Digital workshop production progress intelligent control system adaptive to lithium battery recovery

Abstract

The invention belongs to the field of lithium battery recovery, relates to a data analysis technology, is used for solving the problem that key equipment and key connection processes cannot be screened according to the stage productivity state of each production line in the prior art, and particularly relates to a digital workshop production progress intelligent control system adaptive to lithium battery recovery, which comprises an intelligent control platform, the intelligent control platform is in communication connection with a capacity monitoring module, an influence analysis module, a maintenance management module and a storage module; the capacity monitoring module is used for carrying out capacity monitoring analysis on the lithium battery recovery production line in the digital workshop and acquiring a capacity coefficient of a monitored object in an execution process; according to the invention, capacity monitoring analysis can be carried out on the lithium battery recovery production line in the digital workshop, independent statistics is carried out on the capacity state of each recovery production line in the digital workshop, then numerical calculation is carried out in combination with the duration of the execution process to obtain the capacity coefficient, and the degree of the production state of the execution process is evaluated according to the capacity coefficient.

Description

Technical Field

[0001] The present invention belongs to the field of lithium battery recycling and relates to data analysis technology, specifically to a digital workshop production progress intelligent control system suitable for lithium battery recycling. Background Art

[0002] Lithium battery recycling refers to the physical, chemical and other treatment of waste lithium batteries to extract their internal materials and reshape their utilization value; with the development of science and technology, lithium batteries are widely used in 3C electronics, new energy vehicles and other fields, and recycling has become an inevitable choice to reduce environmental pollution and improve economic benefits.

[0003] The invention patent with announcement number CN116700282A discloses a cluster control method and system for multiple robots in an unmanned workshop. The cluster control method regulates non-working robots in idle areas based on work assistance logic, and temporarily incorporates non-working robots into non-staff robots in busy areas. At this time, the non-working robots serve as non-staff robots and enter the busy section in the busy area; however, the control method cannot screen key equipment and key connection processes according to the phased production capacity status of each production line, and thus cannot timely maintain and optimize the key equipment of all production lines, resulting in the overall production capacity cannot be improved and the production progress cannot be effectively controlled.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a digital workshop production progress intelligent control system suitable for lithium battery recycling, which is used to solve the problem that the existing technology cannot screen key equipment and key connection processes according to the staged production capacity status of each production line;

[0006] The technical problem to be solved by the present invention is: how to provide a digital workshop production progress intelligent control system suitable for lithium battery recycling that can screen key equipment and key connection processes according to the phased production capacity status of each production line.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A digital workshop production progress intelligent control system suitable for lithium battery recycling, including an intelligent control platform, which is communicatively connected to a production capacity monitoring module, an impact analysis module, a maintenance management module, and a storage module;

[0009] The capacity monitoring module is used to perform capacity monitoring and analysis on the lithium battery recycling production line in the digital workshop: the lithium battery recycling production line in the digital workshop is marked as a monitoring object, each monitoring object includes a recycling device HSi, i=1, 2, ..., n, n is a positive integer, and the process from the monitoring object starting to process the waste battery raw materials to the waste battery raw materials completing the recovery of valuable metals is marked as the execution process of the monitoring object, the capacity coefficient of the monitoring object during the execution process is obtained, and the capacity coefficients of all monitoring objects are sent to the impact analysis module through the intelligent control module;

[0010] The impact analysis module is used to analyze the factors affecting the lithium battery recycling capacity of the digital workshop: after all the monitoring objects have completed an execution process, the monitoring objects are arranged in descending order according to the capacity coefficient to obtain a capacity sequence, the first L1 monitoring objects in the capacity sequence are intercepted and formed into a positive impact set, the last L1 monitoring objects in the capacity sequence are intercepted to form a negative impact set, the positive impact set and the negative impact set are cleaned respectively to obtain positive impact objects and negative impact objects; the execution parameter set of the recycling equipment HSi is marked by the positive impact objects and the negative impact objects;

