Spare part scheduling method and device
By obtaining park information and historical data to generate spare parts scheduling tables, the problem of cross-park spare parts scheduling is solved, and hardware repair speed and inventory management efficiency are improved.
Patent Information
- Application Number
- CN202411324173.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-23
- Publication Date
- 2025-01-07
AI Technical Summary
The existing technology cannot realize the coordinated scheduling of spare parts across multiple parks, resulting in limited hardware repair speed.
By obtaining the operating equipment information and historical consumption data of the park, a spare part dependency table and predicting consumption quantity are generated, a spare part schedule is generated based on these data, and spare part scheduling across parks is performed and spare part placement distribution table is updated.
The coordinated scheduling of spare parts across multiple parks has been realized, and the hardware repair speed and inventory management efficiency have been improved.
Smart Images
Figure CN119273065A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of hardware equipment operation and maintenance, and in particular to a method and device for scheduling spare parts. Background Art
[0002] In order to meet the business continuity supervision requirements of information systems, the key business systems of commercial banks, such as core business systems, are usually deployed simultaneously in multiple parks in multiple cities. The more mature and widely used multi-center model in the industry is the "two-site three-center" deployment solution. The "two sites" are usually two cities that are far away from each other, and the "three centers" usually refer to the production park in city 1, the disaster recovery park in the same city in city 1, and the disaster recovery park in a different location in city 2. The hardware equipment that constitutes the information system, including hosts, disks, network switches, physical optical fibers, etc., banks and other enterprises will centrally purchase equipment in proportion and store them in spare parts warehouses in each park. Maintenance personnel usually give priority to selecting the corresponding spare parts from the local spare parts warehouse to replace the faulty hardware. Once the hardware failure occurs and there is no inventory in the local park, it is necessary to call from other parks, which affects the speed of hardware repair. Therefore, it is necessary to dispatch spare parts to ensure that there are enough spare parts in the local warehouse.
[0003] In the existing technology, due to the information barriers between parks, it is impossible to achieve coordinated scheduling of spare parts across multiple parks. Summary of the invention
[0004] In view of this, an embodiment of the present invention provides a method and device for scheduling spare parts to achieve the purpose of coordinated scheduling of spare parts across multiple parks.
[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:
[0006] A first aspect of an embodiment of the present invention discloses a method for scheduling spare parts, the method comprising:
[0007] For each park within the target park range for spare parts scheduling, obtain the operating equipment information and historical consumption data of the park;
[0008] Based on the preset spare parts placement distribution table and the operating equipment information corresponding to each of the parks, a spare parts dependency table is generated; the spare parts dependency table is used to indicate whether there is a dependency relationship between the parks for each type of spare parts; the spare parts placement distribution table is used to specify the inventory quantity of each type of spare parts in each of the parks, and when any of the spare parts is consumed, the spare parts manufacturer will replenish it in real time to keep the spare parts quantity unchanged;
[0009] Predicting the consumption quantity of each type of spare parts in each of the parks within a preset time period based on the historical consumption data;
[0010] Generate a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each of the parks;
[0011] Spare parts scheduling is performed within the target park based on the spare parts scheduling table, and the spare parts placement distribution table is updated.
[0012] Preferably, generating a spare parts dependency table based on a preset spare parts placement distribution table and the operating equipment information corresponding to each of the parks includes:
[0013] Generate an operating equipment distribution table based on the operating equipment information corresponding to each of the parks;
[0014] For each of the parks, if any type of spare parts in the spare parts placement distribution table is not in operation in the park, the dependency relationship between the park and the spare parts is marked as 0; if any type of spare parts in the spare parts placement distribution table is in operation in the park, the dependency relationship between the park and the spare parts is marked as 1, and a spare parts dependency table is obtained.
[0015] Preferably, generating a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each of the parks includes:
[0016] Based on the historical consumption data, the average consumption quantity of each type of spare parts in each of the parks is calculated;
[0017] For each type of spare parts in any of the parks, determine whether the spare parts have the dependency relationship with the park according to the spare parts dependency table; if not, use the inventory quantity of the spare parts as the adjustment quantity corresponding to the spare parts; if so, subtract the corresponding predicted consumption quantity from the average consumption quantity to obtain the scheduling quantity;
[0018] Determine the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table;
[0019] A spare parts scheduling table is generated for the scheduling quantity and the scheduling direction corresponding to each type of spare parts in each park.
[0020] Preferably, determining the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table includes:
[0021] If the scheduling quantity is less than 0, the park having the dependency relationship on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined as the direction of transferring the spare parts to the target park;
[0022] If the scheduling quantity is greater than 0, the park that has the dependency on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park.
[0023] Preferably, the method further comprises:
[0024] For each preset special type of spare part in any of the parks, determining whether the inventory quantity of the spare part is less than a special spare part quantity threshold;
[0025] If so, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is greater than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park;
[0026] If not, the difference between the special spare parts quantity threshold and the inventory quantity is taken as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is less than the special spare parts quantity threshold is taken as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts to the target park.
