conversion and the like.
10.5 integration with PI system: the integrated main content includes information such as on-site production technical indexes, equipment running states and the like. The integration mode can adopt data replication, data aggregation and the like.
10.6, integration with energy management system: the integrated main content includes information such as energy consumption data, energy early warning data, energy statistics data and the like. The integration mode can adopt an API interface, intermediate file conversion and the like.
The invention relates to an intelligent factory selection three-dimensional simulation system module, which comprises: the system comprises a basic function module, a solid modeling and visualization application module; based on the combination of the mineral separation equipment of the entity mineral separation plant and the production operation data of the plant infrastructure and the three-dimensional simulation system, the three-dimensional virtual mineral separation plant is presented, all units of the entity plant, the equipment operation information, the production process information, the image information and the three-dimensional model are linked, the dynamic simulation display is carried out on the three-dimensional model, the visual management and the omnibearing three-dimensional management and control of the production process are realized, the centralized optimization command and dispatch are realized,
The basic functions include: user rights management, providing functions of user, role and rights management; scene management, 3D scene asset resources, management attribute modification of the scene of the physical place; model management, supporting built-in and externally imported model libraries; the data interface management adopts a universal data interface, is easy to integrate and expand, integrates various file formats, and meets the requirement of subsequent expansion of the system; the data display is used for monitoring the data collected by the entity concentrating plant in real time, restoring the running state/action of the field equipment and intuitively grasping the comprehensive running condition of the production/equipment; the video interface is in butt joint with the corresponding camera interface, and the real-time video picture is called by clicking the camera in the 3D scene; the roaming inspection, virtually simulating patrol concentrating mills through set routes in different view angles, and restoring all the scenes in the buildings and the factories one by one as if the scenes are on the scene;
the entity modeling is divided into infrastructure modeling and equipment personnel modeling, wherein the infrastructure modeling comprises factory layout, buildings (factory buildings), crushing stations, belt galleries, intermediate ore bins and other infrastructures; modeling equipment personnel, and accurately representing the working states and dynamic parameters of the personnel and the equipment;
The visual application comprises: the dynamic data display module is used for sharing production data, equipment data, safety data and management data in the mineral processing system, collecting all real-time information collected and selected on a unified platform, and displaying the real-time information on a three-dimensional graph intuitively and dynamically; the whole 3D virtual mining area can be seen from the air through a bird's eye view and displayed in a 3D electronic sand table form; in order to view a specific working section or equipment in a short distance, certain key equipment or production flow which can enter a roaming mode can be dynamically displayed through animation; the abnormal information linkage module can share fault information and alarm information of each unit and module for ore dressing, automatically respond, draw to fault and alarm occurrence places, directly check information details and corresponding machine stations and process details, and call peripheral video monitoring to check site conditions;
the video system linkage module comprises a video monitoring unit and a three-dimensional simulation unit, wherein all cameras in the video monitoring unit are displayed on the three-dimensional simulation unit in the form of icons, and corresponding video information can be checked.
Claims (8)
1. An wisdom mine beneficiation system, its characterized in that: the intelligent ore dressing production control system comprises a mine cloud platform, an ore dressing production command remote control center, an edge optimization control system and an ore dressing intelligent production control system; the mine cloud platform is respectively connected with the intelligent mine mineral separation production control system and the mineral separation production command remote control center in a communication manner;
the mine cloud platform is used for docking industrial equipment and facilities, comprehensively connecting machines, data and systems with people, and is an operating system of the intelligent production management and control system for mineral separation;
the remote control center for mineral processing production command is a vertical management system of the mineral processing production command center to a machine and a post, displays index information of mineral processing production flow in real time, provides technical support for mineral processing production decision, displays energy consumption statistics and analysis in real time, and finishes the progress of yield plan, causes of production problems, finishes and trends mineral processing production cost and mainly comprises the cost, realizes remote start and stop of equipment and production process adjustment through station operation, and monitors production process change in real time;
the edge optimization control system is oriented to production processes, a process optimization model is established by utilizing cloud big data analysis and edge calculation technology, a process optimization and adjustment strategy is output, and cooperative optimization in the processes and among the processes is realized through integration with the control system, so that support is provided for fine production management and control;
The intelligent production management and control system for mineral separation uses communication and information technology and artificial intelligence technology to establish an intelligent manufacturing system architecture and implement of an enterprise, realizes accurate sensing and accurate control of the whole production process, forms a cooperative management and control system based on standardization, lean, digitization, automation and intellectualization, and realizes the aim of improving production efficiency of the enterprise.