[0011] The maintenance management module is used to perform maintenance management analysis on the lithium battery recycling production line in the digital workshop: numerically calculate the execution parameter set of the recycling equipment HSi to obtain the operation influence coefficient YYi and the connection influence coefficient XYi of the recycling equipment HSi, mark the recycling equipment HSi with the largest operation influence coefficient YXi as the operation optimization equipment, and mark the recycling equipment HSi with the largest connection influence coefficient XYi as the connection optimization equipment; send the operation optimization equipment and the connection optimization equipment to the mobile phone terminal of the manager through the intelligent control platform.

[0012] Furthermore, the process of obtaining the capacity coefficient includes: obtaining the total weight of valuable metals recovered during the execution process of the monitored object and marking it as value data, marking the duration of the execution process of the monitored object as execution data, and marking the ratio of the value data to the execution data as the capacity coefficient of the execution process.

[0013] Furthermore, the specific process of cleaning the positive impact set includes: performing variance calculation on the capacity coefficients corresponding to all monitoring objects in the positive impact set to obtain a positive deviation value, and comparing the positive deviation value with the deviation threshold: if the positive deviation value is less than the deviation threshold, then the monitoring object with the largest capacity coefficient in the positive impact set is marked as a positive impact object, and the corresponding execution process is marked as a positive impact process; if the positive deviation value is greater than or equal to the deviation threshold, then the monitoring objects with the largest and smallest capacity coefficients in the positive impact set are eliminated, and then the positive deviation value is recalculated, and so on, until the positive deviation value is less than the deviation threshold.

[0014] Furthermore, the specific process of cleaning the reverse impact set includes: performing variance calculation on the capacity coefficients corresponding to all monitoring objects in the reverse impact set to obtain a reverse deviation value, and comparing the reverse deviation value with the deviation threshold: if the reverse deviation value is less than the deviation threshold, then the monitoring object with the smallest capacity coefficient in the reverse impact set is marked as a reverse impact object, and the corresponding execution process is marked as a reverse impact process; if the reverse deviation value is greater than or equal to the deviation threshold, then the monitoring objects with the largest and smallest capacity coefficients in the reverse impact set are eliminated, and then the reverse deviation value is recalculated, and so on, until the reverse deviation value is less than the deviation threshold.

[0015] Furthermore, the process of acquiring the execution parameter set of the recycling equipment HSi includes: marking the operating time of the recycling equipment HSi in the positive influence process and the operating time in the reverse influence process as the forward operation value ZYi and the reverse operation value FYi respectively; marking the time interval from the end of the operation of the recycling equipment HSi in the positive influence process to the start of the operation of the recycling equipment HSi+1 as the forward connection value ZXi, and marking the time interval from the end of the operation of the recycling equipment HSi in the reverse influence process to the start of the operation of the recycling equipment HSi+1 as the reverse connection value FXi; the execution parameter set of the recycling equipment HSi is composed of the forward operation value ZYi, the reverse operation value FYi, the forward connection value ZXi and the reverse connection value FXi of the recycling equipment HSi.

[0016] Furthermore, the specific process of the maintenance management module performing maintenance management analysis on the lithium battery recycling production line in the digital workshop includes: generating a monitoring cycle, obtaining the forward mark value ZB and the reverse mark value FB of the monitored object at the end of the monitoring cycle; obtaining the overall coefficient ZT of the monitored object during the monitoring cycle by numerically calculating the forward mark value ZB and the reverse mark value FB; marking the L2 monitored objects with the smallest overall coefficient ZT as overall optimization objects, and sending the overall optimization objects to the mobile phone terminal of the manager through the intelligent control platform.

[0017] Furthermore, the positive mark value ZF is the number of times the monitored object is classified into the positive impact set within the monitoring period, and the negative mark value FB is the number of times the monitored object is classified into the negative impact set within the monitoring period.

