Magnesium metal reduction workshop production co-scheduling management system

Abstract

The invention discloses a magnesium metal reduction workshop production collaborative scheduling management system, and relates to the technical field of workshop production management, and the system comprises a workshop monitoring module which is used for monitoring the production progress and the operation state of equipment in a magnesium metal reduction workshop in real time; the workshop monitoring module comprises a data acquisition unit, a data arrangement unit and a data display unit, the data acquisition unit is connected with the data arrangement unit through network signals, and the data arrangement unit is connected with the data display unit through network signals. The workshop monitoring module is designed, so that the comprehensive monitoring function of the workshop production process is realized, the accuracy and efficiency of production scheduling are improved, and the problem that workshop management personnel cannot master the production progress and the equipment state in a workshop at any time is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of workshop production management, and specifically to a production collaborative scheduling management system for a magnesium metal reduction workshop. Background Art

[0002] In the traditional production management mode of the magnesium metal reduction workshop, the transmission of production data often relies on manual records, report summaries, etc. This method is not only inefficient but also prone to problems such as lagging and errors in data transmission. Therefore, it is difficult for workshop managers to obtain accurate data on each production link in real time, and they cannot comprehensively and timely understand the production progress and scheduling situation, resulting in the loss of the best decision-making opportunity when workshop managers obtain production data.

[0003] When facing a complex and changeable production environment, since workshop managers cannot grasp the production situation in real time, when problems such as equipment failures, insufficient raw material supply, and operator errors occur during the production scheduling process in the magnesium metal reduction workshop, it is difficult for workshop managers to respond to these uncertain factors in a timely and accurate manner, resulting in inflexible and inefficient production scheduling.

[0004] 1. Patent document CN113837628B discloses a crane scheduling method for a metallurgical industrial workshop based on deep reinforcement learning. The above patent realizes that the crane scheduling model can generate a globally optimized scheduling plan in a timely manner for randomly generated or temporarily changed transportation tasks, but the above patent cannot realize the comprehensive monitoring function of the workshop production process.

[0005] 2. Patent document CN108445854B discloses a workshop autonomous learning method for an intelligent workshop based on big data. The above patent realizes the automatic adjustment of the temperature and humidity in the workshop, ensures the quality of the products processed in the workshop, and further improves the processing efficiency of the workshop, but the above patent cannot realize the optimization function of the workshop production strategy.

[0006] 3. Patent document CN108073142B discloses a scheduling method and device for job shop resources. The above patent realizes the coordination of the scheduling plan among resources, reduces the occurrence of production disturbance events, and improves the executability of the plan, but the above patent cannot realize the early warning function of potential risks in the workshop production process.

[0007] 4. Patent document CN107832497B discloses an intelligent workshop rapid customization design method and system. The above patent realizes the direct transplantation of the production line optimization design plan into the real production system, saves production input costs, and reduces the uncertainty between design and production manufacturing, but the above patent cannot realize the data trend analysis function of workshop production data.

[0008] In summary, the above-mentioned patent cannot achieve the comprehensive monitoring function of the workshop production process, cannot achieve the optimization function of the workshop production strategy, cannot achieve the early warning function of potential risks in the workshop production process, and cannot achieve the data trend analysis function of workshop production data, resulting in the problems that workshop managers cannot understand production data at any time, production tasks cannot be completed in a timely manner, accidents occur in the production process, and there is a lack of data basis for formulating production strategies; Therefore, the present application proposes a magnesium metal reduction workshop production collaborative scheduling management system that can achieve the comprehensive monitoring function of the workshop production process, the optimization function of the workshop production strategy, the early warning function of potential risks in the workshop production process, and the data trend analysis function of workshop production data. Summary of the Invention

[0009] The purpose of the present invention is to provide a magnesium metal reduction workshop production collaborative scheduling management system to solve the technical problems mentioned in the above background technology, namely, the inability to achieve the comprehensive monitoring function of the workshop production process, the inability to achieve the optimization function of the workshop production strategy, the inability to achieve the early warning function of potential risks in the workshop production process, and the inability to achieve the data trend analysis function of workshop production data, resulting in the problems that workshop managers cannot understand production data at any time, production tasks cannot be completed in a timely manner, accidents occur in the production process, and there is a lack of data basis for formulating production strategies.

[0010] To achieve the above purpose, the present invention provides the following technical solution: A magnesium metal reduction workshop production collaborative scheduling management system, including a workshop monitoring module, where the workshop monitoring module is used to monitor the production progress and operating status of equipment in the magnesium metal reduction workshop in real time; The workshop monitoring module includes: a data collection unit, a data sorting unit, and a data display unit. The data collection unit is connected to the data sorting unit through a network signal, and the data sorting unit is connected to the data display unit through a network signal; The data collection unit uses GPS positioning technology to collect the positions of material transportation vehicles in real time, including magnesium vehicles, slag vehicles, and material vehicles, monitors vehicle dynamics, and through the deployment of a sensor network, collects the load data and operating data of the vehicles in real time, and collects the status data and production data of the reduction furnace; The data sorting unit standardizes the data, stores the standardized data in a database, establishes the linkage relationship between equipment, and correlates the data, including the correlation between transportation vehicles, the correlation between transportation vehicles and reduction furnaces, and the correlation between time and production progress; The data display unit constructs a 3D model of the equipment in the workshop, maps the standardized and associated data into the 3D model, uses lines to connect the associated data points to display the correlation between the data, and shares the 3D model in real time to each area of the workshop to display the changes in the data of transport vehicles and reduction furnaces in real time and show the production scheduling process of the workshop.

