CN117350492A - MES operation management system capable of intelligently controlling comparison historical data - Google Patents

Abstract

The invention discloses an MES operation management system for intelligently regulating and controlling historical data, which belongs to the field of intelligent regulation and control of the historical data and comprises an order management module, a resource scheduling module, a process monitoring module, a data acquisition and analysis module, an inventory management module, an energy management module and a report visualization module; the order management module is used for creating, tracking and managing production orders; the resource scheduling module is responsible for knowing orders to be produced and priorities of the orders, and reasonably distributing production equipment and human resources; the process monitoring module collects real-time data of production equipment and production process; the data acquisition and analysis module uses the historical real-time data to identify potential trends and problems; the energy management module is responsible for helping the resource scheduling module to make more sustainable resource allocation decisions; the report visualization module provides a comprehensive view of the system, and the manager and operators monitor the production performance, quality and efficiency of the system, providing comprehensive insight.

Description

MES operation management system capable of intelligently controlling comparison historical data

Technical Field

The invention relates to the field of intelligent regulation of historical data, in particular to an MES operation management system for intelligent regulation of comparison historical data.

Background

The MES operation management system with intelligent historical data regulation is produced by the manufacturing industry in the digital transformation of wave tide. It stems from the need in the manufacturing industry for a more efficient, flexible and sustainable production process. In the past, traditional MES systems were mainly used for data collection and reporting, but with advances in information technology, such as cloud computing, big data analysis, internet of things (IoT) and Artificial Intelligence (AI), manufacturers began to demand more. These techniques enable MES systems to monitor equipment in real time, analyze mass data, predict demand, optimize resource allocation, and support intelligent decisions. In addition, concerns about environmental sustainability and energy efficiency have driven integration of energy management and environmental monitoring functions. Thus, MES systems intelligently controlled by historical data represent a key step in the digital transformation of manufacturing industries, aiming at improving competitiveness, reducing cost and achieving more sustainable manufacturing.

Early MES system data is often in isolation and difficult to integrate with other enterprise systems, resulting in intermittent information flow. Traditional MES lacks intelligent decision support, and cannot adapt to rapidly changing market demands and production changes. The limited visual function, difficulty in providing real-time, interactive data presentation, limits decision making and problem diagnosis. Historical data analysis focuses primarily on past performance, rather than predicting and optimizing based on data. Manufacturing concerns over energy efficiency and environmental impact have increased, but early MES systems have failed to adequately integrate energy management and environmental monitoring. Some early MES systems were relatively complex to deploy and maintain, requiring high costs and resources.

Disclosure of Invention

The invention aims to provide an MES operation management system for intelligently regulating and controlling historical data, so as to solve the problems set forth in the background art:

early MES system data is often in isolation and difficult to integrate with other enterprise systems, resulting in intermittent information flow. Traditional MES lacks intelligent decision support, and cannot adapt to rapidly changing market demands and production changes. The limited visual function, difficulty in providing real-time, interactive data presentation, limits decision making and problem diagnosis. Historical data analysis focuses primarily on past performance, rather than predicting and optimizing based on data. Manufacturing concerns over energy efficiency and environmental impact have increased, but early MES systems have failed to adequately integrate energy management and environmental monitoring. Some early MES systems were relatively complex to deploy and maintain, requiring high costs and resources.

The technical scheme is as follows: the MES operation management system for intelligently controlling comparison historical data comprises an order management module, a resource scheduling module, a process monitoring module, a data acquisition and analysis module, an inventory management module, an energy management module and a report visualization module;

the order management module is used for creating, tracking and managing production orders, and sequencing and distributing resources according to emergency factors;

The resource scheduling module is responsible for knowing the orders to be produced and the priority of the orders and reasonably distributing production equipment and human resources;

the resource scheduling module knows the state and the availability of the production equipment in real time and makes scheduling decisions;

the process monitoring module collects real-time data of the production equipment and the production process;

the real-time data is provided for the data acquisition and analysis module to use;

the data collection and analysis module uses the real-time data historically to identify potential trends and problems;

the data acquisition and analysis module compares the current real-time data with the past real-time data to find out the abnormality and trend change in the MES operation management system intelligently regulated by the comparison historical data;

the energy management module is responsible for knowing the energy consumption condition of the production equipment and helping the resource scheduling module to make more sustainable resource allocation decisions;

the report visualization module provides a comprehensive view for the MES operation management system intelligently controlled by the comparison historical data, and the manager and the operator monitor the production performance, quality and efficiency of the MES operation management system intelligently controlled by the comparison historical data;