[0027] A second aspect of an embodiment of the present invention discloses a spare parts scheduling device, the device comprising:
[0028] An acquisition unit, for acquiring, for each park within the target park range for spare parts scheduling, operating equipment information and historical consumption data of the park;
[0029] A dependency identification unit is used to generate a spare parts dependency table based on a preset spare parts placement distribution table and the operating equipment information corresponding to each of the parks; the spare parts dependency table is used to indicate whether there is a dependency relationship between the parks for each type of spare parts; the spare parts placement distribution table is used to specify the inventory quantity of each type of spare parts in each of the parks, and when any of the spare parts is consumed, the spare parts manufacturer replenishes it in real time to keep the spare parts quantity unchanged;
[0030] A prediction unit, configured to predict the predicted consumption quantity of each type of spare parts in each of the parks within a preset time period based on the historical consumption data;
[0031] A scheduling generation unit, configured to generate a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each of the parks;
[0032] A scheduling unit is used to perform spare parts scheduling within the target park based on the spare parts scheduling table and update the spare parts placement distribution table.
[0033] Preferably, the dependency identification unit is specifically used to:
[0034] Generate an operating equipment distribution table based on the operating equipment information corresponding to each of the parks;
[0035] For each of the parks, if any type of spare parts in the spare parts placement distribution table is not in operation in the park, the dependency relationship between the park and the spare parts is marked as 0; if any type of spare parts in the spare parts placement distribution table is in operation in the park, the dependency relationship between the park and the spare parts is marked as 1, and a spare parts dependency table is obtained.
[0036] Preferably, the scheduling generation unit is specifically used to:
[0037] Based on the historical consumption data, the average consumption quantity of each type of spare parts in each of the parks is calculated;
[0038] For each type of spare parts in each of the parks, subtract the corresponding predicted consumption quantity from the average consumption quantity to obtain a scheduling quantity, and determine a scheduling direction according to a comparison result between the scheduling quantity and 0 and the spare parts dependency table;
[0039] A spare parts scheduling table is generated for the scheduling quantity and the scheduling direction corresponding to each type of spare parts in each park.
[0040] Preferably, the scheduling generation unit for determining the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table is specifically used for:
[0041] If the scheduling quantity is less than 0, the park having the dependency relationship on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined as the direction of transferring the spare parts to the target park;
[0042] If the scheduling quantity is greater than 0, the park that has the dependency on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park.
[0043] Preferably, the device further comprises:
[0044] A special spare parts scheduling identification unit is used to determine, for each preset special type of spare parts in any of the parks, whether the inventory quantity of the spare parts is less than a special spare parts quantity threshold; if so, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is greater than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park; if not, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is less than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts into the target park.
[0045] Based on a spare parts scheduling method and device provided by the above-mentioned embodiment of the present invention, for each park within the target park range to be scheduled for spare parts, the operating equipment information and historical consumption data of the park are obtained; based on a preset spare parts placement distribution table and the operating equipment information corresponding to each of the parks, a spare parts dependency table is generated; the spare parts dependency table is used to characterize whether there is a dependency relationship between the parks for each type of spare parts; the spare parts placement distribution table is used to specify the inventory quantity of each type of spare parts in each of the parks, and when any of the spare parts is consumed, the spare parts manufacturer replenishes it in real time to keep the spare parts quantity unchanged; based on the historical consumption data, the predicted consumption quantity of each type of spare parts in each of the parks within a preset time period is predicted; based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each of the parks, a spare parts scheduling table is generated; based on the spare parts scheduling table, spare parts are scheduled within the target park range, and the spare parts placement distribution table is updated. In this solution, historical consumption data is combined to obtain differentiated placement requirements for different types of spare parts in each park. A spare parts scheduling table is generated based on the differentiated placement requirements of spare parts in each park, and spare parts are scheduled according to the spare parts scheduling table to achieve the purpose of coordinated scheduling of spare parts across multiple parks. BRIEF DESCRIPTION OF THE DRAWINGS
[0046] 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 embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.
[0047] Figure 1A flowchart of a spare parts scheduling method disclosed in an embodiment of the present invention;
[0048] Figure 2 This is a structural diagram of a spare parts scheduling device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION
[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.
[0050] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.
[0051] First, the terms used in this application are explained:
[0052] 1. Spare parts: refers to the spare parts of hardware equipment required for the operation of the information system. After a hardware failure occurs in operation, the faulty hardware equipment is replaced with spare parts of the same model to restore the system hardware to its health level before the failure. It should be noted that within the pre-planned target park, the inventory quantity of each type of spare parts in each park is fixed. After the spare parts are consumed, the service provider will replenish the corresponding spare parts in a timely manner in accordance with the commercial terms.
[0053] 2. Scheduling: refers to the operation method of changing the placement of spare parts, including spare parts out of the warehouse, spare parts in the warehouse, and the specific quantity of different types of spare parts during the outgoing and incoming processes.