[0011] Preferably, the data sorting unit is connected with an intelligent scheduling module through a network signal. The intelligent scheduling module is used to adjust the production tasks of the equipment in the workshop and adjust and optimize each link in the production process. The intelligent scheduling module includes: a progress analysis unit, a strategy adjustment unit, and a strategy execution unit. The progress analysis unit is connected with the strategy adjustment unit through a network signal, and the strategy adjustment unit is connected with the strategy execution unit through a network signal. The progress analysis unit analyzes the production progress of the workshop according to the real-time data of the equipment. By comparing the actual production progress with the target production plan preset by the staff, it judges the completion of the production tasks. When the target production plan is not reached, it starts the bottleneck identification mechanism. The strategy adjustment unit optimizes the production strategy of the workshop according to the identified production bottlenecks and production requirements, adjusts the transport vehicle scheduling plan, optimizes the production plan of the reduction furnace, and coordinates the allocation of human resources. The strategy execution unit distributes the production tasks to each production link in the workshop according to the production strategy, generates a log report from the workshop production progress data and the optimized production strategy, and feeds back the log report to the workshop management personnel.

[0012] Preferably, the data sorting unit is connected with a risk warning module through a network signal. The risk warning module is used for risk assessment and warning of the workshop. The risk warning module includes: a risk analysis unit, a risk assessment unit, and a risk recording unit. The risk analysis unit is connected with the risk assessment unit through a network signal, and the risk assessment unit is connected with the risk recording unit through a network signal. The risk analysis unit analyzes the load condition and its own state of the transport vehicle according to the load data and operation data of the transport vehicle, identifies the risks of overloading and malfunction of the transport vehicle, and predicts the risks of overheating, overpressure, and leakage of the reduction furnace according to the state data of the reduction furnace. The risk assessment unit quantitatively assesses the analyzed risks, judges the severity of the risks, and provides preventive and solution measures according to the risk information and historical solutions. The risk recording unit feeds back the risk analysis, prediction, assessment, and solution to the workshop management personnel, records the risk data and the risk handling results, classifies them according to the type and level of the risks, and stores the risk data in the database.

[0013] Preferably, the data display unit is connected to a historical analysis module via a network signal, and the historical analysis module is used to access the historical data of the equipment in the workshop; The historical analysis module includes: a historical trend unit, a report generation unit, and an access control unit. The historical trend unit is connected to the report generation unit via a network signal, and the report generation unit is connected to the access control unit via a network signal; After the production task is completed, the historical trend unit analyzes the production data in the database, analyzes the data change trend, compares the historical data, analyzes the bottleneck links and potential problems in the production process, and proposes optimization suggestions and improvement measures; The report generation unit generates a workshop production analysis report based on the historical data analysis results, intuitively displays the data changes and production bottlenecks using trend charts, provides a user interaction interface, and allows users to query, export, and print; The access control unit sets the user's access rights, verifies the user's identity, controls the access and operation of historical data according to the user's rights, and records the user's access to historical data and the user's operation records of the equipment.

[0014] Preferably, the data display unit is connected to a data sharing module via a network signal, and the data sharing module is used to share the production data of each area in the workshop and the conflict points of the scheduling strategies between the identification areas in the workshop; The data sharing module includes: a data integration unit and a conflict identification unit. The data integration unit is connected to the conflict identification unit via a network signal; The data integration unit integrates the production data of the workshop and the scheduling strategies of each area, constructs a comprehensive production overview and scheduling strategy view, and shares the data to each area in the workshop; The conflict identification unit compares and analyzes the scheduling strategies of each area in the workshop and identifies the conflict points of the scheduling strategies between the areas.

[0015] Preferably, the strategy adjustment unit is connected to a transport vehicle scheduling module via a network signal, and the transport vehicle scheduling module is used to schedule the transport vehicles in the workshop; The transport vehicle scheduling module includes: an environment modeling unit, a path optimization unit, and a vehicle operation unit. The environment modeling unit is connected to the path optimization unit via a network signal, the path optimization unit is connected to the vehicle operation unit via a network signal, and the environment modeling unit is connected to a data sorting unit via a network signal; The environment modeling unit establishes a three-dimensional model of the workshop according to the layout of the workshop, reflects the layout of the workshop, the equipment location, and the transport channels, maps the status data of the transport vehicles into the model, and updates the status information of the transport vehicles in real time; The path optimization unit dynamically analyzes the shortest transport path of the transport vehicle according to the real-time status information of the transport vehicle, and dynamically adjusts the transport path according to the real-time information of the transport channels in the three-dimensional model; The vehicle operation unit schedules the transport vehicles to perform transportation tasks according to the path information. Based on the associated data of the transport vehicles, it analyzes the transportation requirements among the magnesium vehicles, slag vehicles, and material vehicles, and schedules the transport vehicles according to the production status and plan of the reduction furnace.

[0016] Preferably, the risk recording unit is connected with an abnormal perception module through a network signal. The abnormal perception module issues an alarm when an abnormal situation occurs in the workshop; The abnormal perception module includes: an abnormal detection unit, an abnormal analysis unit, and an alarm triggering unit. The abnormal detection unit is connected with the abnormal analysis unit through a network signal, and the abnormal analysis unit is connected with the alarm triggering unit through a network signal; The abnormal detection unit uses a camera to capture the environmental image of the workshop, and identifies the position information of the staff, the running information of the transport vehicle, and the road conditions of the transport passage according to the image data; The abnormal analysis unit generates the dangerous areas of the workshop according to the real-time production data of the equipment in the workshop, judges the area where the staff is located according to the position information of the staff, predicts the walking trajectory of the staff, and identifies the transportation status of the transport vehicle; When the alarm triggering unit detects that the staff is in a dangerous area or the position of the transport passage, it reminds the staff to evacuate through an alarm. In the case of the transport vehicle deviating from the transport passage and tipping over, it triggers an alarm and feeds it back to the workshop management personnel.