[0018] The present invention has the following beneficial effects:

[0019] 1. The capacity monitoring module can be used to monitor and analyze the capacity of the lithium battery recycling production line in the digital workshop, independently count the capacity status of each recycling production line in the digital workshop, and then calculate the capacity coefficient based on the execution time. The production status of the execution process is evaluated according to the capacity coefficient;

[0020] 2. The impact analysis module can be used to analyze the factors affecting the lithium battery recycling capacity of the digital workshop. After data cleaning of the positive impact set and the reverse impact set, the positive impact process and the reverse impact process are obtained. Then, the operating parameters of the recycling equipment in the positive impact process and the reverse impact process are compared and analyzed to obtain the execution parameter set. The impact of the recycling equipment on the capacity is fed back through the execution parameter set.

[0021] 3. The maintenance management module can be used to perform maintenance management analysis on the lithium battery recycling production line in the digital workshop and obtain operation optimization equipment and connection optimization equipment. The equipment that needs key maintenance and the connection process that needs key optimization can then be marked, thereby improving the overall production capacity of all production lines and reducing the difficulty of production progress control. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0024] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0025] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Embodiment 1: Figure 1 As shown, a digital workshop production progress intelligent control system suitable for lithium battery recycling includes an intelligent control platform, which is communicatively connected to a capacity monitoring module, an impact analysis module, a maintenance management module and a storage module.

[0027] The capacity monitoring module is used to monitor and analyze the capacity of the lithium battery recycling production line in the digital workshop: the lithium battery recycling production line in the digital workshop is marked as a monitoring object, each monitoring object includes a recycling device HSi, i=1, 2,..., n, n is a positive integer, and the process from the monitoring object starting to process the waste battery raw materials to the waste battery raw materials completing the valuable metal recovery is marked as the execution process of the monitoring object, and the total weight of the valuable metals recovered by the monitoring object during the execution process is obtained and marked as value data. The valuable metals include cobalt, nickel, lithium, copper and aluminum; the duration of the execution process of the monitoring object is marked as execution data, and the ratio of the value data to the execution data is marked as the capacity coefficient of the execution process. The capacity coefficients of all monitoring objects are sent to the impact analysis module through the intelligent control module; the capacity status of each recycling production line in the digital workshop is independently counted, and then the capacity coefficient is obtained by numerical calculation combined with the duration of the execution process, and the production status of the execution process is evaluated according to the capacity coefficient.

[0028] The impact analysis module is used to analyze the factors affecting the lithium battery recycling capacity of the digital workshop: after all the monitoring objects have completed an execution process, the monitoring objects are arranged in descending order of capacity coefficient to obtain a capacity sequence, the first L1 monitoring objects in the capacity sequence are intercepted and formed into a positive impact set, and the last L1 monitoring objects in the capacity sequence are intercepted to form a reverse impact set. The positive impact set and the reverse impact set are cleaned and processed to obtain positive impact objects and reverse impact objects respectively: the variance of the capacity coefficients corresponding to all monitoring objects in the positive impact set is calculated to obtain a positive deviation value, and the positive deviation value is compared with the deviation threshold: if the positive deviation value is less than the deviation threshold, the monitoring object with the largest capacity coefficient in the positive impact set is marked as a positive impact object, and the corresponding execution process is marked as a positive impact process; if the positive deviation value is greater than or equal to the deviation threshold, the monitoring objects with the largest and smallest capacity coefficients in the positive impact set are eliminated, and then the positive deviation value is recalculated, and so on, until the positive deviation value is less than the deviation threshold;

