CN115238931B

CN115238931B - Method and device for planning worn parts, computer equipment and storage medium

Info

Publication number: CN115238931B
Application number: CN202211134200.7A
Authority: CN
Inventors: 孙明明; 王莹; 易炜; 牛建超; 吴栋; 熊波波; 汪凯蔚; 黄铎佳; 谢丽梅; 解禾; 胡湘洪; 罗琴; 张钟文
Original assignee: China Electronic Product Reliability and Environmental Testing Research Institute
Current assignee: China Electronic Product Reliability and Environmental Testing Research Institute
Priority date: 2022-09-19
Filing date: 2022-09-19
Publication date: 2023-04-07
Anticipated expiration: 2042-09-19
Also published as: CN115238931A

Abstract

The present application relates to the field of big data technologies, and in particular, to a method and an apparatus for planning a consumable part, a computer device, and a storage medium. The method comprises the following steps: determining maintenance data corresponding to at least two devices to be maintained, wherein the maintenance data comprise the fault probability of each device to be maintained and the reference consumption number of the worn parts; determining target equipment from at least two pieces of equipment to be maintained based on the maintenance data, and determining a consumable part satisfaction rate according to the target equipment and the maintenance data; and determining a target planning amount of the consumable parts based on the consumable part satisfaction rate and a preset target satisfaction rate. The method and the device for determining the target planning quantity of the consumable part overcome the defect that a consumable part prediction method is absent in the prior art, the target planning quantity of the consumable part consumed during maintenance of the equipment to be maintained is predicted, the target planning quantity corresponding to the consumable part is rapidly determined, and the efficiency of determining the target planning quantity of the consumable part is guaranteed.

Description

Method and device for planning worn parts, computer equipment and storage medium

Technical Field

The present application relates to the field of big data technologies, and in particular, to a method and an apparatus for planning a consumable part, a computer device, and a storage medium.

Background

Along with the improvement of the living standard of people, various devices are filled in the lives of people, great help is brought to the work and the life of people, and in order to maintain the normal operation of the devices, the devices need to be maintained or detected.

In the prior art, when equipment to be maintained needs to be maintained, the quantity of spare parts needed to be consumed in the maintenance process of the equipment to be maintained can be determined according to a spare part prediction method, so that the smooth operation of the maintenance process is ensured.

To explain further, a certain amount of worn parts is consumed when performing maintenance on spare parts in a device to be maintained, but in the prior art, there is no method for predicting a target planned amount of worn parts during maintenance of the device to be maintained.

Disclosure of Invention

In view of the above, it is necessary to provide a consumable part planning method, a consumable part planning device, a computer device, and a storage medium, which can quickly and accurately predict a target planned amount of consumable parts consumed in repairing a device to be repaired.

In a first aspect, a method for planning a consumable part is provided. The method comprises the following steps:

determining maintenance data corresponding to at least two devices to be maintained, wherein the maintenance data comprise the fault probability of each device to be maintained and the reference consumption number of the worn parts;

determining target equipment from at least two pieces of equipment to be maintained based on the maintenance data, and determining a consumable part satisfaction rate according to the target equipment and the maintenance data;

and determining a target planning amount of the consumable parts based on the consumable part satisfaction rate and a preset target satisfaction rate.

In one embodiment, determining the target device from the at least two devices to be serviced based on the service data comprises:

determining fault threshold values corresponding to at least two devices to be maintained based on the maintenance data;

and according to the maintenance data, determining target equipment with the fault probability larger than or equal to the fault threshold value from at least two pieces of equipment to be maintained.

In one embodiment, determining a consumable satisfaction rate based on the target device and the service data comprises:

determining a candidate planning quantity of wearing parts corresponding to the target equipment according to the reference consumption data of the wearing parts corresponding to the target equipment in the maintenance data;

and determining a consumable part satisfaction rate according to the candidate planning amount and the reference consumption data of the consumable parts of the equipment to be maintained in the maintenance data.

In one embodiment, determining a target projected amount of consumable parts based on a consumable part satisfaction rate and a predetermined target satisfaction rate comprises:

determining whether the consumable part satisfaction rate is less than a target satisfaction rate;

if yes, updating the target equipment according to the fault threshold and the maintenance data; and based on the updated target equipment, returning to execute the operation of determining the consumable part satisfaction rate according to the target equipment and the maintenance data.

In one embodiment, determining whether the consumable satisfaction rate is less than the target satisfaction rate further comprises:

and if not, determining the target planning quantity of the worn parts according to the candidate planning quantity of the worn parts corresponding to the target equipment and the maintenance data.

In one embodiment, updating the target device consumable based on the failure threshold and the repair data comprises:

adding the fault threshold value into the maintenance data, and sequencing at least two devices to be maintained according to the fault probability in the added maintenance data;

and updating the target equipment according to the sequencing result.

In a second aspect, the present application further provides a device for planning a consumable part. The device comprises:

the first determining module is used for determining maintenance data corresponding to at least two devices to be maintained, wherein the maintenance data comprise the fault probability of each device to be maintained and the reference consumption number of the worn parts;

the second determining module is used for determining target equipment from at least two pieces of equipment to be maintained based on the maintenance data and determining the consumable part satisfaction rate according to the target equipment and the maintenance data;

and a third determining module, configured to determine a target projected amount of the consumable part based on the consumable part satisfaction rate and a preset target satisfaction rate.

In a third aspect, the present application also provides a computer device. The computer arrangement comprises a memory in which a computer program is stored and a processor which, when executing the computer program, carries out the method of planning wearing parts as described in any of the embodiments of the first aspect.

In a fourth aspect, the present application further provides a computer-readable storage medium. A computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the method of planning a consumable as described above in relation to any one of the embodiments of the first aspect.

In a fifth aspect, the present application further provides a computer program product. A computer program product comprising a computer program which, when executed by a processor, implements a method of planning a consumable part as in any of the embodiments of the first aspect described above.