The report visualization module provides comprehensive insight based on the data generation of the MES operation management system intelligently controlled by the comparison historical data;

preferably, the order management module allows a user to create a new production order, wherein the production order comprises order numbers, product specifications, quantity and delivery date information, and allows the user to edit detailed information of the existing production order;

the order management module provides real-time state tracking functions of the production order, including state information of received, producing, completed and delivered production order;

the order management module automatically updates the state of the production order and reflects the production progress of the production order;

the order management module allows a user to set priorities for different production orders, provides an automatic priority allocation function, and sorts the production orders according to emergency factors of the production orders;

matching the production order with production equipment and staff to create a production plan, wherein the order management module automatically performs the production order scheduling according to the availability of resources and constraint conditions;

the order management module is used for arranging purchasing and inventory management, and allowing a user to attach and manage files related to the production order, wherein the files comprise a process flow chart, a quality standard and a specification;

The order management module sends automatic notification and reminding to notify staff of change events related to the production order state and delivery date;

the order management module provides reporting and analysis functions related to the production order, including completion of the production order, delay analysis and historical data of the production order;

the order management module records and manages the whole life cycle of the production order, including the operations of creating, changing, canceling and closing the production order;

preferably, the MES operation management system intelligently controlled by comparing historical data according to claim 1, wherein the resource scheduling module schedules the on, off, maintenance and cleaning of the equipment, and the resource scheduling module manages and distributes tasks and work schedules of operators and staff, balances the supply and demands of raw materials and parts, tracks stock levels, makes replenishment plans, and coordinates the delivery and use of materials;

the resource scheduling module uses ant colony algorithm and historical data analysis to formulate an optimal resource allocation strategy in consideration of efficiency, capacity and constraint conditions of resources, and creates and manages a production plan, and generates scheduling according to urgency of the production order, a process route and resource availability;

The resource scheduling module provides real-time monitoring on production resources and the state of the production equipment, and rapidly identifies and solves the problems;

the resource scheduling module monitors and manages the use of energy, tracks the workflow, and collects and reports performance indexes about the resource scheduling and production efficiency;

preferably, the MES operation management system intelligently controlled by comparison history data according to claim 3 is characterized in that the ant colony algorithm is an optimization algorithm based on a behavior model of natural ants searching for food paths, and is used for solving the resource scheduling problem of the MES operation management system intelligently controlled by comparison history data, and the ant path selection probability formula is a core formula in the ant colony algorithm and is used for guiding ants to select paths from one place to another place;

in the resource scheduling problem, the ant path selection probability formula path corresponds to allocation of resources and planning of a workflow;

the ant path selection probability formula is as follows:

t represents the number of iterations, τab represents the concentration of the pheromone on the path at the moment, ηab represents the visibility of ants to the path, the knowledge of decision space is reflected, na is the number of sides taking the point a as the starting point, and alpha and beta represent the importance degree of the pheromone and the visibility respectively;

The ant path selection probability formula is used in combination with the resource scheduling module to guide allocation decision of resources and planning of workflow;

preferably, the MES operation management system intelligently controlled by comparing historical data according to claim 1, wherein the process monitoring module collects real-time data related to the production process, including sensor data including equipment status, production speed, temperature, pressure and humidity, and monitors information including whether the production equipment is started, running status, shutdown reasons and equipment faults in real time;

the process monitoring module provides a visual interface of the production process, visually displays the states of factories and production lines, monitors size, weight and color data related to product quality, detects quality problems and timely takes corrective measures;

the process monitoring module collects and analyzes the data of the yield, the production speed and the downtime of the production efficiency, evaluates the production performance, implements an alarm system and sends an alarm notice to operators when problems and abnormal conditions occur;

the process monitoring module stores historical production data for subsequent analysis, reporting and trend analysis, allows remote monitoring and control of the production equipment, monitors energy consumption of the production equipment and the production line, evaluates energy efficiency, and provides advice to reduce energy cost and environmental impact;

Preferably, the MES operation management system for intelligently controlling comparison historical data according to claim 1, wherein the data acquisition and analysis module stores historical production data for subsequent analysis and comparison, cleans and preprocesses the collected historical production data to remove abnormal values, noise and inconsistencies, and ensures the quality and accuracy of the historical production data;

the data acquisition and analysis module provides a real-time monitoring function, visually displays the current production state and trend of the MES operation management system intelligently controlled by comparing historical data, provides a data analysis tool, supports deep analysis of the production data, and analyzes the production data to evaluate the quality, the production efficiency and the resource utilization rate of the product;

the data acquisition and analysis module utilizes the historical data to perform trend analysis and prediction, analyzes the energy consumption data, automatically generates a customized report and a visual chart, and provides detailed information about the performance of the production process to a management layer and operators;

preferably, the MES operation management system intelligently controlled by comparing historical data according to claim 1, wherein the inventory management module tracks and records the inventory quantity and status of the raw materials, semi-finished products and finished products, provides a visual interface, and displays the current status and position of the inventory;