[0017] Preferably, the interlock relationships between the devices include: the interlock relationship between the magnesium vehicle and the reduction furnace, the interlock relationship between the slag vehicle and the reduction furnace, the interlock relationship between the material vehicle and the reduction furnace, and the interlock relationship between the transport vehicles.

[0018] Preferably, the bottleneck identification mechanism includes the following steps: Step 1: Analyze the potential factors that cause the actual production progress not to reach the target production plan, including equipment failures, raw material shortages, and insufficient personnel allocation; Step 2: Analyze the causes of the potential factors and their impact on the production progress, and determine the bottleneck factors.

[0019] Preferably, the conflict points of the scheduling strategy include: equipment usage conflicts, task assignment conflicts, and production progress conflict identification.

[0020] Compared with the prior art, the beneficial effects of the present invention are: 1. By designing a workshop monitoring module, the present invention realizes the comprehensive monitoring function of the workshop production process, improves the accuracy and efficiency of production scheduling, and solves the problem that workshop management personnel cannot always master the production progress and equipment status in the workshop; 2. The present invention realizes the optimization function of the workshop production strategy through the design of an intelligent scheduling module, improves the production efficiency of the workshop, enhances the continuity of the production process, and realizes the real-time monitoring and efficient scheduling of the workshop production process; 3. The present invention realizes the early warning function of potential risks in the workshop production process through the design of a risk warning module, solves the problem that workshop management personnel cannot discover and handle workshop hidden dangers in a timely manner, and improves the safety and stability of workshop production; 4. The present invention realizes the data trend analysis function of workshop production data through the design of a historical analysis module, solves the problem that production data in the past was ignored or underutilized, and improves the management level of workshop management personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a partial schematic diagram of the workshop monitoring module of the present invention; Figure 2 It is a partial schematic diagram of the intelligent scheduling module of the present invention; Figure 3 It is a partial schematic diagram of the risk warning module of the present invention; Figure 4 It is a partial schematic diagram of the historical analysis module of the present invention; Figure 5 It is a partial schematic diagram of the data sharing module of the present invention; Figure 6 It is a partial schematic diagram of the transport vehicle scheduling module of the present invention; Figure 7 It is a partial schematic diagram of the abnormal perception module of the present invention; Figure 8 It is a schematic diagram of the system working process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] Example 1, please refer to Figure 1 、 Figure 5 and Figure 8, A collaborative production scheduling and management system for a magnesium metal reduction workshop, including a workshop monitoring module, which is used to monitor the production progress and operating status of equipment in the magnesium metal reduction workshop in real time; the workshop monitoring module includes: a data collection unit, a data sorting unit, and a data display unit. The data collection unit is connected to the data sorting unit through a network signal, and the data sorting unit is connected to the data display unit through a network signal; the data collection unit uses GPS positioning technology to collect the positions of material transportation vehicles in real time, including magnesium vehicles, slag vehicles, and material vehicles, monitors the vehicle dynamics, and through the deployment of a sensor network, collects the load data and operating data of the vehicles in real time, and collects the status data and production data of the reduction furnaces; the data sorting unit standardizes the data, stores the standardized data in a database, establishes the linkage relationship between equipment, and correlates the data, including the correlation between transportation vehicles, the correlation between transportation vehicles and reduction furnaces, and the correlation between time and production progress; the data display unit constructs a three-dimensional model of the equipment in the workshop, maps the standardized and correlated data into the three-dimensional model, uses lines to connect the relevant data points, displays the correlation between the data, and shares the three-dimensional model in real time to each area of the workshop, and displays the changes in the data of transportation vehicles and reduction furnaces in real time, and shows the production scheduling process of the workshop; The data display unit is connected to a data sharing module through a network signal. The data sharing module is used to share the production data of each area of the workshop and the conflict points of the scheduling strategies between each identification area of the workshop; the data sharing module includes: a data integration unit and a conflict identification unit. The data integration unit is connected to the conflict identification unit through a network signal; the data integration unit integrates the production data of the workshop and the scheduling strategies of each area, constructs a comprehensive production overview and scheduling strategy view, and shares the data to each area of the workshop; the conflict identification unit compares and analyzes the scheduling strategies of each area of the workshop and identifies the conflict points of the scheduling strategies between areas.