According to the technical scheme, the fault probability and the reference consumption quantity are obtained by determining the maintenance data, a data basis is provided for subsequently determining the target equipment and the consumable part satisfaction rate, and the accuracy of determining the target planning quantity is ensured; by determining the target equipment, the loss piece satisfaction rate is determined according to the target equipment, guarantee is provided for subsequently determining the target planning quantity of the loss piece, and the accuracy of the target planning quantity is further improved; through the consumable part satisfaction rate and the target satisfaction rate, the target planning quantity of the consumable parts is determined, the defect that a consumable part prediction method is lacked in the prior art is overcome, and the target planning quantity of the consumable parts consumed during maintenance of the equipment to be maintained is rapidly and accurately predicted.

Drawings

FIG. 1 is a diagram of an exemplary environment in which a method for planning a consumable part is implemented;

fig. 2 is a flowchart of a method for planning a wearing part according to an embodiment of the present disclosure;

fig. 3 is a flowchart of another method for planning a consumable part according to an embodiment of the present disclosure;

fig. 4 is a flowchart of another method for planning a consumable part according to an embodiment of the present disclosure;

FIG. 5 is a flow chart of another method for planning a consumable part according to an embodiment of the present disclosure;

fig. 6 is a flowchart of another method for planning a consumable part according to an embodiment of the present disclosure;

fig. 7 is a block diagram illustrating a configuration of a device for planning a consumable part according to an embodiment of the present disclosure;

fig. 8 is a block diagram of another exemplary configuration of a device for planning a consumable part according to an embodiment of the present disclosure;

fig. 9 is a block diagram of another exemplary apparatus for planning a wearing part according to an embodiment of the present disclosure;

fig. 10 is a block diagram illustrating a configuration of another device for planning a wearing part according to an embodiment of the present disclosure;

FIG. 11 is a diagram illustrating an internal structure of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. In the description of the present application, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

Spare parts are important material bases of the equipment to be maintained in the use, maintenance and other guarantee tasks, and whether the spare part consumption prediction is accurate or not directly influences the readiness integrity and the guarantee cost of the equipment to be maintained. There are 200 spare part prediction methods according to incomplete statistics, wherein the spare part prediction methods can be classified into three types:

one is an analytical prediction method, for example: a mathematical statistics prediction method, a linear regression prediction method, a time series prediction method, a guaranteed probability prediction method, a support vector machine prediction method, a delphire prediction method, and the like.

Second, a simulation prediction method, for example: a monte carlo simulation prediction method, an entity flow graph prediction method, a Petri (mathematical representation of a discrete parallel system) net prediction method, and the like.

Thirdly, a comprehensive method, for example: the method comprises a neural network prediction method, a neural network-gray model combined model prediction method, an adaptive particle swarm-weighted two-times support vector machine combined model prediction method and the like.

How to reasonably predict spare parts under the condition of less development phase data is a key problem. However, researchers have found that the prediction of the device for the development phase is mainly faced with two major problems:

1. and a large amount of similar product data and prior data are lacked, a data base cannot be provided for spare part prediction, and the accuracy of the spare part prediction cannot be ensured.

2. The prior art lacks predictions regarding the consumption of worn parts while servicing spare parts.

In conclusion, due to the factors that the related data of the equipment to be maintained in the development stage is less, the value of the worn part in the equipment to be maintained is lower, and the like, less researchers have to consider the actual use and maintenance guarantee requirements from the forward design perspective, the index requirements of the equipment to be maintained are met, and the reasonable worn part prediction method which accords with the actual engineering application is provided.

The method for planning a consumable part provided by the embodiment of the application can be applied to an application environment shown in fig. 1. In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 1. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store acquisition data for a plan of wearing parts. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of planning a consumable part.

The application discloses a method and a device for planning worn parts, computer equipment and a storage medium. Determining target equipment from equipment to be maintained by determining maintenance data; determining a consumable part satisfaction rate according to the target equipment and the maintenance data; and finally, determining a target planning amount based on the consumable part satisfaction rate and the target satisfaction rate.

Fig. 2 is a flowchart of a method for planning a wearing part according to an embodiment of the present application, and as shown in fig. 2, the method for planning a wearing part may include the following steps:

step 201, determining maintenance data corresponding to at least two devices to be maintained, wherein the maintenance data includes the fault probability of each device to be maintained and the reference consumption number of the worn parts.

It should be noted that the reference consumption number of wearing parts refers to the number of wearing parts that need to be consumed for a single maintenance activity of the equipment to be maintained, which can be understood as the maximum number of wearing parts that need to be consumed in a maintenance activity of the equipment to be maintained.

The worn part is a general name of a consumable spare part and a vulnerable spare part which need to be consumed in the process of maintaining the equipment to be maintained.

It should be noted that the wearing parts include many kinds, which are not limited in this application, and further, the wearing parts may include, but are not limited to: screws, nuts and washers, etc.

In an embodiment of the application, the failure probability of the equipment to be maintained can be calculated according to the failure rate and the working time of the equipment to be maintained.

And as an implementation mode, determining the failure rate and the working time of the equipment to be maintained, and substituting the failure rate and the working time of the equipment to be maintained into the first fault probability analytic expression, thereby determining the fault probability corresponding to the equipment to be maintained.

It should be noted that the first failure probability analysis expression is the following formula (1):

（1）

wherein the content of the first and second substances,

the fault probability corresponding to the equipment to be maintained is referred to;

the failure rate corresponding to equipment to be maintained is referred to; and t refers to the working time corresponding to the equipment to be repaired.

It should be noted that the failure rate corresponding to the device to be maintained may be determined according to the mean time between failures corresponding to the device to be maintained, and specifically, the failure rate corresponding to the device to be maintained and the mean time between failures are in a reciprocal relationship.

In summary, the expression of the failure rate corresponding to the device to be repaired and the average fault interval time is the following formula (2):

（2）

wherein the content of the first and second substances,

the failure rate corresponding to equipment to be maintained is referred to; the MTBF refers to the mean time between failures for the equipment to be maintained.

Substituting the formula (2) into the formula (1) to replace the failure rate corresponding to the equipment to be maintained in the formula (1) with the failure rate corresponding to the equipment to be maintained in the formula (2), and further determining a second failure probability analytic expression.