[0054] It should be noted that in order to meet the business continuity supervision requirements of information systems, the key business systems of commercial banks, such as core business systems, are usually deployed simultaneously in multiple parks in multiple cities. The more mature and widely used multi-center model in the industry is the "two places and three centers" deployment plan. Among them, the "two places" in "two places and three centers" are usually two cities that are far apart, and the distance between the two cities may exceed thousands of kilometers. The "three centers" refers to the scope of the target park, usually referring to the production park in city 1, the disaster recovery park in the same city in city 1, and the disaster recovery park in a different location in city 2.
[0055] The physical distance between the production park in city 1 and the disaster recovery park in the same city of city 1 is usually relatively small, but most of them exceed 50 kilometers to ensure the high availability of the system in the park-level failure scenario. The production system runs in the production park in city 1 under normal circumstances, providing customers with major business support such as deposits and withdrawals. The real-time data replication technology can be used between the disaster recovery park in the same city of city 1 and the production park to synchronously copy the key real-time business data of the production park to the disaster recovery park in the same city, ensuring that the RTO of the data in the disaster recovery park in the same city and the data in the production park can be guaranteed when a sudden park-level failure occurs in the production park. The off-site disaster recovery park in city 2 usually runs a disaster recovery system. Under normal circumstances, the off-site disaster recovery park provides external services such as business queries and other services with low real-time requirements, realizing full utilization of the computing resources of the off-site disaster recovery park. When a disaster occurs or a planned switch is implemented (such as a disaster recovery drill, etc.), the production system switches to the off-site disaster recovery park for operation, and the computing resources in the off-site disaster recovery park provide external business support.
[0056] It should also be noted that after years of operation, the distribution of different types of equipment in multiple parks and the scale of the initial deployment of the information system have usually changed significantly due to years of operation accumulation such as relocation, expansion, and upgrade. The spare parts configuration in each park is difficult to adapt when the information system is initially put into production.
[0057] For example, when a certain type of host in Park 2 is put into production, it has been moved to Park 1 due to relocation operations. The spare parts of this type in Park 2 are no longer needed, and the corresponding demand for spare parts of this type in Park 1 has increased significantly. At this time, since the inventory quantity is certain, some spare parts are still stored in Park 2 and are idle, while Park 1 is in short supply of spare parts. Therefore, there is a need to regularly dispatch spare parts in the target park and update the inventory quantity specified in each park in a timely manner.
[0058] like Figure 1 FIG. 1 is a flowchart of a method for scheduling spare parts disclosed in an embodiment of the present invention, comprising the following steps:
[0059] Step S101: For each park within the target park range for spare parts scheduling, obtain the park's operating equipment information and historical consumption data.
[0060] In step S101, the target park range may be the three parks corresponding to the “three centers” mentioned above.
[0061] Preferably, according to the latest regulatory requirements, the future multi-park operation model will exceed the scale of the current three parks, and therefore, the target park range may include more than three parks.
[0062] The park's operating equipment information refers to the information of various types of equipment running in the park's information system. Each type of equipment has corresponding spare parts.
[0063] Historical consumption data refers to the amount of each type of spare parts consumed in the park during a certain historical period. There is a one-to-one correspondence between spare parts consumption and failures. The main reason for spare parts consumption is that the hardware fails and needs to be replaced.
[0064] It should be noted that there are multiple ways to trigger step S101 to start scheduling:
[0065] Trigger operations can be proactively implemented at fixed cycles and frequencies, such as annually, quarterly, monthly, etc.; spare parts scheduling can also be performed simultaneously with spare parts inventory counting based on the original frequency of spare parts inventory counting; it can also be triggered by specific external events, such as production events, regulatory inspections, etc.
[0066] Step S102: Generate a spare parts dependency table based on the preset spare parts placement distribution table and the operating equipment information corresponding to each park.
[0067] In step S102, the spare parts dependency table is used to indicate whether there is a dependency relationship between each type of spare parts in the park. The spare parts placement distribution table is used to specify the inventory quantity of each type of spare parts in each park. When any spare part is consumed, the spare parts manufacturer will replenish it in real time to keep the spare parts quantity unchanged.
[0068] It is understandable that the spare parts placement distribution table can be updated after spare parts scheduling so that the specified inventory quantity of each type of spare parts in each park matches the actual demand.
[0069] It should be noted that when the equipment corresponding to the spare part is running in a certain park, it means that there is a dependency relationship between the park and the spare part. If it is not running in the park, it means that there is no dependency relationship between the park and the spare part.
[0070] In the specific implementation process of step S102, firstly, an operating equipment distribution table is generated based on the operating equipment information corresponding to each park.
[0071] Exemplarily, the distribution table of running equipment is as follows:
[0072]
[0073] Among them, the types of equipment that constitute the information system include host, disk, switch, and tape library; the model of the host is Z14, and there are 6 and 4 hosts in operation in Park 1 and Park 3 respectively, with a service life of 5 years; the models of the disk include DS8950F, DS8886, DS8870 and DS8800; taking DS8950F as an example, there are 10 in operation in Park 1, and no disk of this model is in operation in Park 2 and Park 3; the models of the switch include 2499-816 and 2499-384. Taking the 2499-816 type as an example, there are 8 in operation in Park 1, 2 in operation in Park 2, and no switch of this model is in operation in Park 3; the models of the tape library include TS7700 and TS4500. Taking TS7700 as an example, there are 3 in operation in Park 1 and Park 3 respectively, and no equipment of this type is in operation in Park 2.