[0029] The variance of the capacity coefficients corresponding to all monitoring objects in the reverse impact set is calculated to obtain the reverse deviation value, and the reverse deviation value is compared with the deviation threshold: if the reverse deviation value is less than the deviation threshold, the monitoring object with the smallest capacity coefficient in the reverse impact set is marked as the reverse impact object, and the corresponding execution process is marked as the reverse impact process; if the reverse deviation value is greater than or equal to the deviation threshold, the monitoring objects with the largest and smallest capacity coefficients in the reverse impact set are eliminated, and then the reverse deviation value is recalculated, and so on, until the reverse deviation value is less than the deviation threshold;

[0030] The operation time of the recycling equipment HSi in the positive influence process and the operation time in the reverse influence process are marked as the forward operation value ZYi and the reverse operation value FYi respectively; the time interval from the end of the operation of the recycling equipment HSi in the positive influence process to the start of the operation of the recycling equipment HSi+1 is marked as the forward connection value ZXi, and the time interval from the end of the operation of the recycling equipment HSi in the reverse influence process to the start of the operation of the recycling equipment HSi+1 is marked as the reverse connection value FXi; the forward operation value ZYi, the reverse operation value FYi, the forward connection value ZXi and the reverse connection value FXi of the recycling equipment HSi constitute the execution parameter set of the recycling equipment HSi, and all the execution parameter sets of the recycling equipment HSi are sent to the maintenance management module through the intelligent control platform; the forward influence set and the reverse influence set are respectively cleaned to obtain the forward influence process and the reverse influence process, and then the execution parameter set is obtained by comparing and analyzing the operation parameters of the recycling equipment in the forward influence process and the reverse influence process, and the influence degree of the recycling equipment on the production capacity is fed back through the execution parameter set.

[0031] The maintenance management module is used to perform maintenance management analysis on the lithium battery recycling production line in the digital workshop: and The operation influence coefficient YYi and connection influence coefficient XYi of the recycling equipment HSi are obtained, and the recycling equipment HSi with the largest operation influence coefficient YXi is marked as the operation optimization equipment, and the recycling equipment HSi with the largest connection influence coefficient XYi is marked as the connection optimization equipment; the operation optimization equipment and the connection optimization equipment are sent to the mobile terminal of the manager through the intelligent control platform.

[0032] Generate a monitoring cycle, and obtain the positive marking value ZB and the reverse marking value FB of the monitored object at the end of the monitoring cycle. The positive marking value ZF is the number of times the monitored object is classified into the positive impact set during the monitoring cycle, and the reverse marking value FB is the number of times the monitored object is classified into the reverse impact set during the monitoring cycle. The overall coefficient ZT of the monitored object during the monitoring cycle is obtained by the formula ZT=k1×ZF-k2×FB, where k1 and k2 are both proportional coefficients, and k1>k2>1. The L2 monitored objects with the smallest overall coefficient ZT value are marked as overall optimization objects, and the overall optimization objects are sent to the mobile phone terminal of the manager through the intelligent control platform. The lithium battery recycling production line in the digital workshop is maintained, managed and analyzed, and the operation optimization equipment and connection optimization equipment are obtained. Then, the equipment that needs to be maintained and the connection process that needs to be optimized can be marked, thereby improving the production capacity of all production lines as a whole and reducing the difficulty of production progress control.

[0033] Embodiment 2: Figure 2 As shown, the intelligent control method for production progress of a digital workshop suitable for lithium battery recycling includes the following steps:

[0034] Step 1: Conduct capacity monitoring and analysis on the lithium battery recycling production line in the digital workshop: Mark the lithium battery recycling production line in the digital workshop as the monitoring object, and obtain the capacity coefficient of the monitoring object during the execution process;

[0035] Step 2: Analyze the factors affecting the lithium battery recycling capacity of the digital workshop: After all monitored objects have completed an execution process, mark the positively affected objects and the negatively affected objects, and then obtain the execution parameter set of the recycling equipment HSi;

[0036] Step 3: Perform maintenance management analysis on the lithium battery recycling production line in the digital workshop, perform numerical calculation on the execution parameter set of the recycling coefficient HSi to obtain the operation influence coefficient YYi and the connection influence coefficient XYi, and mark the operation optimization equipment and the connection optimization equipment through the operation influence coefficient YYi and the connection influence coefficient XYi;

[0037] Step 4: Generate a monitoring cycle. At the end of the monitoring cycle, obtain the forward marking value ZB and the reverse marking value FB of the monitored object and perform numerical calculations to obtain the overall coefficient ZT of the monitored object. Use the overall coefficient ZT to mark the overall optimization object of the monitoring cycle.