2. The intelligent mine mining system according to claim 1, wherein the mine cloud platform comprises a mine industrial internet platform and a big data platform, the mine industrial internet platform is a carrier for realizing intelligent factories and intelligent mines, the edge layer of the intelligent mine internet platform is in butt joint with industrial equipment and facilities, the platform layer combines cloud computing, big data technology and actual experience of industrial production to form industrial data basic analysis capability, and a cloud open shared development environment is constructed; the industrial internet APP of the application layer uniformly manages and controls the upper application system and provides consistent external service; the big data platform provides strong real-time stream processing capability and offline batch processing capability, and can conveniently process stream processing of data. The method has the advantages that the method provides strong data analysis and mining capability, can quickly perform visualization classification of data under a large data scale, performs deep mining on the data through the strong machine learning capability provided by a large data platform, builds a unified data storage, collection, analysis and management environment, and continuously integrates and distributes the environment, and realizes unified data storage, data collection, data analysis and management.
3. An intelligent mine beneficiation system as claimed in claim 1, wherein: the edge optimization control system consists of three modules, namely an edge integration module, an edge calculation module and a Bian Yun cooperative module,
the edge integration module is used for upwards butting an enterprise application system, downwards butting specific hardware equipment of a factory, enabling an upper layer application to realize the functions of monitoring, controlling and operating the bottom layer hardware equipment by calling a unified interface, automatically analyzing different communication protocols of different hardware equipment, and automatically converting binary data messages and available data with practical significance;
the edge computing module deploys an edge computing resource environment facing edge computing nodes, provides computing capability, realizes edge infrastructure management, provides reliable and efficient cloud side information synchronization, realizes persistence of local metadata, abstracts physical equipment, generates a mapping of equipment states at a cloud end, subscribes to equipment data, builds edge application with a micro-service architecture, and deploys according to a scene of an intelligent task;
the Bian Yun cooperation module is oriented to industrial intelligent control scenes and comprises two major categories of equipment optimization and process optimization, wherein the equipment optimization Bian Yun is cooperated, the health state and performance of the equipment are optimized by intelligent analysis on the acquired equipment data, and the process optimization Bian Yun is cooperated: mainly applied at the level of a process section or a production line, and flexibly deployed and adjusted according to the needs.
4. An intelligent mine beneficiation system as claimed in claim 1, wherein: the intelligent mineral separation production management and control system comprises an intelligent cooperative mineral separation production management and control system, a mineral separation energy management system, a mineral separation safety management system and a three-dimensional simulation system of an intelligent mineral separation plant.
5. An intelligent mine beneficiation system as claimed in claim 4, wherein: intelligent collaborative ore dressing production management and control system, include: the system comprises a factory modeling module, a plan management module, a production scheduling module, a quality management module, a process tracking module, a material consumption management module, an operation guidance management module, a production cockpit module, an index data management module, a basic management module and a system integration module;
the factory modeling module takes the ore dressing process as a main line, respectively constructs a product material model, an organization structure model and a production process model, realizes the digital description of the core production elements of what is produced, what production resources are available and how to produce, and further lays a foundation for the realization of other business functions;
the plan management module is used for decomposing a month plan according to a year plan and a quarter plan issued by a company, and decomposing a week plan and a day plan according to mining and ore allocation information; the planning production is optimized based on the ore-distributing raw ore property and the equipment inspection maintenance plan, the production is optimized towards the productivity consumption balance target, the equipment process preparation and the station time plan are formed, and the planning production is estimated; the yield statistics is based on the daily formation index statistics of actual production conditions, the steady state and trend of the productivity are estimated, the steady state and trend of the productivity are gradually fed back to a weekly plan and a monthly plan, and monthly production operation accounting is finally formed;
The production scheduling module converts the mineral processing production plan target into mineral processing production process requirements and actual production operation tasks to be decomposed into production operation areas on the basis of planning production, forms specific starting, station time planning and operation instructions to be issued to production equipment, and comprehensively optimizes operation scheduling according to capacity allocation conditions of bottleneck working procedures and other working procedures, equipment maintenance and energy consumption conditions, and realizes balance of capacity, quality and consumption;
the quality management module comprises quality inspection test data and online quality detection data, is an important basis for evaluating the production condition of a factory and guiding the production of the factory, and the quality management system realizes online acquisition, storage and sharing of the quality inspection test data, realizes non-landing of the factory quality data and provides a reliable data source for an upper business system;
the process tracking module is used for realizing energy consumption tracking, production plan tracking and quality tracking by collecting energy consumption data, production index data and quality index data of the edge computing system, realizing material consumption tracking and on-site worker tracking by data generated by the material management subsystem and the production scheduling and operation execution subsystem, checking production plan and actual completion conditions in real time and tracking quality index information, energy consumption information and material consumption information in real time;