[0074] It should be noted that different types of spare parts can be regarded as different types of spare parts in the present invention. For example, spare parts corresponding to hosts, disks and switches can be regarded as different types of spare parts. If more detailed spare parts scheduling is required, spare parts corresponding to different types of disks including DS8950F, DS8886, DS8870 and DS8800 can also be scheduled as different types of spare parts.
[0075] After generating the operating equipment distribution table, if any type of spare parts in the spare parts placement distribution table is not in operation in the park, the dependency relationship between the park and the spare parts is marked as 0; if any type of spare parts in the spare parts placement distribution table is in operation in the park, the dependency relationship between the park and the spare parts is marked as 1, and a spare parts dependency table is obtained.
[0076] Exemplarily, the spare parts placement distribution table is as follows:
[0077] Spare Part Type Park 1 quantity Park 2 quantity Park 3 quantity total Host 90 0 50 140 disk 1100 8 200 1308 switch 100 2 20 122 Tape Library 300 0 200 500 optical fiber 100 50 200 350
[0078] It is understandable that in order to improve accuracy, the table can be further expanded. For example, spare parts of different models of disk devices can be regarded as different types of spare parts and further expanded and subdivided in quantity. The multiple different components that make up the disk can also be regarded as different types of spare parts and further expanded and subdivided in quantity.
[0079] The spare parts placement distribution table here can be understood as the initial weight ratio of the spare parts distribution between the current parks. For example, for a total of 140 spare parts for the host, the distribution ratio of each park is park 1: park 2: park 3 = 90:0:50.
[0080] The weight of the spare parts placement distribution table may change after a spare parts dispatch, for example, it may change with the migration of spare parts in and out of the warehouse between various parks.
[0081] It is understandable that the spare parts placement distribution table adjusted after the last spare parts scheduling can be used as the spare parts placement distribution table in the next spare parts scheduling process.
[0082] Exemplarily, the spare parts dependency table is as follows:
[0083]
[0084]
[0085] According to the spare parts dependency table, it can be clearly seen whether each park has a dependency on a certain model of spare parts. For example, for host spare parts, Park 1 and Park 3 have a dependency on Z14 model spare parts, while Park 2 has no dependency on this model of host spare parts.
[0086] For spare parts whose spare parts dependency is 0 in this park, when spare parts scheduling is generated, warehousing operations should be prohibited and only outbound operations are allowed, because this park no longer uses this spare part. If it is put into storage in this park, it will occupy the spare parts warehouse space in this park and there is no demand for spare parts in this park. If it is taken out of storage to a park with a spare parts dependency of 1, the spare parts usage demand of this park can be met.
[0087] For spare parts with a spare part dependency of 1, all spare parts scheduling inbound and outbound operations are allowed. When the number of spare parts in this park is insufficient, spare parts inbound scheduling operations are performed. Otherwise, spare parts outbound scheduling operations are performed in this park.
[0088] In an embodiment of the present invention, spare parts that are no longer needed are moved out of the corresponding park through the spare parts dependency identification process. Firstly, the spare parts warehouse space of the corresponding park can be saved. Secondly, they are moved to the park warehouse that is dependent on the specific spare parts, thereby ensuring the availability of spare parts when hardware failures occur and need to be replaced.
[0089] Step S103: Predict the predicted consumption quantity of each type of spare parts in each park within a preset time period based on the historical consumption data.
[0090] In step S103, the latest required inventory quantity of spare parts of a specific model in each park is confirmed in combination with the historical consumption data of spare parts. It can be understood that the latest required inventory quantity is equal to the predicted consumption quantity.
[0091] The analysis of spare parts historical consumption data is mainly carried out through historical fault data, because spare parts consumption and faults are in a one-to-one correspondence, and the main reason for spare parts consumption is that hardware failures need to be repaired. Therefore, the analysis of spare parts historical consumption data specifically includes four types of analysis methods: fault equipment type analysis, equipment fault location analysis, equipment fault park distribution analysis, and special hardware fault analysis. The details are as follows:
[0092] First, the number of failures of all types of equipment (the total number in each park) is analyzed. After identifying the type of equipment that has failed (such as host, disk, switch, etc.), further comparative analysis is performed by comparing the total number of failures of different types of equipment to identify which specific type of equipment has the highest failure frequency, and to identify the key types in the spare parts scheduling process.
[0093] In one embodiment, spare parts scheduling can be performed only for key types of spare parts, that is, only the predicted consumption quantity of key types of spare parts in each park is predicted, and the corresponding subsequent step S104 also only generates a spare parts scheduling table for the predicted consumption quantity of key types of spare parts in each park and the spare parts dependency table.