[0024] Furthermore, the data sorting unit receives the workshop production data collected in real time by the data acquisition unit, standardizes and correlates the data to unify the data format. The data sorting unit stores the standardized data in the database to avoid data loss. The data display unit constructs a 3D model of the equipment in the workshop. The data display unit receives the data processed by the data sorting unit and maps the data into the 3D model, thereby visually displaying the load data and operation data of transportation vehicles such as magnesium vehicles, slag vehicles, and material vehicles in the workshop to the staff, and displaying the status data and production data of the reduction furnace. Workshop managers can accurately grasp the specific positions and movement trajectories of transportation vehicles such as magnesium vehicles, slag vehicles, and material vehicles, so that workshop managers can keep track of the vehicle dynamics at any time and comprehensively monitor various equipment in the workshop, facilitating the staff to promptly discover and solve potential problems. Viewing the associated data according to the lines in the model helps workshop managers better understand the production process in the workshop, enabling managers to intuitively see the interactions and influences between equipment, providing a data basis for workshop managers to formulate or optimize production scheduling strategies. Through the associated data of time information and production tasks, managers can understand the start time, end time, and required time of each production task, thereby helping managers understand the completion status of production tasks. Through the associated data of transportation vehicles such as magnesium vehicles, slag vehicles, and material vehicles and the reduction furnace, managers can understand the transportation situation of raw materials and waste residues, understand the consumption of raw materials, and thus understand the transportation progress of the transport vehicles and the production progress of the reduction furnace, thereby helping managers optimize the production process. When a transport vehicle completes a loading task, its data will be automatically associated with the data of the next transport vehicle that needs to be loaded to ensure the continuity of the production process. It realizes the comprehensive monitoring of the workshop production process, improves the accuracy and efficiency of production scheduling, and also reduces production costs and safety risks; The data integration unit within the data sharing module receives the data collected by the workshop monitoring module. The data integration unit integrates the production data of the workshop and the scheduling strategies of each area to construct a comprehensive view of the production profile and scheduling strategies, and shares it with each area of the workshop. Through the data display unit, it provides an intuitive and visual display to the staff in each area of the workshop. The conflict recognition unit of the data integration unit provides comprehensive data support to ensure the accuracy and comprehensiveness of conflict recognition. The conflict recognition unit promptly discovers and resolves the scheduling strategy conflicts between different areas of the workshop to ensure the smooth progress of production scheduling. Through conflict recognition, the data integration unit and the conflict recognition unit can avoid production delays and resource waste caused by inappropriate scheduling strategies, and improve the production efficiency and economic benefits of the workshop. Through the workshop monitoring module and the data sharing module, the production status and scheduling requirements of the workshop can be monitored in real time to ensure the accuracy and timeliness of production scheduling, promptly discover and resolve the scheduling strategy conflicts between different areas of the workshop, and conduct data sharing so that the data of each area can be transmitted in a timely manner. Through the intuitive and dynamic display of the data display unit, the entire production scheduling process of the magnesium metal reduction workshop is presented, and the status data of the reduction furnace is also shown.

[0025] Example 2, please refer to Figure 1 、 Figure 2 and Figure 8 , a production collaborative scheduling management system for a magnesium metal reduction workshop. The workshop monitoring module is used to monitor the production progress and operating status of the equipment in the magnesium metal reduction workshop in real time. The workshop monitoring module includes: a data collection unit, a data sorting unit, and a data display unit. The data sorting unit is connected to an intelligent scheduling module through a network signal. The intelligent scheduling module is used to adjust the production tasks of the equipment in the workshop and adjust and optimize each link in the production process. The intelligent scheduling module includes: a progress analysis unit, a strategy adjustment unit, and a strategy execution unit. The progress analysis unit is connected to the strategy adjustment unit through a network signal, and the strategy adjustment unit is connected to the strategy execution unit through a network signal. The progress analysis unit analyzes the production progress of the workshop based on the real-time data of the equipment, judges the completion of the production tasks by comparing the actual production progress with the target production plan preset by the staff, and starts the bottleneck identification mechanism when the target production plan is not reached. The strategy adjustment unit optimizes the production strategy of the workshop according to the identified production bottlenecks and production requirements, adjusts the transportation vehicle scheduling plan, optimizes the production plan of the reduction furnace, and coordinates the allocation of human resources. The strategy execution unit assigns the production tasks to each production link in the workshop according to the production strategy, generates a log report from the production progress data of the workshop and the optimized production strategy, and feeds the log report back to the workshop management personnel.

[0026] Further, the progress analysis unit receives the data standardized and associated by the data sorting unit, analyzes the data, analyzes the transportation situation of materials such as magnesium metal raw materials, waste slag, and auxiliary materials by analyzing the load data of transportation vehicles such as magnesium trucks, slag trucks, and material trucks and the operation data between the vehicles, analyzes the production progress of the reduction furnace by analyzing the collected status data and production data of the reduction furnace, thereby further analyzing the real-time production progress of the workshop, determining the operation status of each production link, and by comparing the actual production progress with the target production plan preset by the staff, the progress analysis unit can judge whether the production task is completed on time. When the actual production progress does not reach the target production plan, the progress analysis unit will automatically start the bottleneck identification mechanism, find out the bottleneck links in the production process by analyzing the data. The strategy adjustment unit, according to the analysis results of the progress analysis unit and the associated data of the transportation vehicles and the reduction furnace transmitted by the data sorting unit, further analyzes the real-time positions and load data of magnesium trucks, slag trucks, and material trucks, as well as the raw material requirements, waste slag treatment, and auxiliary material requirements of the reduction furnace, generates strategies for the nearby slag trucks, magnesium trucks, and material trucks to feed and transport materials, while ensuring the coordinated scheduling of transport vehicles, improving the feeding and discharging efficiency of materials such as magnesium metal raw materials, waste slag, and auxiliary materials, ensuring the continuity of the production process, ensuring that materials are delivered to each production link in a timely and accurate manner, reducing production interruptions and waiting times, optimizing the production plan according to the real-time status and production requirements of the reduction furnace, improving the utilization rate of equipment and production efficiency, reasonably allocating human resources according to the priorities of production tasks, ensuring that there are sufficient personnel support for each production link, thereby optimizing the production strategy of the workshop. The strategy execution unit receives the optimized production strategy of the strategy adjustment unit and assigns production tasks to each production link in the workshop. The strategy execution unit generates a log report from the workshop production progress data and the optimized production strategy, detailing the key information in the production process, providing decision-making support for workshop management personnel. The data display unit receives the log report and the generated strategy transmitted by the strategy execution unit and displays them to the workshop staff, enabling workshop management personnel to master accurate and comprehensive production data and analysis results.