The inventory management module dynamically and automatically updates inventory data according to the in-out inventory in the production process, sets an inventory warning threshold value, sends out an alarm and automatically triggers a replenishment flow when the inventory level reaches and is lower than a limit, and generates an inventory report, wherein the inventory report comprises inventory turnover rate, inventory value and outdated inventory information, and predicts the automatically triggered replenishment order according to the inventory level and the demand to coordinate with a supplier;

the inventory management module calculates and manages the storage cost, opportunity cost and loss cost of the inventory, supports batch tracing and the inventory adjustment and scrapping treatment, and processes damaged, expired and unqualified inventory;

preferably, the MES operation management system intelligently controlled by comparing historical data according to claim 1, wherein the energy management module collects data of power, natural gas, water and fuel related to energy in the production process, provides real-time energy consumption monitoring, tracks the use condition of the energy, analyzes the energy data to identify potential energy saving opportunities and optimizes the energy use mode;

the energy management module evaluates energy efficiency of different production devices, identifies the production devices with low energy efficiency, provides advice to improve performance, calculates and analyzes cost of energy consumption, collects and monitors energy efficiency indicators, and evaluates energy efficiency of the production process;

The energy management module provides energy-saving suggestions for operators and management layers, generates a report and a visual chart of the energy consumption, visually presents the energy data, and manages and tracks the progress of energy-saving projects;

preferably, an MES operation management system intelligently controlling comparison history data according to claim 1, wherein the report visualization module allows a user to create and customize reports, provide predefined reporting templates, the user quickly generates reports based on the templates,

the report visualization module provides a visualized report editor, a user creates and customizes a report by dragging and dropping elements, charts and data fields, a real-time report is allowed to be generated, the current production state and data of the MES operation management system intelligently controlled by comparing historical data are reflected in real time, and a historical data analysis report is provided;

the report visualization module is compatible with and comprises a PC, a mobile device and a Web browser platform, and allows a user to share the report and distribute the report to a management layer, operators and suppliers;

the report visualization module provides the data visualization tools including data graphs, charts, and dashboards supporting the report review and audit workflow.

Compared with the prior art, the invention has the advantages that:

(1) The invention is based on big data analysis and intelligent algorithm, and the new generation MES system can provide real-time decision support to help enterprises to rapidly cope with production changes and market demands.

(2) The invention is more comprehensive, not only focuses on data acquisition and monitoring, but also has advanced functions such as demand prediction, resource scheduling and energy management.

(3) The invention can be better integrated with other enterprise systems (such as ERP, SCADA, PLC, etc.), ensures seamless circulation of data, and improves data quality and consistency.

(4) The invention has the automation capability, can automatically trigger the workflow, alarm and replenishment order, reduces manual intervention and improves the production efficiency.

(5) The present invention provides more advanced visualization tools, such as real dashboards, interactive reports, and dashboards, that help users understand data more clearly.

(6) The invention uses historical data analysis, and the systems can predict future trend, support the optimization of the production process and improve the efficiency and quality.

(7) The invention integrates the functions of energy management and environmental monitoring, is beneficial to enterprises to realize sustainable production, and reduces energy consumption and environmental impact.

(8) According to the invention, some new systems adopt cloud computing technology, so that the hardware and maintenance cost is reduced, and more flexible deployment options are provided.

Drawings

FIG. 1 is a schematic diagram of the overall system of the present invention.