[0094] The following table shows an example of a hardware failure count table:
[0095] Device Type Total number of failures Average number of failures per month % Host 60 2.4 2 disk 2418 96.72 95.7 switch 7 0.28 0.3 Tape Library 50 2 2
[0096] Among them, disk devices had the highest number of failures, with a total of 2,418 failures, and an average monthly failure rate of 96.72, accounting for 95.7% of the spare parts analysis period; host and tape library devices had the highest number of failures, with a total of 60 and 50 hardware failures respectively, each accounting for 2% of the total number of failures in the spare parts analysis period.
[0097] Exemplarily, the spare parts corresponding to the disk type may be used as the spare parts of the key type.
[0098] Preferably, if the scheduling process is refined, the disk type may not be used as the key type, but the distribution of hardware failures of disk devices with the highest number of failures may be further analyzed, and different disk models and different disk parts may be further analyzed to further refine the key types of scheduling.
[0099] The following table shows the statistics of different types of disk failures:
[0100] Disk Model Service time (years) Number of failures Average number of failures per month DS8950F 3 25 1 DS8886 6 71 2.8 DS8870 9 679 27.2 DS8800 12 1643 65.7
[0101] Among them, DS8800 and DS8870 disks have the highest number of hardware failures, while DS8886 and DS8950F disks have relatively few hardware failures. Furthermore, the failure rate of different types of disks increases with the increase in service time. Therefore, disk models with relatively long service time are taken as key types.
[0102] For example, disk models that have been in service for more than five years are considered as key types.
[0103] The following table shows the disk failure location statistics:
[0104]
[0105]
[0106] Among them, when various types of disks fail, more than 80% occur in the disk drive module, and the other failure types are power module and board failures. Accordingly, when scheduling spare parts, different components of the disk can be regarded as different types of spare parts, and the disk components with failure times exceeding the threshold can be regarded as key types.
[0107] In the specific implementation process of step S103, the distribution of the number of failures of different equipment in each park is mastered through the historical consumption data of spare parts (from the type of faulty equipment and the location of the faulty equipment).
[0108] In order to ensure that the spare parts placement in all parks meets the emergency repair needs in the event of hardware failure, we assume that the probability of failure of all equipment is consistent with the trend of historical data, and use the number of failures of each type of equipment in each park during the historical period as the predicted consumption quantity of spare parts corresponding to this type of equipment in each park during the preset period. The preset period is equal to the historical period.
[0109] For example, the fault distribution in each park is analyzed, and the predicted consumption quantity of each type of spare parts required in each park is obtained through the analysis.
[0110] Taking the disk type failure obtained in the above analysis as an example, the quantity distribution of this type of failure in each park is analyzed to obtain the corresponding predicted consumption quantity.
[0111] For example, the following table shows the statistics of disk hardware failures in each park.
[0112]
[0113] Among them, since only one flash drive model DS8950F disk device is deployed in Park 1, all disk failures are of this model. If this model is used as the key type, the predicted consumption quantity of spare parts of this key type in Park 1 is predicted to be 332.
[0114] If the disk drive is a key type, the predicted consumption quantity of spare parts of this key type in Park 1 is predicted to be 250.
[0115] Step S104: Generate a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each park.
[0116] Step S41: Based on the historical consumption data, the average consumption quantity of each type of spare parts in each park is calculated.
[0117] In step S41, it is assumed that the spare parts of type A have a total of n1 failures in park 1, n2 failures in park 2, and n3 failures in park 3. It is also assumed that n1>n2>n3, and the average consumption quantity of each park is n, that is:
[0118] n=(n1+n2+n3) / 3
[0119] Step S42: For each type of spare parts in any park, determine whether there is a dependency relationship between the spare parts and the park according to the spare parts dependency table; if not, use the inventory quantity of the spare parts as the corresponding adjustment quantity of the spare parts; if so, subtract the corresponding predicted consumption quantity from the average consumption quantity to obtain the scheduling quantity.
[0120] In step S42, if a park no longer has a dependency on a certain type of spare parts due to information system adjustments or other reasons, all spare parts without dependencies need to be called out. When a park subsequently determines the scheduling direction for this type of spare parts, the park that has no dependency on this type of spare parts will not be used as the target park.
[0121] Step S43: Determine the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table.
[0122] Specifically, if the scheduling quantity is less than 0, the park that has a dependency on this type of spare parts is determined as the target park from the spare parts dependency table, and the scheduling direction is determined to be the direction of transferring the spare parts into the target park; if the scheduling quantity is greater than 0, the park that has a dependency on this type of spare parts is determined as the target park from the spare parts dependency table, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park.
[0123] It should be noted that any park with the corresponding type of spare parts can be used as the target park for the spare parts to be transferred out. If multiple parks have the same type of spare parts, it is sufficient to ensure that the target park can still meet its own needs after the spare parts are transferred out.
[0124] For example, for Park 1, n-n1 spare parts need to be transferred from other parks, for Park 2, n-n2 spare parts need to be transferred from other parks, and for Park 3, n-n3 spare parts need to be transferred from other parks.
[0125] Among them, the absolute value of the above difference is the dispatch quantity. If the difference is less than 0, it means that spare parts are transferred out from the current park; that is, referring to the average of spare parts consumption in all parks, if the spare parts consumption exceeds the average, spare parts need to be transferred in from other parks, and if it is less than the average, spare parts are transferred out from the current park.