[0027] Example 3, please refer to Figure 1 、 Figure 3 and Figure 8, a collaborative scheduling management system for magnesium metal reduction workshop. The workshop monitoring module is used to monitor the production progress and operation status of equipment in the magnesium metal reduction workshop in real time; the workshop monitoring module includes: a data collection unit, a data sorting unit, and a data display unit; the data sorting unit is connected to an intelligent scheduling module through a network signal. The intelligent scheduling module is used to adjust the production tasks of equipment in the workshop and adjust and optimize each link in the production process; the data sorting unit is connected to a risk warning module through a network signal. The risk warning module is used for risk assessment and warning of the workshop; the risk warning module includes: a risk analysis unit, a risk assessment unit, and a risk recording unit. The risk analysis unit is connected to the risk assessment unit through a network signal, and the risk assessment unit is connected to the risk recording unit through a network signal; the risk analysis unit analyzes the load data and operation data of the transport vehicle to identify the load condition and its own status of the transport vehicle, and identifies the risks of overloading and malfunction of the transport vehicle. According to the status data of the reduction furnace, it predicts the risks of overheating, overpressure, and leakage of the reduction furnace; the risk assessment unit quantitatively assesses the analyzed risks, judges the severity of the risks, and provides preventive and solution measures based on the risk information and historical solutions; the risk recording unit feeds back the risk analysis, prediction, assessment, and solution to the workshop management personnel, records the risk data and risk handling results, classifies them according to the type and level of the risks, and stores the risk data in the database.

[0028] Furthermore, the risk analysis unit receives the data transmitted by the data sorting unit in the workshop monitoring module. The risk analysis unit analyzes the real-time data of transport vehicles and reduction furnaces, including the load data and operation data of transport vehicles, such as speed, acceleration, driving time, etc., and the status data of reduction furnaces, such as temperature, pressure, leakage detection data, etc. For transport vehicles, the risk analysis unit can identify whether there are risks of overloading or malfunction by analyzing the load data and operation data. When the load of the vehicle exceeds the upper limit of its bearing capacity, the risk analysis unit will identify the overloading risk. When the driving time of the vehicle is too long or it stops for a long time, the risk analysis unit will identify the malfunction risk; for the reduction furnace, the risk analysis unit can predict whether there are risks of overheating, overpressure, or leakage by analyzing the status data. When the temperature or pressure of the reduction furnace exceeds the preset safety threshold, the risk analysis unit will identify the overheating or overpressure risk. When it is detected that there is a leakage phenomenon in the reduction furnace, the risk analysis unit determines that the reduction furnace leaks; The risk assessment unit receives risk information from the risk analysis unit, quantifies and assesses this information, determines key indicators such as the severity, likelihood, and scope of impact of the risk. The risk assessment unit will classify the identified risks and provide solutions based on historical risk and solution data in the system database, and provide recommended measures for preventing and resolving risks. The risk recording unit feeds back information such as risk data and solutions to the workshop management personnel through the data display unit. The workshop management personnel can intuitively view the risk information through the data display unit. The workshop management personnel understand the severity and scope of impact of the risk based on the analysis, prediction, and assessment data of the risk, so as to effectively prevent and solve related problems. At the same time, the risk recording unit will generate a detailed risk report, including information such as risk type, level, occurrence time, location, cause, and handling measures. The risk recording unit stores the risk data in the database for the workshop management personnel to consult and analyze, and at the same time provides a data basis for the next risk assessment of the risk assessment unit.

[0029] Example 4, please refer to Figure 1 、 Figure 4 and Figure 8 , a collaborative production scheduling and management system for a magnesium metal reduction workshop. The workshop monitoring module is used to monitor the production progress and operating status of equipment in the magnesium metal reduction workshop in real time; the workshop monitoring module includes: a data acquisition unit, a data sorting unit, and a data display unit; the data sorting unit is connected to an intelligent scheduling module through a network signal. The intelligent scheduling module is used to adjust the production tasks of equipment in the workshop and adjust and optimize each link in the production process; the data display unit is connected to a historical analysis module through a network signal. The historical analysis module is used to access the historical data of equipment in the workshop; the historical analysis module includes: a historical trend unit, a report generation unit, and an access control unit. The historical trend unit is connected to the report generation unit through a network signal, and the report generation unit is connected to the access control unit through a network signal; the historical trend unit analyzes the production data in the database after the production task is completed, analyzes the data change trend, compares the historical data, analyzes the bottleneck links and potential problems in the production process, and proposes optimization suggestions and improvement measures; the report generation unit generates a workshop production analysis report based on the historical data analysis results, intuitively displays the data change and production bottleneck using a trend chart, provides a user interaction interface, and allows users to query, export, and print; the access control unit sets the access rights of users, verifies the user identity, controls the access and operation of historical data according to the user rights, and records the access of users to historical data and the operation records of users on equipment.

