Tobacco logistics equipment alarm data analysis method and system, storage medium and terminal

Abstract

The invention provides a tobacco logistics equipment alarm data analysis method and system, a storage medium and a terminal, and the method comprises the following steps: obtaining daily alarm data of tobacco logistics equipment, and storing the daily alarm data in a database; and analyzing the daily alarm data in the database to obtain fault equipment information. According to the alarm data analysis method and system for the tobacco logistics equipment, the storage medium and the terminal, a basis is provided for preventive maintenance of the tobacco logistics equipment by analyzing massive alarm data.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a method, system, storage medium and terminal for analyzing alarm data of tobacco logistics equipment. Background Art

[0002] Warehouse Management System (WMS) is software, information system, and information tool, a tool used to control, coordinate and optimize the movement of goods, work processes and field operations within the warehouse. Warehouse management system is used to effectively manage warehouse business processes and field operations, including receiving, shelving, picking, reviewing, transferring, transferring, inventory, etc. It also includes support for radio frequency communication (RF), allowing real-time data transmission between the system and warehouse personnel, and can also maximize space utilization and minimize material handling through automated storage processes, thereby helping growing companies simplify the processes of warehousing, outbound storage, and inventory management, which is more efficient than traditional manual processes. A powerful warehouse management system helps improve warehouse management, thereby improving accuracy, reducing errors, and reducing labor costs, thereby saving a lot of costs.

[0003] The warehouse management system consists of the raw material formula library LT system, the auxiliary material balance library DM system, and the finished product cigarette library FG system. In the prior art, the tobacco logistics equipment failure alarm system is applied to the internal logistics link of cigarette production enterprises to alarm the abnormal status of equipment. Usually, there are about 500 to 800 alarm messages of various types of equipment every day. The alarm information includes equipment number, occurrence time, end time, alarm code, alarm information description and other contents.

[0004] However, the existing tobacco logistics equipment fault alarm has the following shortcomings:

[0005] (1) The amount of alarm data stored is limited

[0006] The alarm information of each warehouse system in the warehouse management system is numbered separately in sequence. When the number exceeds 999999, it is renumbered from 0, resulting in a storage limit of 999999 for the number of alarm information of each warehouse system.

[0007] (2) Massive alarm data is difficult to analyze manually one by one

[0008] The current warehouse management system generates about 500 to 800 alarm messages per day. It is difficult to analyze the massive alarm information manually, and it is even more difficult to mine the alarm patterns and the equipment status information they imply.

[0009] (3) Alarm data does not include processing suggestions

[0010] The alarm information of the warehouse management system only includes the equipment number, occurrence time, end time, alarm code, alarm information description, etc. The alarm information has no direct guidance for operation and maintenance, and has not formed a valuable knowledge base. Summary of the invention

[0011] In view of the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a tobacco logistics equipment alarm data analysis method, system, storage medium and terminal, which provide a basis for preventive maintenance of tobacco logistics equipment by analyzing massive alarm data.

[0012] In a first aspect, the present invention provides a method for analyzing alarm data of tobacco logistics equipment, the method comprising the following steps: obtaining daily alarm data of tobacco logistics equipment, and storing the daily alarm data in a database; analyzing the daily alarm data in the database to obtain faulty equipment information.

[0013] In an implementation of the first aspect, obtaining historical alarm data of tobacco logistics equipment and storing the historical alarm data in a database includes the following steps:

[0014] Export daily alarm data of tobacco logistics equipment from the warehouse management system;

[0015] The imported daily alarm data is compared with the existing alarm data in the database, and the difference alarm data obtained by the comparison is stored in sequence after the existing alarm data.

[0016] In an implementation of the first aspect, the database adopts a SQL Server database.

[0017] In an implementation of the first aspect, analyzing the daily alarm data in the database to obtain faulty device information includes the following steps:

[0018] Analyze the daily alarm data to obtain the alarm type and alarm quantity of each tobacco logistics equipment;

[0019] When the number of alarms of a certain alarm type issued by the tobacco logistics equipment in a single day exceeds the upper quartile of the alarm data in a single day, the tobacco logistics equipment is determined to be faulty.

[0020] In an implementation of the first aspect, analyzing the daily alarm data in the database to obtain faulty device information includes the following steps:

[0021] Analyze the daily alarm data to obtain the daily alarm times of each tobacco logistics equipment;

[0022] When the number of daily alarms of the tobacco logistics equipment increases for three consecutive days, it is determined that the tobacco logistics equipment is faulty.