[0126] In one embodiment, if the dispatch quantity is equal to 0, it is determined that the corresponding type of spare parts does not need to be transferred out or into the current park.
[0127] In one embodiment, for each preset special type of spare part in any park, it is determined whether the inventory quantity of the spare part is less than a special spare part quantity threshold;
[0128] If so, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park whose inventory quantity of special type of spare parts is greater than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park;
[0129] If not, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is less than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts to the target park.
[0130] It should be noted that the special spare parts quantity threshold is adjusted in real time according to the changes in the hardware in the information system. Initially, the special spare parts quantity threshold is consistent with the inventory quantity of the corresponding special type of spare parts. Changes in the information system will cause a difference between the special spare parts quantity threshold and the inventory quantity.
[0131] Special failures refer to certain hardware failures that occur infrequently or even never, but have a significant impact on the operation of the information system after they occur. For example, a storage switch may have a hardware failure during peak trading hours. The hardware failure may cause the IO of the information system to be blocked, leading to a large backlog of transactions. The failure to repair the failure in a timely manner may further cause global transaction timeouts to occur and spread, affecting the information system's ability to ensure business continuity.
[0132] Therefore, the spare parts corresponding to these hardware will be pre-marked as special spare parts. For campuses that have dependencies on special spare parts, it is ensured that the number of special spare parts in the campus will not be less than the special spare parts quantity threshold.
[0133] The algorithm for determining the scheduling direction is as follows:
[0134] start:
[0135] For spare parts of type j in park i:
[0136] 1) Determine whether there is a dependency relationship between park i and type j of spare parts according to the spare parts dependency table;
[0137] 2) If park i has no dependency on spare parts of type j:
[0138] Then the park that depends on the j-type spare parts is selected as the target park, and the dispatch direction is determined to be the direction of dispatching to the target park;
[0139] 3) If park i has a dependency on spare parts of type j:
[0140] 3.1) Compare the predicted consumption of spare parts of type j in park i with the average consumption of spare parts of type j in each park:
[0141] 3.2) If the consumption of park i is less than the average consumption of all parks:
[0142] The park that depends on the j-type spare parts is selected as the target park, and the dispatch direction is determined to be the direction of dispatching to the target park;
[0143] 3.3) If the consumption of park i is greater than the average consumption of all parks:
[0144] The park that depends on the j-type spare parts is selected as the target park, and the dispatch direction is determined to be the direction of dispatching out of the target park;
[0145] 4) Determine whether the spare part of type j is of special type:
[0146] 4.1) If the j type spare part is a special type spare part:
[0147] Determine whether the number of spare parts of type j in park i is less than 2;
[0148] If so, the park with more than 2 spare parts of type j is selected as the target park, and the dispatch direction is determined to be the direction of dispatching out of the target park;
[0149] Finish.
[0150] Step S44: Generate a spare parts scheduling table for the scheduling quantity and scheduling direction corresponding to each type of spare parts in each park.
[0151] Exemplarily, the spare parts schedule is as follows:
[0152] Spare Part Type Target park Target Park Scheduling quantity Key Type switch Park 1 Park 2 3 yes disk Park 1 Park 2 10 no Tape Library Park 3 Park 1 3 no Host Park 3 Park 1 1 yes switch Park 1 Park 3 1 yes disk Park 1 Park 3 1 no Fiber Optic Module Park 1 Park 3 2 no … … … … …
[0153] Step S105: Perform spare parts scheduling within the target park based on the spare parts scheduling table, and update the spare parts placement distribution table.
[0154] Taking the above spare parts scheduling table as an example, the scheduling process is: migrate 3 switch spare parts and 10 disk device spare parts from the spare parts library of Park 1 to the spare parts library of Park 2; migrate 1 switch spare part, 1 disk spare part, and 2 optical fiber module spare parts from the spare parts library of Park 1 to the spare parts library of Park 3; migrate 3 tape library spare parts and 1 host spare part from the spare parts library of Park 3 to the spare parts library of Park 1.
[0155] The updated spare parts placement distribution table is as follows:
[0156] Spare Part Type Park 1 quantity Park 2 quantity Park 3 quantity total Host 91 0 49 140 disk 1089 18 201 1308 switch 96 5 21 122 Tape Library 303 0 197 500 optical fiber 98 50 202 350
[0157] It is understandable that during the scheduling process, the spare parts warehouse of each park will perform outbound operations and / or inbound operations, thereby timely updating the spare parts placement distribution table.
[0158] Based on a method for scheduling spare parts disclosed in the above-mentioned embodiment of the present invention, for each park within the scope of the target park to be scheduled for spare parts, the operating equipment information and historical consumption data of the park are obtained; based on the preset spare parts placement distribution table and the operating equipment information corresponding to each park, a spare parts dependency table is generated; based on the historical consumption data, the predicted consumption quantity of each type of spare parts in each park within a preset time period is predicted; based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each park, a spare parts scheduling table is generated; spare parts scheduling is performed within the scope of the target park based on the spare parts scheduling table, and the spare parts placement distribution table is updated. In this scheme, the differentiated placement requirements of different types of spare parts in each park are obtained in combination with the historical consumption data of spare parts, a spare parts scheduling table is generated according to the differentiated placement requirements of spare parts for each park, and finally, spare parts scheduling is performed according to the spare parts scheduling table, so as to achieve the purpose of coordinated scheduling of spare parts across multiple parks.