[0030] Furthermore, the data acquisition unit in the workshop monitoring module collects the production data of the workshop in real time. The data sorting unit processes the data collected by the data acquisition unit and stores the processed data in the database. After the production task is completed, the historical trend unit extracts the workshop production data from the database, uses statistical methods and data analysis tools to analyze the change trend of the data, identify the abnormal points and fluctuations in the data, analyze the production bottlenecks and risk information that occur in the production process, compare with historical data, find the improvement space in the production process, put forward targeted optimization suggestions and improvement measures, provide a scientific basis for the next production to improve production efficiency, reveal potential problems and improvement space in the production process through trend analysis, and solve the problem that production data was previously ignored or underutilized; The report generation unit integrates relevant data and information according to the analysis results of the historical trend unit, uses charts and trend charts to visually display data changes and production bottlenecks, provides a user interaction interface, allows users to query, export and print reports, so that workshop managers can understand the production status at any time after production is completed, and provide a data basis for the next production decision according to the production report. The access control unit verifies the identity and permissions of users when they access the system, ensures that users can only access the data and functions within their permissions, records the access of users to historical data and the operation records of equipment for auditing and traceability, and protects the security and privacy of production data.

[0031] Example 5, please refer to Figure Figure 2 、 Figure 6 and Figure 8, A production collaborative scheduling management system for a magnesium metal reduction workshop, including a workshop monitoring module, which is used to monitor the production progress and operating status of equipment in the magnesium metal reduction workshop in real time; the workshop monitoring module includes: a data acquisition unit, a data sorting unit, and a data display unit; the intelligent scheduling module includes: a progress analysis unit, a strategy adjustment unit, and a strategy execution unit. The progress analysis unit is connected to the strategy adjustment unit through a network signal, and the strategy adjustment unit is connected to the strategy execution unit through a network signal; the strategy adjustment unit is connected to a transport vehicle scheduling module through a network signal, and the transport vehicle scheduling module is used for the scheduling of transport vehicles in the workshop; the transport vehicle scheduling module includes: an environment modeling unit, a path optimization unit, and a vehicle operation unit. The environment modeling unit is connected to the path optimization unit through a network signal, the path optimization unit is connected to the vehicle operation unit through a network signal, and the environment modeling unit is connected to the data sorting unit through a network signal; the environment modeling unit establishes a three-dimensional model of the workshop according to the layout of the workshop, reflecting the layout of the workshop, the location of equipment, and the transport channels, maps the state data of the transport vehicles into the model, and updates the state information of the transport vehicles in real time; the path optimization unit dynamically analyzes the shortest transport path of the transport vehicles according to the real-time state information of the transport vehicles, and dynamically adjusts the transport path according to the real-time information of the transport channels in the three-dimensional model; the vehicle operation unit schedules the transport vehicles to perform transport tasks according to the path information, analyzes the transport requirements among magnesium vehicles, slag vehicles, and material vehicles according to the associated data of the transport vehicles, and schedules the transport vehicles according to the production status and plan of the reduction furnace.

[0032] Furthermore, during the process of the intelligent scheduling module optimizing the scheduling strategy of the system, the transport vehicle scheduling module receives the signal for adjusting the scheduling of transport vehicles transmitted by the strategy adjustment unit in the intelligent scheduling module. The environment modeling unit in the transport vehicle scheduling module constructs a three-dimensional model of the workshop according to the layout information of the workshop, including equipment location, transport channels, obstacles, etc., accurately reflecting the actual layout and transport environment of the workshop. The transport vehicle scheduling module receives the state data of the transport vehicles collected in real time by the workshop monitoring module, such as location, speed, load, etc., and maps the data into the three-dimensional model of the workshop in real time to ensure that the vehicle state in the model is consistent with the actual state. As the transport vehicles move and their states change, the environment modeling unit dynamically adjusts the vehicle state information in the three-dimensional model; the path optimization unit uses algorithms to analyze the shortest transport path of the transport vehicles, and dynamically adjusts the transport path according to the real-time information of the transport channels, such as congestion conditions, obstacle locations, etc., to ensure the optimality of the path. The path optimization unit outputs the optimized path information to the strategy execution unit and the vehicle operation unit to match the optimal transport path for each transport vehicle. The strategy execution unit then assigns production tasks such as the transport time interval and load of the transport vehicles.

[0033] Example 6, please refer to Figure 3 , Figure 7 andFigure 8 , a collaborative scheduling and management system for magnesium metal reduction workshop production. The data sorting unit is connected to a risk warning module through a network signal. The risk warning module is used for risk assessment and warning of the workshop. The risk warning module includes: a risk analysis unit, a risk assessment unit, and a risk recording unit. The risk analysis unit is connected to the risk assessment unit through a network signal, and the risk assessment unit is connected to the risk recording unit through a network signal. The risk recording unit is connected to an abnormal perception module through a network signal. The abnormal perception module issues an alarm when an abnormal situation occurs in the workshop. The abnormal perception module includes: an abnormal detection unit, an abnormal analysis unit, and an alarm triggering unit. The abnormal detection unit is connected to the abnormal analysis unit through a network signal, and the abnormal analysis unit is connected to the alarm triggering unit through a network signal. The abnormal detection unit uses a camera to capture the environmental image of the workshop, and identifies the position information of the staff, the running information of the transport vehicle, and the road conditions information of the transport passage according to the image data. The abnormal analysis unit generates the dangerous area of the workshop according to the real-time production data of the equipment in the workshop, judges the area where the staff is located according to the position information of the staff, predicts the walking trajectory of the staff, and identifies the transport state of the transport vehicle. When the alarm triggering unit detects that the staff is in a dangerous area or the staff is in the position of the transport passage, it reminds the staff to evacuate through an alarm. In the case of the transport vehicle deviating from the transport passage and tipping over, it triggers an alarm and feeds it back to the workshop management personnel.