Detailed Description

Referring to fig. 1, an MES operation management system for intelligently controlling comparison history data includes an order management module, a resource scheduling module, a process monitoring module, a data acquisition and analysis module, an inventory management module, an energy management module, and a report visualization module;

the order management module is used for creating, tracking and managing production orders, and sequencing the orders and distributing resources according to the emergency factors;

specifically, ordering orders and allocating resources includes the following steps;

s1, order receiving: first, the system needs to receive orders from customers, sales teams, or other channels. These orders may be standard orders, emergency orders, or special orders;

s2, order verification: verifying the received order, ensuring that the order information is complete, accurate and in line with enterprise specifications, including checking order quantity, product specifications, price, payment terms, etc.;

s3, order priority distribution: assigning a priority to each order according to a series of criteria and rules, the priority being determinable according to factors such as order type, customer importance, date of delivery, etc.;

S4, generating a production plan: generating a production plan based on the order priorities, including determining production start and end dates, required resources (e.g., machines, personnel, raw materials), and production processes;

s5, resource scheduling: and carrying out resource scheduling according to the production plan. This involves distributing orders to the appropriate production lines, machines and operators, the goal of the resource distribution being to ensure maximum utilization of production capacity while meeting the lead time requirements of the orders;

s6, inventory checking: prior to resource allocation, the system checks the inventory level to determine if there are enough raw materials and parts to complete the order, and if there is insufficient inventory, it may be necessary to trigger a purchase or production restocking;

s7, tracking and monitoring: once the order is allocated resources, the system tracks the production progress of the order, including monitoring production status, production speed, and any potential delays;

s8, optimizing and adjusting: depending on the actual production situation, the system may need to be adjusted and optimized to ensure that orders are delivered on time, which may involve reallocating resources, adjusting production schedules, or coordinating with supply chain partners;

s9, reporting and communicating: the system typically generates reports summarizing key indicators of order management, such as order completion rate, delivery delay, resource utilization, etc., which are available for reference by the management layer and related departments and used for decision-making.

The resource scheduling module is responsible for knowing orders to be produced and priorities of the orders, and reasonably distributing production equipment and human resources;

the resource scheduling module knows the state and the availability of the production equipment in real time and makes scheduling decisions;

the process monitoring module collects real-time data of production equipment and production process;

the real-time data is provided for a data acquisition and analysis module to use;

the data acquisition and analysis module uses the historical real-time data to identify potential trends and problems;

the data acquisition and analysis module compares the current real-time data with the past real-time data to find out the abnormality and trend change in the MES operation management system intelligently regulated by the comparison historical data;

the energy management module is responsible for knowing the energy consumption condition of the production equipment and helping the resource scheduling module to make more sustainable resource allocation decisions;

the report visualization module provides a comprehensive view for an MES operation management system intelligently controlled by comparison historical data, and a manager and an operator monitor the production performance, quality and efficiency of the MES operation management system intelligently controlled by comparison historical data;

the report visualization module provides comprehensive insight based on data generation of an MES operation management system intelligently controlled by comparing historical data.

In this embodiment, the order management module allows the user to create a new production order, which includes order number, product specification, quantity, delivery date information, allowing the user to edit detailed information of the existing production order;

the order management module provides a real-time production order state tracking function, including state information of received, producing, completed and delivered production orders;

the order management module automatically updates the state of the production order and reflects the production progress of the production order;

the order management module allows a user to set priorities for different production orders, provides an automatic priority allocation function, and sorts the production orders according to urgency factors of the production orders;

matching the production order with production equipment and staff to create a production plan, and automatically performing production order scheduling by an order management module according to the availability of resources and constraint conditions;

the order management module is used for arranging purchasing and inventory management, and allowing a user to attach and manage files related to production orders, wherein the files comprise a process flow chart, a quality standard and a specification;

the order management module sends automatic notification and reminding to notify staff about change of production order state and change event of delivery date;

The order management module provides a report and analysis function related to the production order, including completion status of the production order, delay analysis and historical data of the production order;

the order management module records and manages the entire lifecycle of the production order, including creation, modification, cancellation, and shutdown operations of the production order.

Specifically, the state tracking includes the following steps;

s1, order creation: status tracking of production orders begins with creation of orders, which may be submitted by customers, generated by sales teams, or automatically generated from demand planning systems, containing detailed information about products, quantities, delivery dates, and other relevant information;

s2, order distribution: once an order is created, it is assigned to the appropriate production resource, which may involve the intervention of a resource scheduling module to determine which machine, which workstation, or which production team to assign;

s3, production is started: when an order is assigned to a production resource, the production process begins, at which point the order status changes from "waiting for production" or "in-process" to "in-process", meaning that the associated machine and operator have begun manufacturing the product;

s4, production monitoring: the system monitors the production process in real time, which may include monitoring equipment status, production speed, quantity of production, etc., and sensors and meters may provide critical data about the production process;