[0159] Corresponding to the method for scheduling spare parts disclosed in the above embodiment of the present invention, as Figure 2 FIG. 1 is a structural diagram of a spare parts scheduling device disclosed in an embodiment of the present invention, comprising:
[0160] The acquisition unit 201 is used to acquire the operating equipment information and historical consumption data of each park within the target park range to be scheduled for spare parts;
[0161] The dependency identification unit 202 is used to generate a spare parts dependency table based on the preset spare parts placement distribution table and the operating equipment information corresponding to each park; the spare parts dependency table is used to indicate whether there is a dependency relationship between each type of spare parts in the park; the spare parts placement distribution table is used to specify the inventory quantity of each type of spare parts in each park, and when any spare part is consumed, the spare parts manufacturer will replenish it in real time to keep the spare parts quantity unchanged;
[0162] The prediction unit 203 is used to predict the predicted consumption quantity of each type of spare parts in each park within a preset time period based on the historical consumption data;
[0163] A scheduling generation unit 204, configured to generate a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each park;
[0164] The scheduling unit 205 is used to perform spare parts scheduling within the target park based on the spare parts scheduling table and update the spare parts placement distribution table.
[0165] Preferably, the dependency identification unit 202 is specifically configured to:
[0166] Generate an operating equipment distribution table based on the operating equipment information corresponding to each park;
[0167] For each park, if any type of spare parts in the spare parts placement distribution table is not in operation in the park, the dependency relationship between the park and the spare parts is marked as 0; if any type of spare parts in the spare parts placement distribution table is in operation in the park, the dependency relationship between the park and the spare parts is marked as 1, and a spare parts dependency table is obtained.
[0168] Preferably, the scheduling generation unit 204 is specifically configured to:
[0169] Based on historical consumption data, calculate the average consumption quantity of each type of spare parts in each park;
[0170] For each type of spare parts in each park, the average consumption quantity is subtracted from the corresponding predicted consumption quantity to obtain the dispatch quantity, and the dispatch direction is determined based on the comparison result between the dispatch quantity and 0 and the spare parts dependency table;
[0171] A spare parts scheduling table is generated for the scheduling quantity and scheduling direction corresponding to each type of spare parts in each park.
[0172] Preferably, the scheduling generation unit 204 for determining the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table is specifically used for:
[0173] If the dispatch quantity is less than 0, the park that has a dependency on the type of spare parts is determined as the target park from the spare parts dependency table, and the dispatch direction is determined to be the direction of transferring the spare parts to the target park;
[0174] If the scheduling quantity is greater than 0, the park that has a dependency on the type of spare parts is determined as the target park from the spare parts dependency table, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park.
[0175] Preferably, the scheduling device further includes:
[0176] A special spare parts scheduling identification unit is used to determine, for each preset special type of spare parts in any park, whether the inventory quantity of the spare parts is less than a special spare parts quantity threshold;
[0177] If so, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park whose inventory quantity of special type of spare parts is greater than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park;
[0178] If not, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is less than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts to the target park.
[0179] Based on a spare parts scheduling device disclosed in the above-mentioned embodiment of the present invention, for each park within the scope of the target park to be scheduled for spare parts, the operating equipment information and historical consumption data of the park are obtained; based on the preset spare parts placement distribution table and the operating equipment information corresponding to each park, a spare parts dependency table is generated; based on the historical consumption data, the predicted consumption quantity of each type of spare parts in each park within a preset time period is predicted; based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each park, a spare parts scheduling table is generated; spare parts scheduling is performed within the scope of the target park based on the spare parts scheduling table, and the spare parts placement distribution table is updated. In this solution, the differentiated placement requirements of different types of spare parts in each park are obtained in combination with the historical consumption data of spare parts, a spare parts scheduling table is generated according to the differentiated placement requirements of spare parts for each park, and finally, spare parts scheduling is performed according to the spare parts scheduling table, so as to achieve the purpose of coordinated scheduling of spare parts across multiple parks.
[0180] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.
[0181] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.
[0182] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for scheduling spare parts, characterized in that: The method comprises: For each park within the target park range for spare parts scheduling, obtain the operating equipment information and historical consumption data of the park; Based on the preset spare parts placement distribution table and the operating equipment information corresponding to each of the parks, a spare parts dependency table is generated; the spare parts dependency table is used to indicate whether there is a dependency relationship between the parks for each type of spare parts; the spare parts placement distribution table is used to specify the inventory quantity of each type of spare parts in each of the parks, and when any of the spare parts is consumed, the spare parts manufacturer will replenish it in real time to keep the spare parts quantity unchanged; Predicting the consumption quantity of each type of spare parts in each of the parks within a preset time period based on the historical consumption data; Generate a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each of the parks; Spare parts scheduling is performed within the target park based on the spare parts scheduling table, and the spare parts placement distribution table is updated.