[0038] The intelligent control system for production progress of a digital workshop adapted for lithium battery recycling, when working, marks the lithium battery recycling production line in the digital workshop as a monitoring object, and obtains the capacity coefficient of the monitoring object during the execution process; after all the monitoring objects have completed an execution process, the positive impact objects and the negative impact objects are marked, and then the execution parameter set of the recycling equipment HSi is obtained; maintenance management and analysis are performed on the lithium battery recycling production line in the digital workshop, and the execution parameter set of the recycling coefficient HSi is numerically calculated to obtain the operation impact coefficient YYi and the connection impact coefficient XYi, and the operation optimization equipment and the connection optimization equipment are marked by the operation impact coefficient YYi and the connection impact coefficient XYi; a monitoring cycle is generated, and at the end of the monitoring cycle, the positive marking value ZB and the reverse marking value FB of the monitoring object are obtained and numerically calculated to obtain the overall coefficient ZT of the monitoring object, and the overall optimization object of the monitoring cycle is marked by the overall coefficient ZT.

[0039] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0040] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula ZT = k1 × ZF-k2 × FB; technicians in this field collect multiple groups of sample data and set corresponding overall coefficients for each group of sample data; substitute the set overall coefficients and the collected sample data into the formula, any two formulas constitute a binary linear equation system, screen the calculated coefficients and take the average, and obtain the values ​​of k1 and k2 as 2.85 and 2.32 respectively;

[0041] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding overall coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the overall coefficient is proportional to the value of the positive mark value.

[0042] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0043] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The digital workshop production progress intelligent control system suitable for lithium battery recycling is characterized by: It includes an intelligent control platform, which is communicatively connected to a capacity monitoring module, an impact analysis module, a maintenance management module and a storage module; The capacity monitoring module is used to perform capacity monitoring and analysis on the lithium battery recycling production line in the digital workshop: the lithium battery recycling production line in the digital workshop is marked as a monitoring object, each monitoring object includes a recycling device HSi, i=1, 2, ..., n, n is a positive integer, and the process from the monitoring object starting to process the waste battery raw materials to the waste battery raw materials completing the recovery of valuable metals is marked as the execution process of the monitoring object, the capacity coefficient of the monitoring object during the execution process is obtained, and the capacity coefficients of all monitoring objects are sent to the impact analysis module through the intelligent control module; The impact analysis module is used to analyze the factors affecting the lithium battery recycling capacity of the digital workshop: after all the monitoring objects have completed an execution process, the monitoring objects are arranged in descending order according to the capacity coefficient to obtain a capacity sequence, the first L1 monitoring objects in the capacity sequence are intercepted and formed into a positive impact set, the last L1 monitoring objects in the capacity sequence are intercepted to form a negative impact set, the positive impact set and the negative impact set are cleaned respectively to obtain positive impact objects and negative impact objects; the execution parameter set of the recycling equipment HSi is marked by the positive impact objects and the negative impact objects; The maintenance management module is used to perform maintenance management analysis on the lithium battery recycling production line in the digital workshop: numerically calculate the execution parameter set of the recycling equipment HSi to obtain the operation influence coefficient YYi and the connection influence coefficient XYi of the recycling equipment HSi, mark the recycling equipment HSi with the largest operation influence coefficient YXi as the operation optimization equipment, and mark the recycling equipment HSi with the largest connection influence coefficient XYi as the connection optimization equipment; send the operation optimization equipment and the connection optimization equipment to the mobile phone terminal of the manager through the intelligent control platform.