S5, exception handling: if a problem occurs, such as equipment failure, shortage of raw materials, or process problems, the system will record an anomaly and trigger an associated alarm, and the order status may be updated to "anomaly" or "stall";

s6, production is completed: once all of the products in the order are produced, the order status will be updated to "completed", meaning that the products are ready for delivery to the customer or moved to the next production stage;

s7, quality control: after the production is completed, quality inspection may be required, if the product is qualified, the order status will remain as "completed", if there is a quality problem, reworking or scrapping may be required, and the order status will be updated accordingly;

s8, delivery and delivery: if the order includes a delivery process, once the product is ready, the order status will be updated to "delivered" or "out of stock," and the product will be shipped to the customer;

s9, closing the order: eventually, the order status will update to "closed," indicating that the lifecycle of the order has ended, which typically occurs after successful delivery of the product to the customer;

s10, reporting and notifying in real time: the system may generate real-time reports to provide information about the status of the order and the progress of the production, and may send real-time notifications to the relevant parties via e-mail, text messages, or other communication channels to take timely action.

In the embodiment, the resource scheduling module schedules the on, off, maintenance and cleaning of equipment, and the resource scheduling module manages and distributes tasks and work schedules of operators and staff, balances the supply and the demand of raw materials and parts, tracks the stock level, makes a replenishment schedule and coordinates the delivery and the use of materials;

the resource scheduling module uses ant colony algorithm and historical data analysis to formulate an optimal resource allocation strategy in consideration of the efficiency, capacity and constraint conditions of resources, and creates and manages a production plan to generate a schedule according to the urgency of a production order, a process route and resource availability;

the resource scheduling module provides real-time monitoring on the production resources and the states of production equipment, and rapidly identifies and solves the problems;

the resource scheduling module monitors and manages energy usage, tracks workflow, and collects and reports performance metrics regarding resource scheduling and production efficiency.

In this embodiment, the ant colony algorithm is an optimization algorithm based on a behavior model of searching a food path by natural ants, and is used to solve a resource scheduling problem of an MES operation management system intelligently regulated by comparing historical data, and the ant path selection probability formula is a core formula in the ant colony algorithm and is used to guide ants to select a path from one place to another place;

In the resource scheduling problem, the ant path selection probability formula path corresponds to the allocation of resources and the planning of a workflow;

the ant path selection probability formula is as follows:

t represents the number of iterations, τab represents the concentration of the pheromone on the path at the moment, ηab represents the visibility of ants to the path, the knowledge of decision space is reflected, na is the number of sides taking the point a as the starting point, and alpha and beta represent the importance degree of the pheromone and the visibility respectively;

the ant path selection probability formula is used in combination with the resource scheduling module to guide the allocation decision of resources and the planning of workflow.

In this embodiment, the process monitoring module collects real-time data related to the production process, including sensor data including equipment status, production speed, temperature, pressure, and humidity, and monitors information including whether the production equipment is on, running status, shutdown cause, and equipment failure in real time;

the process monitoring module provides a visual interface of the production process, visually displays the states of factories and production lines, monitors size, weight and color data related to the quality of products, detects quality problems and timely takes corrective measures;

the process monitoring module collects and analyzes the data of the yield, the production speed and the downtime of the production efficiency, evaluates the production performance, implements an alarm system and sends an alarm notice to operators when problems and abnormal conditions occur;

The process monitoring module stores historical production data for subsequent analysis, reporting and trend analysis, allows for remote monitoring and control of production equipment, monitoring of energy consumption of production equipment and production lines, assessment of energy efficiency, and provides advice to reduce energy costs and environmental impact.

In the embodiment, the data acquisition and analysis module stores the historical production data for subsequent analysis and comparison, cleans and preprocesses the acquired historical production data to remove abnormal values, noise and inconsistency, and ensures the quality and accuracy of the historical production data;

the data acquisition and analysis module provides a real-time monitoring function, visually displays the current production state and trend of the MES operation management system intelligently regulated and controlled by comparing historical data, provides a data analysis tool, supports deep analysis of production data, analyzes the production data and evaluates the quality, the production efficiency and the resource utilization rate of the product;

the data acquisition and analysis module utilizes historical data to perform trend analysis and prediction, analyzes the energy consumption data, automatically generates customized reports and visual charts, and provides detailed information about the performance of the production process to management layers and operators.