[0023] In an implementation of the first aspect, analyzing the daily alarm data in the database to obtain faulty device information includes the following steps:

[0024] Analyze the daily alarm data to obtain the daily alarm quantity and material flow of each tobacco logistics equipment;

[0025] A fault path node is determined based on the single-day alarm quantity and the material flow, and the equipment fault corresponding to the fault path node is determined.

[0026] In an implementation of the first aspect, it also includes obtaining maintenance information of the faulty logistics tobacco equipment and building a fault maintenance knowledge base based on the maintenance information.

[0027] In a second aspect, the present invention provides a tobacco logistics equipment alarm data analysis system, the system comprising a data acquisition module and an analysis module;

[0028] The data acquisition module is used to acquire daily alarm data of tobacco logistics equipment and store the daily alarm data in a database;

[0029] The analysis module is used to analyze the daily alarm data in the database to obtain faulty equipment information.

[0030] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned tobacco logistics equipment alarm data analysis method.

[0031] In a fourth aspect, the present invention provides a tobacco logistics equipment alarm data analysis terminal, comprising: a processor and a memory;

[0032] The memory is used to store computer programs;

[0033] The processor is used to execute the computer program stored in the memory so that the tobacco logistics equipment alarm data analysis terminal executes the above-mentioned tobacco logistics equipment alarm data analysis method.

[0034] In a fifth aspect, the present invention provides a tobacco logistics equipment alarm data analysis system, comprising the above-mentioned tobacco logistics equipment alarm data analysis terminal and database;

[0035] The database is used to store the daily alarm data imported by the warehouse management system, and provide the daily alarm data to the tobacco logistics equipment alarm data analysis terminal.

[0036] As described above, the tobacco logistics equipment alarm data analysis method, system, storage medium and terminal of the present invention have the following beneficial effects:

[0037] (1) It can be applied to the internal logistics of cigarette manufacturing enterprises. By analyzing and mining the massive historical alarm data of tobacco logistics equipment, the abnormal status of the equipment and its status trend can be discovered, thereby achieving preventive maintenance of the equipment.

[0038] (2) By classifying and organizing the handling methods of tobacco logistics equipment alarms, a fault maintenance knowledge base is formed to improve the efficiency of troubleshooting;

[0039] (3) The storage capacity is effectively expanded through database backup and other means. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Shown is a flow chart of a tobacco logistics equipment alarm data analysis method in one embodiment of the present invention;

[0041] Figure 2 Shown is a schematic diagram of a framework of a tobacco logistics equipment alarm data analysis method in one embodiment of the present invention;

[0042] Figure 3 Shown is a schematic structural diagram of a tobacco logistics equipment alarm data analysis system in one embodiment of the present invention;

[0043] Figure 4 Shown is a schematic structural diagram of a tobacco logistics equipment alarm data analysis terminal in one embodiment of the present invention;

[0044] Figure 5 Shown is a schematic diagram of the structure of the tobacco logistics equipment alarm data analysis system in another embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0046] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0047] The tobacco logistics equipment alarm data analysis method, system, storage medium and terminal of the present invention can realize the analysis and mining of massive historical alarm data by grading and layering the alarm information of the existing warehouse management system; realize the preventive maintenance of equipment by establishing an equipment failure trend model; and form a maintenance experience knowledge base by classifying and arranging the processing methods of equipment alarms to improve the equipment maintenance efficiency. Preferably, the tobacco logistics equipment alarm data analysis method, system, storage medium and terminal of the present invention can be realized by using SQL Server database as a data storage carrier and Python programming language as a program compilation platform.

[0048] like Figure 1 and Figure 2 As shown, in one embodiment, the tobacco logistics equipment alarm data analysis method of the present invention includes steps S1 and S2.

[0049] Step S1, obtaining daily alarm data of tobacco logistics equipment, and storing the daily alarm data in a database.

[0050] Specifically, the daily alarm data of tobacco logistics equipment is generated in the warehouse management system. The daily alarm data in the warehouse management system is exported through Excel. At the same time, the daily alarm data of the tobacco logistics equipment are stored in the database. When the daily alarm data with information is exported, the exported daily alarm data is required to be compared with the existing alarm data in the database, and the difference alarm data obtained by the comparison is renumbered and stored in sequence after the existing alarm data. Therefore, the daily alarm data is stored in the database and renumbered, which breaks through the limitation of the existing warehouse management system that can only store 999999 alarm data, and the storage capacity is expanded by means of database backup.