It should be noted that the second failure probability analysis expression is the following formula (3):

（3）

wherein, the first and the second end of the pipe are connected with each other,

the fault probability corresponding to equipment to be maintained is referred to; t refers to the working time corresponding to the equipment to be maintained; the MTBF refers to the mean time between failures for the equipment to be maintained.

In an embodiment of the present application, when the failure probability of the device to be repaired needs to be determined, the number, MTBF and the working time corresponding to eleven devices to be repaired are known.

The corresponding numbers, MTBF and operating time of eleven devices to be serviced are shown in table 1 below:

TABLE 1 MTBF and hours of operation of equipment to be serviced

In an embodiment of the present application, the failure probability of the device to be maintained may be calculated according to the average failure interval time and the working time of the device to be maintained. Specifically, the mean time between failures and the working time of the equipment to be maintained are determined, and the mean time between failures and the working time of the equipment to be maintained are substituted into the second failure probability analysis expression, so that the failure probability corresponding to the equipment to be maintained is determined.

In summary, according to table 1, the MTBF and the working time corresponding to eleven pieces of equipment to be maintained are determined, the MTBF and the working time corresponding to eleven pieces of equipment to be maintained are substituted into the second failure probability analytic expression (3), and the failure probability corresponding to eleven pieces of equipment to be maintained is calculated;

specifically, according to the failure probability calculation method, the failure probability corresponding to eleven pieces of equipment to be maintained can be determined as shown in table 2 below:

TABLE 2 probability of failure of the device to be repaired

In an embodiment of the application, the fault probability of the equipment to be maintained can be calculated according to the average fault interval time and the working time of the equipment to be maintained; specifically, the mean fault interval time and the working time of the equipment to be maintained are determined, and the mean fault interval time and the working time of the equipment to be maintained are substituted into the second fault probability analysis expression, so that the fault probability corresponding to the equipment to be maintained is determined.

Step 202, determining a target device from at least two devices to be maintained based on the maintenance data, and determining a consumable part satisfaction rate according to the target device and the maintenance data.

It should be noted that the target device refers to a device, of which the failure probability satisfies the judgment condition, in at least two devices to be maintained; wherein, the judging condition may include: n devices with the largest fault probability in the at least two devices to be maintained, wherein N is a positive integer different from 0; or the failure probability of the at least two devices to be maintained is larger than or equal to the preset failure threshold value. With respect to the two determination conditions for determining the target device, the following description is made:

in an embodiment of the present application, if the determination condition is N devices with the largest failure probability in the at least two devices to be maintained, the number of the devices to be maintained in the at least two devices to be maintained is greater than or equal to N, where N is a positive integer (for example, N may be 3); when the target equipment needs to be determined, sequencing at least two pieces of equipment to be maintained according to the fault probability, and determining N pieces of equipment to be maintained with the maximum fault probability according to a sequencing result; the N devices to be maintained with the maximum fault probability are the target devices.

In an embodiment of the present application, if the determination condition is that the failure probability of at least two devices to be maintained is greater than or equal to a predetermined failure threshold; the method comprises the steps of presetting a fault threshold value as M, screening at least two pieces of equipment to be maintained according to fault probability when the target equipment is determined to be the equipment to be maintained, and determining the equipment to be processed of which the fault probability is greater than the fault threshold value in the at least two pieces of equipment to be maintained, wherein the equipment to be processed of which the fault probability is greater than the fault threshold value is the target equipment.

It should be noted that the method for determining the consumable satisfaction rate may include: and determining the consumable part requirement total amount of the target equipment, and further performing satisfaction rate calculation according to the consumable part requirement total amount, so as to determine the consumable part satisfaction rate corresponding to the target equipment.

Further, the consumable part satisfaction rate is in a direct proportion relation with the expectation corresponding to the consumable part demand total of the target device, and the larger the expectation corresponding to the consumable part demand total of the target device is, the higher the consumable part satisfaction rate corresponding to the target device is; the factors that influence the total amount of consumable parts required by the target device to the expectation may include: the number of target devices in the device to be maintained, the consumption of the corresponding quick-wear parts of the target devices and the like.

For example, on the premise that the consumption of the consumable parts corresponding to the target device and other factors are fixed, if the number of the target devices in the device to be maintained is larger, the consumable part satisfaction rate corresponding to the target device is larger, and if the number of the target devices in the device to be maintained is smaller, the consumable part satisfaction rate corresponding to the target device is smaller; similarly, on the premise that the number of the target devices in the device to be maintained and other factors are fixed, if the consumption of the quick-wear parts corresponding to the target devices is larger, the satisfaction rate of the quick-wear parts corresponding to the target devices is larger, and if the consumption of the quick-wear parts corresponding to the target devices is smaller, the satisfaction rate of the quick-wear parts corresponding to the target devices is smaller.

In step 203, a target projected amount of consumable parts is determined based on the consumable part satisfaction rate and a preset target satisfaction rate.

The target satisfaction rate refers to a consumable part satisfaction rate corresponding to the target planning quantity, and it should be noted that the setting of the target satisfaction rate may be determined according to an actual situation, and the target satisfaction rate is not limited herein.

It should be noted that the target planning amount may be determined according to the consumable part satisfaction rate and the maintenance data, and the first consumable part number corresponding to the consumable part satisfaction rate is determined when the consumable part satisfaction rate is greater than the target satisfaction rate; determining the quantity of second worn parts respectively needed for maintaining each device to be maintained according to the maintenance data; determining a target planning quantity according to the first consumable part quantity and each second consumable part quantity;

in one embodiment of the present application, if the first number of wearing parts and the respective second number of wearing parts are determined, the largest number of wearing parts of the first number of wearing parts and the respective second number of wearing parts is used as the target planning number; for example, if the first number of wearing parts is 20, the second numbers of wearing parts are respectively: 18. 9 and 6; when the target planning amount needs to be determined, the largest number of worn parts in the first number of worn parts and the second number of worn parts, and the first number of worn parts 20 are determined, and 20 is taken as the target planning amount.