Specifically, the trend analysis includes the following steps;

S1, data collection: first, the module needs to collect historical data from various data sources, which may include production equipment, sensors, production work orders, inventory records, sales data, quality reports, etc.;

s2, data cleaning and pretreatment: the collected historical data may contain errors, missing values or inconsistent data, and prior to trend analysis, data cleaning and preprocessing is required to ensure the accuracy and integrity of the data, including outlier removal, missing value filling, data smoothing, etc.;

s3, data storage: the cleaned and preprocessed data is typically stored in a database or data warehouse for subsequent analysis;

s4, data query and extraction: the analysis module needs to be able to query and extract historical data as needed for analysis, which may involve writing SQL queries or using data extraction tools;

s5, trend identification: identifying trends in historical data using statistical methods, machine learning algorithms, or time series analysis, etc., which may be linear, nonlinear, periodic, or seasonal, depending on the nature of the data;

s6, data visualization: the results of the trend analysis are presented in a visual manner, such as a line graph, trend graph, histogram, etc., which helps the user to understand the trend and pattern more easily;

S7, trend analysis report: generating a trend analysis report including key trends, change point detection, periodic analysis and statistical summaries of the trends, the report typically including charts, data tables and explanatory text;

s8, explanation and application: an analyst or decision maker needs to interpret the analysis results and apply trends to business decisions, which may include making production plans, optimizing supply chains, predicting sales trends, resource planning, etc.;

s9, monitoring and updating: trend analysis is a continuous process, and the module needs to monitor data periodically, update trend analysis, and adjust analysis results according to new data;

s10, automation: some systems may have automated functionality that may automatically perform trend analysis and trigger alarms or automated operations when abnormal trends or patterns are detected.

In this embodiment, the inventory management module tracks and records the inventory quantity and status of raw materials, semi-finished products and finished products, provides a visual interface, and displays the current status and position of the inventory;

the inventory management module automatically updates inventory data according to the in-out inventory dynamic state in the production process, sets an inventory warning threshold value, sends out an alarm and automatically triggers a replenishment flow when the inventory level reaches and is lower than the limit, generates an inventory report, and automatically triggers a replenishment order according to the inventory level and the demand forecast to coordinate with a supplier, wherein the inventory report comprises inventory turnover rate, inventory value and expiration inventory information;

The inventory management module calculates and manages the storage cost, opportunity cost and loss cost of the inventory, supports batch tracing and inventory adjustment and scrapping processing, and processes damaged, expired and unqualified inventory.

Specifically, the replenishment process includes the following steps;

s1, inventory monitoring: the initial step involves monitoring the current inventory levels, the system needs to track the inventory amounts of different products, parts or materials, and periodically update inventory information, determine the lowest and highest inventory threshold for each product or material, which are key indicators of what inventory levels to trigger restocking;

s2, inventory analysis: analysis based on inventory data, including inventory turnover, demand forecast, supply chain availability, etc., helps determine which materials need replenishment to meet future demands, demand forecast using historical sales data, production plans, and other relevant information, which can help determine material demand over a period of time in the future;

s3, order generation: based on the demand forecast and the inventory threshold, the system generates a replenishment order, which may include a purchase order, a production work order, or an inventory transfer request, depending on the inventory management policy, the generated replenishment order may need to go through an approval process, which may involve approval by a relevant department or management layer to ensure the rationality of the order;

S4, supplier selection: if a purchase order is made, a suitable supplier needs to be selected, which may be determined according to price, delivery time, delivery capacity, quality and other factors, and after approval, the order is issued to the relevant supplier or production department, and for an inventory transfer request, the order will instruct to transfer material from one inventory location to another inventory location, and the replenishment order is tracked to ensure delivery or production on time, the system can provide information on the status of the order and delivery date in real time;

s5, receiving and checking: once the order is completed, the receiving department receives the material or product, and for the purchase order, material verification may be required to ensure quality compliance, update inventory records, reflect new inventory levels, including adding inventory, reducing inventory, and updating inventory locations;

s6, notifying a relevant party: notifying the relevant departments or stakeholders that the order is complete and ensuring that inventory is available;

s7, cost analysis: performing restocking cost analysis, including purchasing cost, transportation cost, storage cost, etc., to evaluate the total cost of inventory restocking;

s8, performance monitoring: performance indicators of inventory replenishment processes, such as order processing time, inventory turnover rate, etc., are tracked and monitored to continually improve the process.

In the embodiment, the energy management module collects the data of power, natural gas, water and fuel related to energy in the production process, provides real-time energy consumption monitoring, tracks the use condition of the energy, analyzes the energy data to identify potential energy saving opportunities and optimizes the energy use mode;

the energy management module evaluates the energy efficiency of different production devices, identifies production devices with low energy efficiency, provides advice to improve performance, calculates and analyzes the cost of energy consumption, collects and monitors energy efficiency indexes, and evaluates the energy efficiency of the production process;

the energy management module provides energy-saving suggestions for operators and management layers, generates reports and visual charts of energy consumption, visually presents energy data, and manages and tracks the progress of energy-saving projects.