[0051] In one embodiment, the database adopts a SQL Server database.

[0052] Step S2: Analyze the daily alarm data in the database to obtain faulty equipment information.

[0053] Specifically, the daily alarm data in the database is analyzed in terms of the number of alarms, changes in the number of alarms, and the relationship between the number of alarms and material flow, so as to mine the operating status information of the tobacco logistics equipment, thereby realizing the accurate location of the faulty equipment.

[0054] Among them, the daily alarm data is analyzed to obtain the alarm type and alarm number of each tobacco logistics equipment. For each tobacco logistics equipment, when the number of alarms for a certain alarm type of the tobacco logistics equipment in a single day exceeds the upper quartile of the alarm data in a single day, it is determined that the tobacco logistics equipment is faulty and needs maintenance. In the present invention, the "upper quartile" is used as the judgment threshold for the abnormal alarm frequency of a single-machine device in a single day, which can effectively mine the equipment failure predictive information implicit in the fault data.

[0055] At the same time, the daily alarm data is analyzed to obtain the daily alarm times of each tobacco logistics equipment. For each tobacco logistics equipment, when the daily alarm times of the tobacco logistics equipment increase for three consecutive days, it is determined that the tobacco logistics equipment is faulty and needs maintenance.

[0056] In addition, the daily alarm data is analyzed to obtain the number of daily alarms and material flow of each tobacco logistics equipment. The material flow can be the number of cigarette packs in the raw material formula library. The fault path node is determined based on the number of daily alarms and the material flow, and the equipment fault corresponding to the fault path node is determined. The path node where the material flow has a greater impact on the number of daily alarms is taken as the fault path node, and preventive maintenance is performed to improve the equipment health level.

[0057] In one embodiment, after the maintenance personnel repair the faulty equipment, the maintenance information of the faulty logistics tobacco equipment is obtained and entered into the database, thereby constructing a fault maintenance knowledge base based on the maintenance information. The fault maintenance knowledge base can be used during the operation and maintenance process to reduce the troubleshooting time and improve the troubleshooting efficiency.

[0058] The protection scope of the tobacco logistics equipment alarm data analysis method described in the embodiment of the present invention is not limited to the execution order of the steps listed in this embodiment. All solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present invention are included in the protection scope of the present invention.

[0059] An embodiment of the present invention also provides a tobacco logistics equipment alarm data analysis system, which can implement the tobacco logistics equipment alarm data analysis method described in the present invention. However, the implementation device of the tobacco logistics equipment alarm data analysis system described in the present invention includes but is not limited to the structure of the tobacco logistics equipment alarm data analysis system listed in this embodiment. All structural deformations and replacements of the prior art made according to the principles of the present invention are included in the protection scope of the present invention.

[0060] like Figure 3 As shown, in one embodiment, the tobacco logistics equipment alarm data analysis system of the present invention includes a data acquisition module 31 and an analysis module 32 .

[0061] The data acquisition module 31 is used to acquire daily alarm data of tobacco logistics equipment and store the daily alarm data in a database.

[0062] The analysis module 32 is connected to the data acquisition module 31 and is used to analyze the daily alarm data in the database and obtain faulty equipment information.

[0063] Among them, the structure and principle of the data acquisition module 31 and the analysis module 32 correspond one by one to the steps in the above-mentioned tobacco logistics equipment alarm data analysis method, so they are not repeated here.

[0064] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software called by processing elements, or they can all be implemented in the form of hardware, or some modules can be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. For example: the x module can be a separately established processing element, or it can be integrated in a certain chip of the above device. In addition, the x module can also be stored in the memory of the above device in the form of program code, and called and executed by a certain processing element of the above device. The implementation of other modules is similar. These modules can be integrated together in whole or in part, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software. The above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASIC), one or more microprocessors (DSP), one or more field programmable gate arrays (FPGA), etc. When a module is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call program code. These modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0065] The storage medium of the present invention stores a computer program, which implements the above tobacco logistics equipment alarm data analysis method when executed by the processor. Preferably, the storage medium includes: ROM, RAM, disk, U disk, memory card or CD and other media that can store program codes.

[0066] like Figure 4 As shown, in one embodiment, the tobacco logistics equipment alarm data analysis terminal of the present invention includes: a processor 41 and a memory 42.

[0067] The memory 42 is used to store computer programs, and includes: ROM, RAM, disk, USB flash drive, memory card, optical disk, and other media that can store program codes.