[0034] Furthermore, the abnormal detection unit captures the environmental image of the workshop in real time through the camera. The abnormal detection unit extracts the position information of the staff, the running information of the transport vehicle, and the road conditions information of the transport passage, etc. from the captured image data, and obtains the environmental image and relevant information in the workshop in real time, providing a data basis for subsequent abnormal analysis and alarm triggering, and realizing the accurate identification and positioning of various elements in the workshop. The abnormal analysis unit generates the dangerous area of the workshop according to the real-time production data of the equipment in the workshop and the preset safety specifications. The abnormal analysis unit judges whether the area where the staff is currently located is safe according to the real-time position information of the staff located by the abnormal detection unit, predicts its possible walking trajectory, judges whether the staff will block the transport vehicle, and at the same time, the abnormal analysis unit also identifies the transport state of the transport vehicle, judges whether the transport vehicle deviates from the transport passage or tips over, etc. By analyzing and judging various elements in the workshop in real time, it is possible to discover and identify abnormal situations in time, provide accurate abnormal information for the alarm triggering unit, and take corresponding countermeasures in time. The alarm triggering unit judges whether it is necessary to trigger an alarm according to the abnormal information provided by the abnormal analysis unit. The alarm triggering unit issues an alarm message to the staff through the alarm system in the workshop, reminding the staff to pay attention and take corresponding evacuation or countermeasures. The risk recording unit records the accidents analyzed by the abnormal analysis unit.

[0035] Working principle: The workshop monitoring module collects the workshop production data in real time, maps the data into the 3D model. The data sharing module receives the production data transmitted by the workshop monitoring module and integrates it with the scheduling strategies of each area to identify the scheduling strategy conflicts between areas. The data sharing module transmits the integrated and identified data back to the workshop monitoring module so that the staff in each area of the workshop can understand the production progress and production strategies of themselves and other areas in real time through the workshop monitoring module, and thus adjust the production strategy. When the intelligent scheduling module detects that the actual production progress has not reached the target production plan, the intelligent scheduling module analyzes the bottleneck links and optimizes the production strategy of the workshop. The intelligent scheduling module optimizes the transportation route through the transport vehicle scheduling module, and the intelligent scheduling module adjusts the adjusted scheduling strategy to improve the transportation efficiency of the transport vehicle. The historical analysis module reveals the potential problems and improvement spaces in the production process through trend analysis, providing a data basis for the formulation and optimization of the production strategy. The risk warning module identifies the potential risks of the transport vehicle and the reduction furnace based on the real-time data of the transport vehicle and the reduction furnace. The risk warning module evaluates the risk information and provides solutions. At the same time, the abnormal perception module analyzes and judges various elements in the workshop in real time so that the abnormal perception module can detect abnormal situations in time and trigger an alarm. The risk warning module records the risks and abnormal information occurring in the production process.

[0036] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

Claims

1. A magnesium metal reduction workshop production collaborative scheduling management system, characterized by: It includes a workshop monitoring module, which is used to monitor the production progress and operation status of equipment in the magnesium metal reduction workshop in real time; The workshop monitoring module includes: a data acquisition unit, a data sorting unit and a data display unit, wherein the data acquisition unit is connected to the data sorting unit via a network signal, and the data sorting unit is connected to the data display unit via a network signal; The data acquisition unit uses GPS positioning technology to collect the positions of material transport vehicles in real time, including magnesium vehicles, slag vehicles, and material vehicles, monitors vehicle dynamics, and collects vehicle load data and operation data in real time by deploying a sensor network, and collects reduction furnace status data and production data; The data sorting unit performs standardized processing on the data, stores the standardized data in a database, establishes a linkage relationship between the devices, and associates the data, including the association between the transport vehicles, the association between the transport vehicles and the reduction furnace, and the association between the time and the production progress; The data display unit constructs a three-dimensional model of the equipment in the workshop, maps the standardized and associated data into the three-dimensional model, uses lines to connect associated data points, displays the correlation between the data, shares the three-dimensional model to various areas of the workshop in real time, displays changes in transport vehicle and reduction furnace data in real time, and displays the workshop production scheduling process.

2. A magnesium metal reduction workshop production collaborative scheduling management system according to claim 1, characterized in that: The data sorting unit is connected to an intelligent scheduling module via a network signal, and the intelligent scheduling module is used to adjust the production tasks of the equipment in the workshop and adjust and optimize each link in the production process; The intelligent scheduling module includes: a schedule analysis unit, a strategy adjustment unit and a strategy execution unit. The schedule analysis unit is connected to the strategy adjustment unit through a network signal, and the strategy adjustment unit is connected to the strategy execution unit through a network signal. The progress analysis unit analyzes the production progress of the workshop based on the real-time data of the equipment, and judges the completion of the production task by comparing the actual production progress with the target production plan preset by the staff. If the target production plan is not reached, the bottleneck identification mechanism is activated; The strategy adjustment unit optimizes the workshop production strategy based on the identified production bottlenecks and production needs, adjusts the transportation vehicle scheduling plan, optimizes the reduction furnace production plan, and coordinates the allocation of human resources; The strategy execution unit allocates production tasks to various production links in the workshop according to the production strategy, generates a log report based on the workshop production progress data and the optimized production strategy, and feeds the log report back to the workshop management personnel.

3. A magnesium metal reduction workshop production collaborative scheduling management system according to claim 1, characterized in that: The data sorting unit is connected to a risk warning module via a network signal, and the risk warning module is used for risk assessment and warning of the workshop; The risk warning module includes: a risk analysis unit, a risk assessment unit and a risk recording unit. The risk analysis unit is connected to the risk assessment unit via a network signal, and the risk assessment unit is connected to the risk recording unit via a network signal. The risk analysis unit analyzes the load and status of the transport vehicle based on the vehicle's load data and operation data, identifies the risk of overloading and failure of the transport vehicle, and predicts the risk of overheating, overpressure, and leakage of the reduction furnace based on the reduction furnace's status data; The risk assessment unit conducts quantitative assessment of the analyzed risks, determines the severity of the risks, and provides prevention and resolution measures based on risk information and historical solutions; The risk recording unit feeds back risk analysis, prediction, assessment and solutions to workshop managers, records risk data and risk handling results, classifies them according to risk type and level, and stores risk data in a database.