2. The method according to claim 1, characterized in that The generating of the spare parts dependency table based on the preset spare parts placement distribution table and the operating equipment information corresponding to each of the parks includes: Generate an operating equipment distribution table based on the operating equipment information corresponding to each of the parks; For each of the parks, if any type of spare parts in the spare parts placement distribution table is not in operation in the park, the dependency relationship between the park and the spare parts is marked as 0; if any type of spare parts in the spare parts placement distribution table is in operation in the park, the dependency relationship between the park and the spare parts is marked as 1, and a spare parts dependency table is obtained.
3. The method according to claim 1, characterized in that The generating of a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each of the parks includes: Based on the historical consumption data, the average consumption quantity of each type of spare parts in each of the parks is calculated; For each type of spare parts in any of the parks, determine whether the spare parts have the dependency relationship with the park according to the spare parts dependency table; if not, use the inventory quantity of the spare parts as the adjustment quantity corresponding to the spare parts; if so, subtract the corresponding predicted consumption quantity from the average consumption quantity to obtain the scheduling quantity; Determine the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table; A spare parts scheduling table is generated for the scheduling quantity and the scheduling direction corresponding to each type of spare parts in each park.
4. The method according to claim 3, characterized in that The determining the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table includes: If the scheduling quantity is less than 0, the park having the dependency relationship on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined as the direction of transferring the spare parts to the target park; If the scheduling quantity is greater than 0, the park that has the dependency on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park.
5. The method according to claim 3, characterized in that: The method further comprises: For each preset special type of spare part in any of the parks, determining whether the inventory quantity of the spare part is less than a special spare part quantity threshold; If so, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is greater than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park; If not, the difference between the special spare parts quantity threshold and the inventory quantity is taken as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is less than the special spare parts quantity threshold is taken as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts to the target park.
6. A spare parts dispatching device, characterized in that: The device comprises: An acquisition unit, for acquiring, for each park within the target park range for spare parts scheduling, operating equipment information and historical consumption data of the park; A dependency identification unit is used to generate a spare parts dependency table based on a preset spare parts placement distribution table and the operating equipment information corresponding to each of the parks; the spare parts dependency table is used to indicate whether there is a dependency relationship between the parks for each type of spare parts; the spare parts placement distribution table is used to specify the inventory quantity of each type of spare parts in each of the parks, and when any of the spare parts is consumed, the spare parts manufacturer replenishes it in real time to keep the spare parts quantity unchanged; A prediction unit, configured to predict the predicted consumption quantity of each type of spare parts in each of the parks within a preset time period based on the historical consumption data; A scheduling generation unit, configured to generate a spare parts scheduling table based on the spare parts dependency table and the predicted consumption quantity of each type of spare parts in each of the parks; A scheduling unit is used to perform spare parts scheduling within the target park based on the spare parts scheduling table and update the spare parts placement distribution table.
7. The device according to claim 6, characterized in that The dependency identification unit is specifically used for: Generate an operating equipment distribution table based on the operating equipment information corresponding to each of the parks; For each of the parks, if any type of spare parts in the spare parts placement distribution table is not in operation in the park, the dependency relationship between the park and the spare parts is marked as 0; if any type of spare parts in the spare parts placement distribution table is in operation in the park, the dependency relationship between the park and the spare parts is marked as 1, and a spare parts dependency table is obtained.
8. The device according to claim 6, characterized in that The scheduling generation unit is specifically used for: Based on the historical consumption data, the average consumption quantity of each type of spare parts in each of the parks is calculated; For each type of spare parts in each of the parks, subtract the corresponding predicted consumption quantity from the average consumption quantity to obtain a scheduling quantity, and determine a scheduling direction according to a comparison result between the scheduling quantity and 0 and the spare parts dependency table; A spare parts scheduling table is generated for the scheduling quantity and the scheduling direction corresponding to each type of spare parts in each park.
9. The device according to claim 8, characterized in that The scheduling generation unit is used to determine the scheduling direction according to the comparison result between the scheduling quantity and 0 and the spare parts dependency table, specifically used to: If the scheduling quantity is less than 0, the park having the dependency relationship on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined as the direction of transferring the spare parts to the target park; If the scheduling quantity is greater than 0, the park that has the dependency on the spare parts of the type is determined as the target park from the spare parts dependency table, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park.
10. The device according to claim 8, characterized in that The device also includes: A special spare parts scheduling identification unit is used to determine, for each preset special type of spare parts in any of the parks, whether the inventory quantity of the spare parts is less than a special spare parts quantity threshold; if so, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is greater than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts out of the target park; if not, the difference between the special spare parts quantity threshold and the inventory quantity is used as the scheduling quantity, the park where the inventory quantity of the special type of spare parts is less than the special spare parts quantity threshold is used as the target park, and the scheduling direction is determined to be the direction of transferring the spare parts into the target park.