[0068] The processor 41 is connected to the memory 42 and is used to execute the computer program stored in the memory so that the tobacco logistics equipment alarm data analysis terminal executes the above-mentioned tobacco logistics equipment alarm data analysis method.

[0069] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0070] like Figure 5 As shown, in one embodiment, the tobacco logistics equipment alarm data analysis system of the present invention includes the above-mentioned tobacco logistics equipment alarm data analysis terminal 51 and database 52.

[0071] The database 52 is connected to the tobacco logistics equipment alarm data analysis terminal 51 and is used to store the daily alarm data imported by the warehouse management system and provide the daily alarm data to the tobacco logistics equipment alarm data analysis terminal 51 .

[0072] In summary, the tobacco logistics equipment alarm data analysis method, system, storage medium and terminal of the present invention can be applied to the internal logistics link of cigarette production enterprises. By analyzing and mining the massive historical alarm data of tobacco logistics equipment, the abnormal state of the equipment and its state trend can be discovered, thereby realizing the preventive maintenance of the equipment; by classifying and arranging the processing methods of tobacco logistics equipment alarms, a fault maintenance knowledge base is formed, thereby improving the troubleshooting efficiency; and the expansion of storage capacity is effectively realized through database backup and other methods. Therefore, the present invention effectively overcomes the various shortcomings of the prior art and has a high industrial utilization value.

[0073] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A tobacco logistics equipment alarm data analysis method, characterized in that: The method comprises the following steps: Acquire daily alarm data of tobacco logistics equipment, and store the daily alarm data in a database; The daily alarm data in the database is analyzed to obtain faulty equipment information.

2. The tobacco logistics equipment alarm data analysis method according to claim 1, characterized in that: Acquiring historical alarm data of tobacco logistics equipment and storing the historical alarm data in a database comprises the following steps: Export daily alarm data of tobacco logistics equipment from the warehouse management system; The imported daily alarm data is compared with the existing alarm data in the database, and the difference alarm data obtained by the comparison is stored in sequence after the existing alarm data.

3. The tobacco logistics equipment alarm data analysis method according to claim 1, characterized in that: Analyzing the daily alarm data in the database to obtain faulty equipment information includes the following steps: Analyze the daily alarm data to obtain the alarm type and alarm quantity of each tobacco logistics equipment; When the number of alarms of a certain alarm type issued by the tobacco logistics equipment in a single day exceeds the upper quartile of the alarm data in a single day, the tobacco logistics equipment is determined to be faulty.

4. The tobacco logistics equipment alarm data analysis method according to claim 1, characterized in that: Analyzing the daily alarm data in the database to obtain faulty equipment information includes the following steps: Analyze the daily alarm data to obtain the daily alarm times of each tobacco logistics equipment; When the number of daily alarms of the tobacco logistics equipment increases for three consecutive days, it is determined that the tobacco logistics equipment is faulty.

5. The tobacco logistics equipment alarm data analysis method according to claim 1, characterized in that: Analyzing the daily alarm data in the database to obtain faulty equipment information includes the following steps: Analyze the daily alarm data to obtain the daily alarm quantity and material flow of each tobacco logistics equipment; A fault path node is determined based on the single-day alarm quantity and the material flow, and the equipment fault corresponding to the fault path node is determined.

6. The tobacco logistics equipment alarm data analysis method according to claim 1, characterized in that: It also includes obtaining maintenance information of faulty logistics tobacco equipment and building a fault maintenance knowledge base based on the maintenance information.

7. A tobacco logistics equipment alarm data analysis system, characterized in that: The system includes a data acquisition module and an analysis module; The data acquisition module is used to acquire daily alarm data of tobacco logistics equipment and store the daily alarm data in a database; The analysis module is used to analyze the daily alarm data in the database to obtain faulty equipment information.

8. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the tobacco logistics equipment alarm data analysis method described in any one of claims 1 to 6 is implemented.

9. A tobacco logistics equipment alarm data analysis terminal, characterized in that: include: Processor and memory; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory so that the tobacco logistics equipment alarm data analysis terminal executes the tobacco logistics equipment alarm data analysis method described in any one of claims 1 to 6.

10. A tobacco logistics equipment alarm data analysis system, characterized by: Including the tobacco logistics equipment alarm data analysis terminal and database as described in claim 9; The database is used to store the daily alarm data imported by the warehouse management system, and provide the daily alarm data to the tobacco logistics equipment alarm data analysis terminal.

Images