In an embodiment of the present application, if the first number of wearing parts, each of the second number of wearing parts, and the predetermined margin are determined, the largest number of wearing parts among the first number of wearing parts and each of the second number of wearing parts is determined, and a result of adding the largest number of wearing parts and the margin is used as the target planning quantity; for example, if the first number of wearing parts is 20, the second numbers of wearing parts are respectively: 18. 9 and 6, the preset margin is 3; when the target planning quantity needs to be determined, determining the largest number of worn parts in the first number of worn parts and the second number of worn parts, and determining a first number of worn parts 20; adding the allowance to the first consumable part quantity to serve as a target planning quantity, wherein the target planning quantity is as follows: 20+3=23.

According to the method for planning the worn parts, the failure probability and the reference consumption quantity are obtained by determining the maintenance data, a data basis is provided for subsequently determining the target equipment and the worn part satisfaction rate, and the accuracy of determining the target planning quantity is guaranteed; by determining the target equipment, the loss part satisfaction rate is determined according to the target equipment, guarantee is provided for subsequently determining the target planning quantity of the loss part, and the accuracy of the target planning quantity is further improved; through the consumable part satisfaction rate and the target satisfaction rate, the target planning quantity of the consumable parts is determined, the defect that a consumable part prediction method is lacked in the prior art is overcome, the target planning quantity of the consumable parts consumed during maintenance of the equipment to be maintained is predicted, the target planning quantity corresponding to the consumable parts is rapidly determined, and the efficiency of determining the target planning quantity of the consumable parts is guaranteed.

It should be noted that, by determining the fault threshold of the device to be maintained, the target device is determined from at least two devices to be maintained, as shown in fig. 3, and fig. 3 is a flowchart of another method for planning a consumable part according to an embodiment of the present application. Specifically, the method for planning the wearing parts comprises the following steps:

step 301, determining a fault threshold corresponding to at least two devices to be maintained based on the maintenance data.

It should be noted that the fault threshold is a judgment index used for judging whether the equipment to be repaired is the target equipment; determining target equipment according to the size relation between the fault probability of the equipment to be maintained and the fault threshold; specifically, if the failure probability of the equipment to be maintained is greater than or equal to the failure threshold, the equipment to be maintained is indicated as target equipment; and if the fault probability of the equipment to be maintained is smaller than the fault threshold value, the equipment to be maintained is not the target equipment.

In an embodiment of the application, the fault probabilities of all equipment to be maintained can be obtained according to the maintenance data, the mean value operation is performed on the fault probabilities of all the maintenance equipment, and the operation result is used as the fault threshold.

For example, the fault threshold of the equipment to be maintained can be calculated according to the fault probability of the equipment to be maintained; specifically, the fault probability of the equipment to be maintained is determined, and the fault probability of the equipment to be maintained is substituted into the first fault threshold expression, so that the fault threshold of the equipment to be maintained is determined.

It should be noted that the first failure threshold value analysis expression is the following formula (4):

(4)

wherein the content of the first and second substances,

refers to a failure threshold of the equipment to be serviced; k refers to the total amount of equipment to be serviced;

the fault probability corresponding to the Kth equipment to be repaired is referred to.

In one embodiment of the application, the failure probability of the equipment to be repaired and the reference consumption number of wearing parts of each equipment to be repaired can be determined according to the repair data; and carrying out weighted average operation on the reference consumption quantity and the fault probability, and taking an operation result as a fault threshold value.

For example, a fault threshold of the equipment to be repaired may be calculated according to the reference consumption number and the fault probability; specifically, according to the maintenance data, determining the fault probability of each device to be maintained and the reference consumption number of wearing parts of each device to be maintained; and substituting the reference consumption quantity and the fault probability into a second fault threshold expression so as to determine a fault threshold of the equipment to be repaired.

It should be noted that the second failure threshold value analysis expression is the following formula (5):

(5)

refers to the failure threshold of the equipment to be repaired, and K refers to the total amount of the equipment to be repaired;

referring to the reference consumption quantity of the corresponding consumable part of the Kth equipment to be maintained;

Step 302, according to the maintenance data, determining a target device with a failure probability greater than or equal to a failure threshold value from at least two devices to be maintained.

In an embodiment of the application, according to the maintenance data, the equipment to be maintained, of which the failure probability is greater than the failure threshold value, is determined from at least two pieces of equipment to be maintained, and the equipment to be maintained, of which the failure probability is greater than the failure threshold value, is taken as the target equipment.

For example, the determination of the target device may be accomplished based on a settings data capturer and a data analyzer; specifically, when the target device needs to be determined, data capturing is performed on the maintenance data according to the data capture device, the fault probabilities corresponding to at least two devices to be maintained are determined, the fault probabilities corresponding to the at least two devices to be maintained are analyzed according to the data analyzer, and the target device, of which the fault probability is larger than a fault threshold value, of the at least two devices to be maintained is screened out.

According to the method for planning the worn parts, the fault threshold is determined through the maintenance data, the target equipment is determined, and the successful process of subsequently determining the worn part satisfaction rate is guaranteed; the fault threshold is determined according to the maintenance data, the fault threshold can meet the condition of the equipment to be maintained, the target equipment is determined according to the condition of the equipment to be maintained, the accuracy of determining the target planning quantity is guaranteed, and a judgment basis is provided for subsequently determining the target planning quantity of the worn parts.

It should be noted that, determining the consumable part satisfaction rate is implemented by determining the candidate planning amount, as shown in fig. 4, and fig. 4 is a flowchart of another consumable part planning method provided in this embodiment of the present application. Specifically, the method for determining the consumable part satisfaction rate comprises the following steps:

step 401, determining a candidate planning amount of a consumable part corresponding to the target device according to the reference consumption data of the consumable part corresponding to the target device in the maintenance data.

It should be noted that the candidate planning amount refers to a sum of reference consumption data of the target device corresponding to the consumable part, and can be understood as: the candidate planning quantity is the sum of the reference consumption quantities of the at least two devices to be maintained, the failure probability of which is greater than the failure threshold value.