In this embodiment, the report visualization module allows a user to create and customize a report, provide a predefined reporting template, the user quickly generates a report based on the template,

the report visualization module provides a visualized report editor, a user creates and customizes a report by dragging and dropping elements, charts and data fields, a real-time report is allowed to be generated, the current production state and data of the MES running management system intelligently controlled by comparing historical data are reflected immediately, and a historical data analysis report is provided;

The report visualization module is compatible with and comprises a PC, a mobile device and a Web browser platform, and allows users to share reports and distribute the reports to a management layer, operators and suppliers;

the report visualization module provides data visualization tools including data graphs, charts, and dashboards, supporting report review and audit workflows.

The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and their equivalents.

Claims (9)

1. The MES operation management system for intelligently controlling the comparison historical data is characterized by comprising an order management module, a resource scheduling module, a process monitoring module, a data acquisition and analysis module, an inventory management module, an energy management module and a report visualization module;

The order management module is used for creating, tracking and managing production orders, and sequencing and distributing resources according to emergency factors;

the resource scheduling module is responsible for knowing the orders to be produced and the priority of the orders and reasonably distributing production equipment and human resources;

the resource scheduling module knows the state and the availability of the production equipment in real time and makes scheduling decisions;

the process monitoring module collects real-time data of the production equipment and the production process;

the real-time data is provided for the data acquisition and analysis module to use;

the data collection and analysis module uses the real-time data historically to identify potential trends and problems;

the data acquisition and analysis module compares the current real-time data with the past real-time data to find out the abnormality and trend change in the MES operation management system intelligently regulated by the comparison historical data;

the energy management module is responsible for knowing the energy consumption condition of the production equipment and helping the resource scheduling module to make more sustainable resource allocation decisions;

the report visualization module provides a comprehensive view for the MES operation management system intelligently controlled by the comparison historical data, and the manager and the operator monitor the production performance, quality and efficiency of the MES operation management system intelligently controlled by the comparison historical data;

The report visualization module provides comprehensive insight based on the data generation of the MES operation management system intelligently controlled by the comparison historical data.

2. The intelligently controlled MES operation management system according to claim 1, wherein the order management module allows a user to create a new production order, the production order including order number, product specification, quantity, delivery date information, allowing the user to edit detailed information of the existing production order;

the order management module provides real-time state tracking functions of the production order, including state information of received, producing, completed and delivered production order;

the order management module automatically updates the state of the production order and reflects the production progress of the production order;

the order management module allows a user to set priorities for different production orders, provides an automatic priority allocation function, and sorts the production orders according to emergency factors of the production orders;

matching the production order with production equipment and staff to create a production plan, wherein the order management module automatically performs the production order scheduling according to the availability of resources and constraint conditions;

The order management module is used for arranging purchasing and inventory management, and allowing a user to attach and manage files related to the production order, wherein the files comprise a process flow chart, a quality standard and a specification;

the order management module sends automatic notification and reminding to notify staff of change events related to the production order state and delivery date;

the order management module provides reporting and analysis functions related to the production order, including completion of the production order, delay analysis and historical data of the production order;

the order management module records and manages the entire lifecycle of the production order, including creation, modification, cancellation, and shutdown operations of the production order.

3. The system of claim 1, wherein the resource scheduling module schedules the opening, closing, maintenance and cleaning of the equipment, and the resource scheduling module manages and distributes the tasks and work schedules of operators and staff, balances the supply and demand of raw materials and parts, tracks stock levels, makes replenishment schedules, and coordinates the delivery and use of materials;

The resource scheduling module uses ant colony algorithm and historical data analysis to formulate an optimal resource allocation strategy in consideration of efficiency, capacity and constraint conditions of resources, and creates and manages a production plan, and generates scheduling according to urgency of the production order, a process route and resource availability;

the resource scheduling module provides real-time monitoring on production resources and the state of the production equipment, and rapidly identifies and solves the problems;

the resource scheduling module monitors and manages energy usage, tracks workflow, and collects and reports performance metrics regarding the resource scheduling and production efficiency.