4. A magnesium metal reduction workshop production collaborative scheduling management system according to claim 1, characterized in that: The data display unit is connected to a history analysis module via a network signal, and the history analysis module is used to access the history data of the equipment in the workshop; The historical analysis module includes: a historical trend unit, a report generation unit, and an access control unit. The historical trend unit is connected to the report generation unit via a network signal, and the report generation unit is connected to the access control unit via a network signal. After the production task is completed, the historical trend unit analyzes the production data in the database, analyzes the data change trend, compares the historical data, analyzes the bottleneck links and potential problems in the production process, and puts forward optimization suggestions and improvement measures; The report generation unit generates workshop production analysis reports based on historical data analysis results, uses trend charts to intuitively display data changes and production bottlenecks, and provides a user interaction interface that allows users to query, export and print; The access control unit sets the user's access rights, verifies the user's identity, controls the access and operation to the historical data according to the user's rights, and records the user's access to the historical data and the user's operation records on the equipment.

5. The production collaborative scheduling management system for a magnesium metal reduction workshop according to claim 1, characterized in that: The data display unit is connected to a data sharing module via a network signal, and the data sharing module is used to share production data of various areas of the workshop and identify conflicting points of scheduling strategies between various identification areas of the workshop; The data sharing module includes: a data integration unit and a conflict identification unit, wherein the data integration unit is connected to the conflict identification unit via a network signal; The data integration unit integrates the production data of the workshop and the scheduling strategies of each area, builds a comprehensive production overview and scheduling strategy view, and shares the data to each area of ​​the workshop; The conflict identification unit compares and analyzes the scheduling strategies of various areas in the workshop and identifies the conflict points of the scheduling strategies between areas.

6. A magnesium metal reduction workshop production collaborative scheduling management system according to claim 2, characterized in that: The strategy adjustment unit is connected to a transport vehicle scheduling module via a network signal, and the transport vehicle scheduling module is used for scheduling transport vehicles in the workshop; The transport vehicle scheduling module includes: an environment modeling unit, a path optimization unit, and a vehicle operation unit. The environment modeling unit is connected to the path optimization unit through a network signal, the path optimization unit is connected to the vehicle operation unit through a network signal, and the environment modeling unit is connected to the data sorting unit through a network signal; The environmental modeling unit builds a three-dimensional model of the workshop according to the layout of the workshop, reflecting the layout of the workshop, the location of equipment and the transportation channel, maps the status data of the transportation vehicles into the model, and updates the status information of the transportation vehicles in real time; The path optimization unit dynamically analyzes the shortest transportation path of the transportation vehicle based on the real-time status information of the transportation vehicle, and dynamically adjusts the transportation path based on the real-time information of the transportation channel in the three-dimensional model; The vehicle operation unit dispatches the transport vehicles to perform the transport tasks according to the route information, analyzes the transportation demand between the magnesium vehicles, slag vehicles and material vehicles according to the associated data of the transport vehicles, and dispatches the transport vehicles according to the generation status and plan of the reduction furnace.

7. A magnesium metal reduction workshop production collaborative scheduling management system according to claim 3, characterized in that: The risk recording unit is connected to an abnormality sensing module via a network signal, and the abnormality sensing module issues an alarm when an abnormal condition occurs in the workshop; The abnormality sensing module includes: an abnormality detection unit, an abnormality analysis unit and an alarm triggering unit, the abnormality detection unit is connected to the abnormality analysis unit through a network signal, and the abnormality analysis unit is connected to the alarm triggering unit through a network signal; The anomaly detection unit uses a camera to capture the environment image of the workshop, and identifies the location information of the staff, the operation information of the transport vehicle and the road condition information of the transport channel based on the image data; The abnormal analysis unit generates dangerous areas of the workshop based on the real-time production data of the equipment in the workshop, determines the area where the staff is located based on the staff's location information, predicts the staff's walking trajectory, and identifies the transportation status of the transport vehicle; When the alarm trigger unit detects that a worker is in a dangerous area or in a transport channel, it will use an alarm to remind the worker to evacuate. When the transport vehicle deviates from the transport channel or overturns, the alarm will be triggered and feedback will be given to the workshop manager.

8. The production collaborative scheduling management system for a magnesium metal reduction workshop according to claim 1 is characterized by: The linkage relationship between the equipment includes: the linkage relationship between the magnesium car and the reduction furnace, the linkage relationship between the slag car and the reduction furnace, the linkage relationship between the material car and the reduction furnace, and the linkage relationship between the transport cars.

9. A magnesium metal reduction workshop production collaborative scheduling management system according to claim 2, characterized in that: The bottleneck identification mechanism comprises the following steps: Step 1: Analyze potential factors that cause the actual production progress to fail to meet the target production plan, including equipment failure, raw material shortage, and insufficient staffing; Step 2: Analyze the causes of potential factors and their impact on production progress, and determine the bottleneck factors.

10. A magnesium metal reduction workshop production collaborative scheduling management system according to claim 5, characterized in that: The conflict points of the scheduling strategy include: equipment use conflict, task allocation conflict, and production schedule conflict identification.

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