In summary, the reference consumption numbers of the devices with the failure probability larger than the failure threshold value in the at least two devices to be maintained can be added to determine the candidate planning quantity; therefore, the analytical expression of the candidate planning amount is the following formula (6):

(6)

wherein the content of the first and second substances,

refers to a candidate planning quantity of the target device; k refers to the number of devices to be serviced; j represents an identity label corresponding to the target equipment, and J is less than or equal to K;

referring to a reference consumption number corresponding to the jth target device;

referring to the fault probability corresponding to the J-th target device;

refers to the failure threshold of the equipment to be serviced.

For example, assume that three devices to be maintained are included, the three devices to be maintained are a device to be maintained a, a device to be maintained B, and a device to be maintained C, and the failure probabilities corresponding to the three devices to be maintained are: 0.83, 0.79 and 0.71; and, the reference consumption quantity that three equipment to be maintained respectively corresponds is: 12. 8 and 5. When the candidate planning amount needs to be determined, substituting the reference consumption quantity corresponding to the three devices to be maintained and the fault probability corresponding to the three devices to be maintained into the second fault threshold analytical expression (5) to obtain the following formula (7) based on the second fault threshold analytical expression:

（7）

the expression (7) is subjected to arithmetic processing to determine

=0.7932, the failure threshold is determined to be: 0.7932; and judging the relation between the fault probability of the three devices to be maintained and the fault threshold value based on the fault threshold value, determining that the fault probability of the device A to be maintained is greater than the fault threshold value, and determining the candidate planning quantity to be 12 according to the analytical expression of the candidate planning quantity.

Step 402, determining a consumable part satisfaction rate according to the candidate planning amount and the reference consumption data of the consumable parts of the equipment to be maintained in the maintenance data.

In an embodiment of the application, a consumable part satisfaction rate can be calculated according to the candidate planning quantity, the fault probability of each device to be maintained and the reference consumption quantity of the consumable parts; specifically, the candidate planning quantity, the fault probability of each to-be-maintained device and the reference consumption number of the worn parts are determined, and the candidate planning quantity, the fault probability of each to-be-maintained device and the reference consumption number of the worn parts are substituted into a worn part satisfaction rate analysis expression, so that the worn part satisfaction rate is obtained.

It should be noted that the consumable part satisfies the rate resolution expression as the following formula (8):

(8)

wherein the content of the first and second substances,

refers to a candidate planning quantity of the target device; p refers to the candidate planning quantity

A corresponding consumable part satisfaction rate;

the reference consumption number of the K-th equipment to be maintained corresponding to the wearing part is referred to;

the fault probability corresponding to the Kth device to be maintained is referred to.

For example, assume that three devices to be maintained are included, the three devices to be maintained are a device to be maintained a, a device to be maintained B, and a device to be maintained C, and the failure probabilities corresponding to the three devices to be maintained are: 0.83, 0.79 and 0.71; and, the reference consumption quantity that three equipment to be maintained respectively corresponds is: 12. 8 and 5; and the candidate planning quantity is 12. When the consumable part satisfaction rate needs to be determined, substituting the fault probability corresponding to each of the three devices to be maintained, the reference consumption number corresponding to each of the three devices to be maintained and the candidate planning amount into a consumable part satisfaction rate analytical expression (8) to obtain the following formula (9):

（9）

expression (9) was subjected to arithmetic processing, and P =0.502269 was determined. The wearware satisfaction rate was 0.502269.

According to the method for planning the consumable parts, the candidate planning quantity is determined by referring to the consumption data, the preliminary determination of the planning quantity is realized, a judgment basis is provided for the subsequent determination of the target planning quantity, and the efficiency of the subsequent determination of the target planning quantity is ensured; and determining a consumable part satisfaction rate according to the candidate planning quantity, ensuring that the consumable part satisfaction rate can meet the actual condition of the target equipment, ensuring the accuracy of the consumable part satisfaction rate and ensuring the accuracy of the target planning quantity.

It should be noted that the target planning amount is determined by determining whether the consumable part satisfaction rate is smaller than the target satisfaction rate, as shown in fig. 5, and fig. 5 is a flowchart of another consumable part planning method provided in this embodiment of the present application. Specifically, the method for determining the target planning quantity comprises the following steps:

step 501, determining maintenance data corresponding to at least two devices to be maintained, wherein the maintenance data comprises the fault probability of each device to be maintained and the reference consumption number of wearing parts.

In the embodiment of the present application, step 501 may be implemented by using any one of the embodiments of the present application, which is not limited herein and is not described in detail herein.

Step 502, determining a target device from at least two devices to be maintained based on the maintenance data, and determining a consumable part satisfaction rate according to the target device and the maintenance data.

In the embodiment of the present application, step 502 may be implemented by any one of the embodiments of the present application, which is not limited in this embodiment and is not described again.

In step 503, it is determined whether the consumable part satisfaction rate is less than the target satisfaction rate, if yes, step 504 is executed, and if not, step 505 is executed.

Step 504, updating the target device according to the fault threshold and the maintenance data; and based on the updated target equipment, returning to execute the operation of determining the consumable part satisfaction rate according to the target equipment and the maintenance data.

And 505, determining a target planning quantity of the worn parts according to the candidate planning quantity of the worn parts corresponding to the target equipment and the maintenance data.

Wherein, updating the target device wearing part means: adding a fault threshold value into the maintenance data, and sequencing at least two devices to be maintained according to the fault probability in the added maintenance data; and updating the target equipment according to the sequencing result.

In one embodiment of the present application, updating the target device refers to: and according to the sequencing result, the equipment to be maintained with the closest fault probability is used as new target equipment, so that the target equipment is updated.

For example, the following steps are carried out: the hypothesis includes that three maintenance of treating equipment, three maintenance of treating equipment be respectively for treating maintenance of equipment A, treat maintenance of equipment B and treat maintenance of equipment C, and the three fault probability that maintenance of equipment respectively corresponds of treating is: 0.83, 0.79 and 0.71; the reference consumption quantity respectively corresponding to the three devices to be maintained is as follows: 12. 8 and 5; the failure thresholds for the three devices to be serviced are: 0.7932, wherein the equipment a to be repaired is the target equipment. When the target equipment needs to be updated, adding the fault threshold value into the maintenance data, and performing sequencing processing according to the fault probability in the maintenance data, wherein the sequencing result is determined as follows: 0.71 and 0.79 are formed into 0.7932 and 0.83; according to the sorting result, determining that the fault probability closest to the fault threshold value is 0.79; taking the equipment B to be maintained corresponding to the fault probability of 0.79 as new target equipment; the updated target device includes: equipment B to be maintained and equipment A to be maintained.