2. According to claim 1, the digital workshop production progress intelligent control system suitable for lithium battery recycling is characterized in that: The process of obtaining the capacity coefficient includes: obtaining the total weight of valuable metals recovered during the execution process of the monitored object and marking it as value data, marking the duration of the execution process of the monitored object as execution data, and marking the ratio of the value data to the execution data as the capacity coefficient of the execution process.

3. The digital workshop production progress intelligent control system suitable for lithium battery recycling according to claim 2 is characterized in that: The specific process of cleaning the positive impact set includes: performing variance calculation on the capacity coefficients corresponding to all monitoring objects in the positive impact set to obtain a positive deviation value, and comparing the positive deviation value with the deviation threshold: if the positive deviation value is less than the deviation threshold, the monitoring object with the largest capacity coefficient in the positive impact set is marked as a positive impact object, and the corresponding execution process is marked as a positive impact process; if the positive deviation value is greater than or equal to the deviation threshold, the monitoring objects with the largest and smallest capacity coefficients in the positive impact set are eliminated, and then the positive deviation value is recalculated, and so on, until the positive deviation value is less than the deviation threshold.

4. The digital workshop production progress intelligent control system suitable for lithium battery recycling according to claim 3 is characterized in that: The specific process of cleaning the reverse impact set includes: performing variance calculation on the capacity coefficients corresponding to all monitoring objects in the reverse impact set to obtain a reverse deviation value, and comparing the reverse deviation value with the deviation threshold: if the reverse deviation value is less than the deviation threshold, the monitoring object with the smallest capacity coefficient in the reverse impact set is marked as a reverse impact object, and the corresponding execution process is marked as a reverse impact process; if the reverse deviation value is greater than or equal to the deviation threshold, the monitoring objects with the largest and smallest capacity coefficients in the reverse impact set are eliminated, and then the reverse deviation value is recalculated, and so on, until the reverse deviation value is less than the deviation threshold.

5. According to claim 4, the digital workshop production progress intelligent control system suitable for lithium battery recycling is characterized in that: The process of acquiring the execution parameter set of the recycling equipment HSi includes: marking the operating time of the recycling equipment HSi in the positive influence process and the operating time in the reverse influence process as the forward operation value ZYi and the reverse operation value FYi respectively; marking the time interval from the end of the operation of the recycling equipment HSi in the positive influence process to the start of the operation of the recycling equipment HSi+1 as the forward connection value ZXi, and marking the time interval from the end of the operation of the recycling equipment HSi in the reverse influence process to the start of the operation of the recycling equipment HSi+1 as the reverse connection value FXi; the execution parameter set of the recycling equipment HSi is composed of the forward operation value ZYi, the reverse operation value FYi, the forward connection value ZXi and the reverse connection value FXi of the recycling equipment HSi.

6. The digital workshop production progress intelligent control system suitable for lithium battery recycling according to claim 5 is characterized in that: The specific process of the maintenance management module performing maintenance management and analysis on the lithium battery recycling production line in the digital workshop includes: generating a monitoring cycle, obtaining the forward mark value ZB and the reverse mark value FB of the monitored object at the end of the monitoring cycle; obtaining the overall coefficient ZT of the monitored object during the monitoring cycle by numerically calculating the forward mark value ZB and the reverse mark value FB; marking the L2 monitored objects with the smallest overall coefficient ZT as overall optimization objects, and sending the overall optimization objects to the mobile terminal of the manager through the intelligent control platform.

7. The digital workshop production progress intelligent control system suitable for lithium battery recycling according to claim 6 is characterized in that: The positive mark value ZF is the number of times the monitored object is classified into the positive impact set during the monitoring period, and the negative mark value FB is the number of times the monitored object is classified into the negative impact set during the monitoring period.

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