The material consumption management module performs statistical analysis on the purchasing, inventory and receiving processes of materials such as bulk materials, production auxiliary materials, energy sources and the like and on the energy consumption, the material consumption, the yield and the cost;
the operation guidance management module is used for carrying out unified management and centralized control on the operation guidance of each procedure of the factory selection, and accurately issuing the operation guidance to the operation terminal;
the production cockpit module is used as a comprehensive data visualization system of an intelligent factory, and covers the visual display of statistical management data and execution process data of businesses, and the visualization of the multi-element data from an industrial interconnection platform is realized rapidly in a graphical configuration mode according to business scene requirements, so that the factory selection realizes production management transparency and enterprise management cockpit;
the index data management module is oriented to the whole ore dressing production flow, establishes a multidimensional index system, covers the ore dressing technical economic index and the ore dressing production process index related to the integrated management of the ore dressing, forms the correlation and the gradual decomposition among the indexes, defines the calculation and statistics methods of various indexes and direct data sources, can realize the automatic calculation and gradual summarization of the indexes according to the acquisition of the real-time process data of the system, realizes the calculation, the convergence and the statistics of various levels of indexes on the basis of the establishment of the index system, outputs various personalized statistical forms and analysis results, and realizes the index correlation analysis and the data mining by utilizing the big data analysis technology;
The basic management module supports basic services operated by the system, forms personalized function requirements aiming at an intelligent collaborative production management and control system based on the whole basic services provided by the cloud platform, and realizes flexible configuration of user role management, resource authority management, message management and log management;
the system integration module is a system facing the production field, and the management control system is also an information transmission system for connecting the operation layer and the field control layer, and forms an enterprise nervous system together with an upper business system and a bottom edge computing system, so that instructions of business planning are transmitted to the production field, and information of the production field is timely collected, uploaded and processed.
6. An intelligent mine beneficiation system as claimed in claim 4, wherein: the energy management system comprises: the system comprises an energy instrument foundation management module, an energy instrument state management module, an energy data monitoring module, an energy information early warning module, an energy information prediction module, an energy information statistics module and an energy information analysis module;
the energy instrument foundation management module is used for providing operation for instrument information, counting the energy of the unit where the energy instrument foundation management module is located by each operation area, reporting the counting result to an energy office, integrating the energy and comparing the energy with the total energy data of each production technical department, and judging the energy balance;
The energy instrument state management module is used for limiting and checking the instrument operation state of the operation area of the designated equipment by a manager, and when the instrument fails and has a link problem, alarming prompt of a designated level is carried out according to the specific problem to provide log inquiry of the instrument;
the energy data monitoring module monitors regional energy, monitors the whole of the important energy utilization units at the regional level, firstly provides a factory-level energy monitoring layout diagram, displays the total energy utilization condition of a main operation area included in a factory, and can enter an energy monitoring interface of a corresponding operation area; the operation area level comprises the overall use condition of specific energy, the energy use condition of specific energy utilization equipment, and real-time data monitoring is carried out on the instrument;
the energy information early warning module judges the instantaneous quantity, the cumulative quantity and the threshold value of energy in the production process, and further makes corresponding early warning prompts, wherein the energy information early warning comprises instantaneous quantity early warning and cumulative quantity early warning;
the energy information prediction module realizes characteristic analysis based on historical energy consumption data according to energy consumption information and assists in forming function plan assessment and prediction;
the energy information statistics module performs energy statistics by taking an operation area as a partition limit and a team as a recording unit, comprises various dosage information and product yield information of corresponding time periods, forms a team energy report of a daily operation area, and the energy management center calculates energy information of the whole plant according to the daily energy report of each operation area;
The energy information analysis comprises energy balance analysis, energy behavior analysis and energy comparison analysis; the energy balance analysis is used for carrying out classification statistics on the supply quantity, conversion and consumption of energy in each operation area, and analyzing whether the net inflow and consumption of energy are consistent or not as a whole, wherein the difference is an instrument statistical error or an energy omission item; analyzing the process energy supply amount and the equipment energy consumption amount before and after the use of the energy from the process, and searching the unbalanced energy consumption reason from the process energy source; the energy behavior analysis is carried out, corresponding energy consumption guidance is given by counting the energy use time period, the energy consumption process and the use equipment of the factory selection and combining the equipment station time and the production process requirements of different processes, and an enterprise energy consumption behavior model is established so as to simulate the energy cost of the enterprise under different energy consumption behaviors; and (3) energy comparison analysis, namely, comparing the operation area and the energy utilization equipment according to items, including ring ratio, same ratio, historical best level and average level, and comparing the historical best level and average level with the standard in the industry, and finding out influencing factors of energy consumption change.