Further illustratively, returning to performing the operation of determining the consumable part satisfaction rate based on the updated target device and the repair data may include the steps of: in summary, determining the updated target device includes: a device B to be maintained and a device A to be maintained. When the consumable part satisfaction rate needs to be determined, substituting the fault probability corresponding to each of the three devices to be maintained, the reference consumption number corresponding to each of the three devices to be maintained and the candidate planning amount into a consumable part satisfaction rate analysis expression (8) to obtain the following formula (10):

（10）

expression (10) was subjected to arithmetic processing, and P = 0.820978 was determined. The consumable part satisfaction rate corresponding to the updated target device is 0.820978. And if the consumable part satisfaction rate corresponding to the updated target equipment is greater than the target satisfaction rate, determining the target planning quantity of the consumable part according to the updated candidate planning quantity and the updated maintenance data of the target equipment.

Further illustratively, determining a target projected amount of a consumable part may include the steps of: if the judgment basis of the target planning quantity is as follows: the numerical value with the largest numerical value is the candidate planning quantity and the reference consumption quantity of each worn part of the equipment to be maintained; in conclusion, the candidate planning quantity of the updated target equipment is determined to be 20, and the reference consumption quantity of the consumed parts of the equipment to be maintained is determined to be 5; the candidate projection amount value is the largest, and the target projection amount may be determined to be 20.

According to the consumable part planning method, whether the consumable part satisfaction rate is smaller than the target satisfaction rate or not is judged, the target planning quantity can meet the consumable part requirement for maintaining the equipment to be maintained, the target planning quantity is set to meet the target satisfaction rate, the accuracy of the target planning quantity is further improved, the defect that a consumable part prediction method is lacked in the prior art is overcome, the target planning quantity corresponding to the consumable part is rapidly determined, and the efficiency of determining the target planning quantity of the consumable part is guaranteed.

In an embodiment of the present application, as shown in fig. 6, fig. 6 is a flowchart of another consumable part planning method provided in the embodiment of the present application, and when a target planning amount of consumable parts corresponding to at least two devices to be repaired needs to be determined:

step 601, determining maintenance data corresponding to at least two devices to be maintained, wherein the maintenance data comprises the fault probability of each device to be maintained and the reference consumption number of the worn parts.

Step 602, determining a failure threshold corresponding to at least two devices to be repaired based on the repair data.

Step 603, determining a candidate planning quantity of the wearing parts corresponding to the target device according to the reference consumption data of the wearing parts corresponding to the target device in the maintenance data.

In step 604, it is determined whether the consumable part satisfaction rate is less than the target satisfaction rate, if yes, go to step 605, otherwise go to step 606.

Step 605, updating the target device according to the fault threshold and the maintenance data; and based on the updated target equipment, returning to execute the operation of determining the consumable part satisfaction rate according to the target equipment and the maintenance data.

Step 606, determining a target planning amount of the worn parts according to the candidate planning amount of the worn parts corresponding to the target equipment and the maintenance data.

In an embodiment of the application, when a target planning amount of consumable parts corresponding to 11 devices to be maintained needs to be determined, the 11 devices to be maintained are respectively numbered from 1 to 11, the devices to be maintained with different numbers are different devices, and maintenance data of the 11 devices to be maintained are determined, wherein the fault probability of the devices to be maintained does not directly correspond to the reference consumption amount. Specifically, the maintenance device of the 11 devices to be maintained includes a failure probability corresponding to each of the 11 devices to be maintained and a reference consumption number corresponding to each of the 11 devices to be maintained. The maintenance data of 11 devices to be maintained are shown in table 3 below;

TABLE 3 probability of failure and reference consumption number of 11 devices to be repaired

When the target projected amount of wearing parts corresponding to 11 devices to be repaired needs to be determined,

substituting the fault probability of the equipment to be maintained and the reference consumption number of the wearing parts in the maintenance data into a second fault threshold value analytical expression (5) to obtain:

the failure threshold was determined to be 0.007133.

Based on the failure threshold and the maintenance data, determining that the target device with the failure probability greater than or equal to the failure threshold is: no. 8 equipment to be maintained, no. 10 equipment to be maintained and No. 7 equipment to be maintained. Adding the reference consumption numbers of the No. 8 equipment to be maintained, the No. 10 equipment to be maintained and the No. 7 equipment to be maintained, and further determining the candidate planning quantity; substituting the fault probability of the equipment to be maintained and the reference consumption number of the wearing parts in the maintenance data into an analytical expression (6) of the candidate planning quantity to obtain:

and determining the candidate planning quantity corresponding to the target equipment as 14.

Presetting a target satisfaction rate to be 0.9; and substituting the candidate planning amount, the fault probability of the equipment to be maintained and the reference consumption number of the wearing parts into a wearing part satisfaction rate analysis expression (8). Obtaining:

the consumable part satisfaction rate corresponding to the 11 devices to be repaired is determined to be 0.707858.

Determining whether the wearware satisfaction rate is less than the target satisfaction rate, since 0.707858 & lt 0.9 > the consumable satisfaction rate is less than the target satisfaction rate.

Adding the fault threshold value into maintenance data, and sequencing at least two devices to be maintained according to the fault probability in the added maintenance data;

in summary, the addition of the failure probability to the repair data can be formulated as:

，

wherein the content of the first and second substances,

-

the respective corresponding failure probabilities of the equipment to be repaired of numbers 1-11 are referred to,

refers to a failure probability threshold.

To the formula after adding the fault threshold

And performing ascending processing to obtain a sorted formula:

。

and determining a sorting result according to the sorted formula. The results of the ranking are shown in table 4 below.