4. The MES operation management system for intelligent regulation of comparison history data according to claim 3, wherein the ant colony algorithm is an optimization algorithm based on a behavior model of natural ants searching for food paths, and is used for solving the resource scheduling problem of the MES operation management system for intelligent regulation of comparison history data, and the ant path selection probability formula is a core formula in the ant colony algorithm and is used for guiding ants to select paths from one place to another place;

in the resource scheduling problem, the ant path selection probability formula path corresponds to allocation of resources and planning of a workflow;

The ant path selection probability formula is as follows:

t represents the number of iterations, τab represents the concentration of the pheromone on the path at the moment, ηab represents the visibility of ants to the path, the knowledge of decision space is reflected, na is the number of sides taking the point a as the starting point, and alpha and beta represent the importance degree of the pheromone and the visibility respectively;

the ant path selection probability formula is used in combination with the resource scheduling module to guide allocation decision of resources and planning of workflow.

5. The MES operation management system intelligently controlled by comparing historical data according to claim 1, wherein the process monitoring module collects real-time data related to the production process, sensor data including equipment status, production speed, temperature, pressure and humidity, and monitors information including whether the production equipment is started, running status, shutdown reasons and equipment faults in real time;

the process monitoring module provides a visual interface of the production process, visually displays the states of factories and production lines, monitors size, weight and color data related to product quality, detects quality problems and timely takes corrective measures;

The process monitoring module collects and analyzes the data of the yield, the production speed and the downtime of the production efficiency, evaluates the production performance, implements an alarm system and sends an alarm notice to operators when problems and abnormal conditions occur;

the process monitoring module stores historical production data for subsequent analysis, reporting and trend analysis, allows remote monitoring and control of the production equipment, monitors energy consumption of the production equipment and the production line, evaluates energy efficiency, and provides advice to reduce energy costs and environmental impact.

6. The MES operation management system intelligently controlled by comparing historical data according to claim 1, wherein the data acquisition and analysis module stores historical production data for subsequent analysis and comparison, and cleans and preprocesses the collected historical production data to remove abnormal values, noise and inconsistency, so as to ensure the quality and accuracy of the historical production data;

the data acquisition and analysis module provides a real-time monitoring function, visually displays the current production state and trend of the MES operation management system intelligently controlled by comparing historical data, provides a data analysis tool, supports deep analysis of the production data, and analyzes the production data to evaluate the quality, the production efficiency and the resource utilization rate of the product;

The data acquisition and analysis module utilizes the historical data to perform trend analysis and prediction, analyzes the energy consumption data, automatically generates a customized report and a visual chart, and provides detailed information about the performance of the production process to a management layer and operators.

7. The system of claim 1, wherein the inventory management module tracks and records the inventory quantity and status of the raw materials, semi-finished products and finished products, provides a visual interface, and displays the current status and location of the inventory;

the inventory management module dynamically and automatically updates inventory data according to the in-out inventory in the production process, sets an inventory warning threshold value, sends out an alarm and automatically triggers a replenishment flow when the inventory level reaches and is lower than a limit, and generates an inventory report, wherein the inventory report comprises inventory turnover rate, inventory value and outdated inventory information, and predicts the automatically triggered replenishment order according to the inventory level and the demand to coordinate with a supplier;

the inventory management module calculates and manages storage cost, opportunity cost and loss cost of the inventory, supports batch traceability and the inventory adjustment and discard processing, and processes damaged, expired and unqualified inventory.

8. The system of claim 1, wherein the energy management module collects power, natural gas, water, and fuel data associated with energy during the production process, provides real-time energy consumption monitoring, tracks the energy usage, analyzes the energy data to identify potential energy conservation opportunities, and optimizes energy usage;

the energy management module evaluates energy efficiency of different production devices, identifies the production devices with low energy efficiency, provides advice to improve performance, calculates and analyzes cost of energy consumption, collects and monitors energy efficiency indicators, and evaluates energy efficiency of the production process;

the energy management module provides energy-saving suggestions for operators and management layers, generates a report and a visual chart of the energy consumption, visually presents the energy data, and manages and tracks the progress of energy-saving projects.

9. The intelligently controlled MES operation management system according to claim 1, wherein the report visualization module allows a user to create and customize reports, provide predefined reporting templates, the user quickly generates reports based on the templates,

The report visualization module provides a visualized report editor, a user creates and customizes a report by dragging and dropping elements, charts and data fields, a real-time report is allowed to be generated, the current production state and data of the MES operation management system intelligently controlled by comparing historical data are reflected in real time, and a historical data analysis report is provided;

the report visualization module is compatible with and comprises a PC, a mobile device and a Web browser platform, and allows a user to share the report and distribute the report to a management layer, operators and suppliers;

the report visualization module provides the data visualization tools including data graphs, charts, and dashboards supporting the report review and audit workflow.