7. An intelligent mine beneficiation system as claimed in claim 4, wherein: the safety management system module comprises: the system comprises a potential safety hazard management module, a staff safety training module, a staff safety assessment module and a safety key person electronic file module; the method is characterized in that big data analysis is used as a core operation platform, safety problems focused on by concentrating mills, including potential safety hazards, employee safety training and safety assessment are collected, stored and analyzed, a safety problem database of an enterprise is established, full-flow safety informatization and visual management are realized, safety responsibility is realized, safety executive force is enhanced, and scientific basis is provided for safety decision of the enterprise;
The potential safety hazard management module is used for: the static potential safety hazard is input into the system, and the repetitive static potential hazard is given to
Prompting;
the staff safety training module comprises national laws, regulations, standards and specifications related to safety production, basic knowledge, methods and technologies for safety production management, major accident prevention, emergency rescue, typical accident cases and the like;
the staff safety assessment module is used for checking and finding that the staff has dynamic problem reasons when the staff has first dynamic safety problems including illegal or nonstandard operation, analyzing the reasons of the dynamic problems by the staff, implementing safety training in a certain class, and inputting a training track and assessment conditions into the system after the training is finished to form staff safety assessment records;
the security key person electronic archive module is used for searching the security check record, and for staff with secondary and above same-class dynamic problems, the security key person electronic archive module is listed in the security key person electronic archive, and the electronic archive content can comprise information such as key person names, security problem descriptions, problem occurrence times and the like.
8. An intelligent mine beneficiation system as claimed in claim 4, wherein: the intelligent factory selection three-dimensional simulation system module comprises: the system comprises a basic function module, a solid modeling module and a visualization application module; based on the combination of the mineral separation equipment of the entity mineral separation plant and the production operation data of the plant infrastructure and the three-dimensional simulation system, the three-dimensional virtual mineral separation plant is presented, all units of the entity plant, the equipment operation information, the production process information, the image information and the three-dimensional model are linked, the dynamic simulation display is carried out on the three-dimensional model, the visual management and the omnibearing three-dimensional management and control of the production process are realized, the centralized optimization command and dispatch are realized,
The basic functional module comprises: user rights management, providing functions of user, role and rights management; scene management, 3D scene asset resources, management attribute modification of the scene of the physical place; model management, supporting built-in and externally imported model libraries; the data interface management adopts a universal data interface, is easy to integrate and expand, integrates various file formats, and meets the requirement of subsequent expansion of the system; the data display is used for monitoring the data collected by the entity concentrating plant in real time, restoring the running state/action of the field equipment and intuitively grasping the comprehensive running condition of the production/equipment; the video interface is in butt joint with the corresponding camera interface, and the real-time video picture is called by clicking the camera in the 3D scene; the roaming inspection, virtually simulating patrol concentrating mills through set routes in different view angles, and restoring all the scenes in the buildings and the factories one by one as if the scenes are on the scene;
the entity modeling module is divided into two modules, namely an infrastructure modeling module and an equipment personnel modeling module, wherein the infrastructure modeling module comprises a factory layout, a building (factory building), a crushing station, a belt corridor, an intermediate ore bin and other infrastructures; modeling equipment personnel, and accurately representing the working states and dynamic parameters of the personnel and the equipment;
The visual application module comprises: the dynamic data display module is used for sharing production data, equipment data, safety data and management data in the mineral processing system, collecting all real-time information collected and selected on a unified platform, and displaying the real-time information on a three-dimensional graph intuitively and dynamically; the whole 3D virtual mining area can be seen from the air through a bird's eye view and displayed in a 3D electronic sand table form; in order to view a specific working section or equipment in a short distance, certain key equipment or production flow which can enter a roaming mode can be dynamically displayed through animation; the abnormal information linkage module can share fault information and alarm information of each unit and module for ore dressing, automatically respond, draw to fault and alarm occurrence places, directly check information details and corresponding machine stations and process details, and call peripheral video monitoring to check site conditions;
the video system linkage module comprises a video monitoring unit and a three-dimensional simulation unit, wherein all cameras in the video monitoring unit are displayed on the three-dimensional simulation unit in the form of icons, and corresponding video information can be checked.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117787880A (en) * | 2023-11-13 | 2024-03-29 | 深圳赛瀚德技术有限公司 | Industrial digital management system and method based on cloud edge cooperation |
| CN118195168A (en) * | 2024-04-11 | 2024-06-14 | 广西拓普塞恩节能科技有限公司 | Intelligent ore blending system and method for alumina plant and mine |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117787880A (en) * | 2023-11-13 | 2024-03-29 | 深圳赛瀚德技术有限公司 | Industrial digital management system and method based on cloud edge cooperation |
| CN118195168A (en) * | 2024-04-11 | 2024-06-14 | 广西拓普塞恩节能科技有限公司 | Intelligent ore blending system and method for alumina plant and mine |
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