TABLE 4 sequencing results of 11 devices to be repaired

And according to the sequencing result, taking the equipment to be maintained with the closest fault probability as new target equipment, finishing updating the target equipment, and taking the No. 8 equipment to be maintained, the No. 10 equipment to be maintained, the No. 7 equipment to be maintained and the No. 1 equipment to be maintained as updated target equipment.

Substituting the candidate planning quantity of the target equipment, the fault probability of the equipment to be maintained and the reference consumption quantity of the worn parts into a worn part satisfaction rate analytical expression (8) to obtain:

it is determined whether the wear parts satisfaction rate is less than the target satisfaction rate, and since 0.787366 is straw 0.9, the wear parts satisfaction rate is less than the target satisfaction rate. And updating the target equipment again according to the sequencing result, re-determining the consumable part satisfaction rate corresponding to the target equipment, and further realizing iterative processing on the consumable part satisfaction rate until the consumable part satisfaction rate is greater than or equal to the target satisfaction rate.

Further, when regard as the target equipment after the renewal with No. 8 equipment of waiting to maintain, no. 10 equipment of waiting to maintain, no. 7 equipment of waiting to maintain, no. 1 equipment of waiting to maintain No. 4 equipment of waiting to maintain, no. 6 equipment of waiting to maintain, no. 11 equipment of waiting to maintain and No. 3 equipment of waiting to maintain.

Substituting the updated candidate planning quantity of the target equipment, the fault probability of the equipment to be maintained and the reference consumption quantity of the worn parts into a worn part satisfaction rate analytical expression (8) to obtain:

and determining whether the consumable part satisfaction rate is less than the target satisfaction rate, wherein the consumable part satisfaction rate is greater than the target satisfaction rate because of 0.92493> -0.9.

The updated candidate planning quantity of the target device is as follows:

the updated candidate plan amount for the target device is determined to be 42.

If the judgment basis of the target planning quantity is as follows: the candidate planning quantity and the reference consumption quantity of 11 worn parts of the equipment to be maintained have the largest value; in summary, it is determined that the updated candidate planning amount of the target device is 42, and the reference consumption amounts of the 11 consumed devices to be repaired are: 9. 17, 12, 4, 3, 2, 5, 6, 4, 3 and 1; since the candidate planning quantity value is the largest, the target planning quantity may be determined to be 42.

As can be seen from the above, the target planning quantity S is calculated by the following formula:

it should be noted that, because there is no corresponding relationship between the reference consumption quantity and the failure probability of the equipment to be maintained, there are cases where the failure probability is low but the reference consumption quantity is large and the failure probability is high but the reference consumption quantity is small, and in order to ensure that the target planning quantity can meet the normal maintenance requirement of the staff, the target planning quantity should be determined by taking the maximum value of the candidate planning quantity and the reference consumption quantities of all the consumable parts as the target planning quantity.

It should be understood that, although the steps in the flowcharts related to the above embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the application also provides a consumable part planning device for realizing the consumable part planning method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so that specific limitations in one or more embodiments of the device for planning wearing parts provided below can be referred to the limitations of the method for planning wearing parts in the above description, and are not described herein again.

In an embodiment, as shown in fig. 7, fig. 7 is a block diagram of a device for planning a consumable part according to an embodiment of the present application, and the device for planning a consumable part includes: a first determination module 710, a second determination module 720, and a third determination module 730, wherein:

the first determining module 710 is configured to determine maintenance data corresponding to at least two devices to be maintained, where the maintenance data includes a failure probability of each device to be maintained and a reference consumption amount of consumable parts.

A second determining module 720, configured to determine a target device from the at least two devices to be maintained based on the maintenance data, and determine a consumable part satisfaction rate according to the target device and the maintenance data.

A third determining module 730, configured to determine a target projected amount of the consumable part based on the consumable part satisfying rate and a preset target satisfying rate.

According to the consumable part planning device, the fault probability and the reference consumption quantity are obtained by determining the maintenance data, a data basis is provided for subsequently determining the target equipment and the consumable part satisfaction rate, and the accuracy of determining the target planning quantity is guaranteed; by determining the target equipment, the loss piece satisfaction rate is determined according to the target equipment, guarantee is provided for subsequently determining the target planning quantity of the loss pieces, and the accuracy of the target planning quantity is further improved; through the consumable part satisfaction rate and the target satisfaction rate, the target planning quantity of the consumable parts is determined, the defect that a consumable part prediction method is lacked in the prior art is overcome, the target planning quantity of the consumable parts consumed during maintenance of the equipment to be maintained is predicted, the target planning quantity corresponding to the consumable parts is rapidly determined, and the efficiency of determining the target planning quantity of the consumable parts is guaranteed.

In an embodiment, as shown in fig. 8, fig. 8 is a block diagram of another apparatus for planning a consumable part according to an embodiment of the present application, and provides an apparatus for planning a consumable part, in which the second determining module 820 includes: a first determination unit 821 and a second determination unit 822.

The first determining unit 821 is configured to determine, based on the maintenance data, failure thresholds corresponding to at least two devices to be maintained.

A second determining unit 822, configured to determine, according to the maintenance data, a target device with a failure probability greater than or equal to a failure threshold from among the at least two devices to be maintained.

Wherein 810, 830 in fig. 8 and 710, 730 in fig. 7 have the same function and structure.

According to the worn part planning device, the fault threshold is determined through the maintenance data, the target equipment is determined, and the successful determination of the worn part satisfaction rate is guaranteed; the fault threshold is determined according to the maintenance data, the fault threshold can meet the condition of the equipment to be maintained, the target equipment is determined according to the condition of the equipment to be maintained, the accuracy of determining the target planning quantity is guaranteed, and a judgment basis is provided for subsequently determining the target planning quantity of the worn parts.

In an embodiment, as shown in fig. 9, fig. 9 is a block diagram of a planning apparatus for a wearing part according to another embodiment of the present application, and provides a planning apparatus for a wearing part, in which the second determining module 920 further includes: a third determining unit 923 and a fourth determining unit 924.

A third determining unit 923, configured to determine a candidate planning amount of the consumable part corresponding to the target device according to the reference consumption data of the consumable part corresponding to the target device in the maintenance data;

a fourth determining unit 924, configured to determine a consumable part satisfaction rate according to the candidate planning amount and reference consumption data of consumable parts of each device to be repaired in the repair data.

910 and 930 in fig. 9 and 810 and 830 in fig. 8 have the same functions and structures.

According to the planning device for the consumable parts, the candidate planning quantity is determined by referring to the consumption data, the preliminary determination of the planning quantity is realized, a judgment basis is provided for the subsequent determination of the target planning quantity, and the efficiency of the subsequent determination of the target planning quantity is ensured; and determining a consumable part satisfaction rate according to the candidate planning quantity, ensuring that the consumable part satisfaction rate can meet the actual condition of the target equipment, ensuring the accuracy of the consumable part satisfaction rate and ensuring the accuracy of the target planning quantity.

In an embodiment, as shown in fig. 10, fig. 10 is a block diagram of a planning apparatus for a consumable part according to another embodiment of the present application, and provides the planning apparatus for a consumable part, in which the third determining module 1030 further includes: a fifth determining unit 1031, a sixth determining unit 1032, and a seventh determining unit 1033.

A fifth determination unit 1031 for determining whether the consumable satisfaction rate is less than the target satisfaction rate;

a sixth determining unit 1032, configured to update the target device according to the failure threshold and the maintenance data if the failure occurs; and based on the updated target equipment, returning to execute the operation of determining the consumable part satisfaction rate according to the target equipment and the maintenance data.

It should be noted that, the fault threshold is added to the maintenance data, and the at least two devices to be maintained are sequenced according to the fault probability in the added maintenance data; and updating the target equipment according to the sequencing result.

A seventh determining unit 1033, configured to determine, if the target planning amount of the consumable part is not the target planning amount, according to the candidate planning amount of the consumable part and the maintenance data corresponding to the target device.

1010 and 1020 in fig. 10 and 910 and 920 in fig. 9 have the same functions and structures.

According to the consumable part planning device, whether the consumable part satisfaction rate is smaller than the target satisfaction rate or not is judged, the target planning quantity can meet the consumable part requirement for maintaining the equipment to be maintained, the target planning quantity is set to meet the target satisfaction rate, the accuracy of the target planning quantity is further improved, the defect that a consumable part prediction method is lacked in the prior art is overcome, the corresponding target planning quantity of the consumable part is rapidly determined, and the efficiency of determining the target planning quantity of the consumable part is guaranteed.

The modules in the consumable planning apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 11. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of planning a consumable part. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by those skilled in the art that the configuration shown in fig. 11 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:

In one embodiment, the processor, when executing the computer program, further performs the steps of:

determining fault thresholds corresponding to at least two devices to be maintained based on the maintenance data;

In one embodiment, the processor when executing the computer program further performs the steps of:

and updating the target equipment according to the sequencing result.

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

determining maintenance data corresponding to at least two devices to be maintained, wherein the maintenance data comprise the fault probability of each device to be maintained and the reference consumption number of wearing parts;

In one embodiment, the computer program when executed by the processor further performs the steps of:

and updating the target equipment according to the sequencing result.

In one embodiment, a computer program product is provided, comprising a computer program which when executed by a processor performs the steps of:

and determining a target planning amount of the worn parts based on the worn part satisfaction rate and a preset target satisfaction rate.

if yes, updating the target equipment according to the fault threshold value and the maintenance data; and based on the updated target equipment, returning to execute the operation of determining the consumable part satisfaction rate according to the target equipment and the maintenance data.

and updating the target equipment according to the sequencing result.

It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases involved in the embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method of planning a consumable, the method comprising:

determining target equipment from the at least two pieces of equipment to be maintained based on the maintenance data, and determining candidate planning quantity of the consumable part corresponding to the target equipment according to reference consumption data of the consumable part corresponding to the target equipment in the maintenance data;

determining the consumable part satisfaction rate according to the candidate planning amount and the reference consumption data of the consumable parts of the equipment to be maintained in the maintenance data;

determining whether the consumable part satisfaction rate is less than the target satisfaction rate;

if yes, updating the target equipment according to a fault threshold and the maintenance data, and returning to execute the operation of determining the consumable part satisfaction rate according to the target equipment and the maintenance data based on the updated target equipment;

if not, determining the target planning quantity of the worn part according to the candidate planning quantity of the worn part corresponding to the target equipment and the maintenance data;

wherein, confirm that each treats the fault probability of maintenance equipment in the maintenance data that at least two are treated the maintenance equipment to correspond, include:

determining the failure rate of each device to be maintained according to the average fault interval time corresponding to the device to be maintained; the failure rate corresponding to the equipment to be maintained and the mean fault interval time are in a reciprocal relation;

and determining the fault probability of each device to be maintained in the maintenance data corresponding to at least two devices to be maintained according to the failure rate and the working time of each device to be maintained.

2. The method of claim 1, wherein the determining a target device from the at least two devices to be serviced based on the service data comprises:

determining fault thresholds corresponding to the at least two devices to be maintained based on the maintenance data;

and according to the maintenance data, determining the target equipment with the fault probability larger than or equal to the fault threshold value from the at least two pieces of equipment to be maintained.

3. The method of claim 1, wherein updating the target equipment consumable based on the fault threshold and the repair data comprises:

adding the fault threshold value into the maintenance data, and sequencing the at least two devices to be maintained according to the fault probability in the added maintenance data;

and updating the target equipment according to the sequencing result.

4. An apparatus for planning a consumable, the apparatus comprising:

a second determining module, configured to determine a target device from the at least two devices to be maintained based on the maintenance data, and determine a candidate planning amount of the consumable part corresponding to the target device according to reference consumption data of the consumable part corresponding to the target device in the maintenance data; determining the consumable part satisfaction rate according to the candidate planning amount and the reference consumption data of the consumable parts of the equipment to be maintained in the maintenance data;

a third determination module to determine whether the consumable satisfaction rate is less than the target satisfaction rate; if yes, updating the target equipment according to a fault threshold and the maintenance data, and returning to execute the operation of determining the consumable part satisfaction rate according to the target equipment and the maintenance data based on the updated target equipment; if not, determining the target planning quantity of the worn part according to the candidate planning quantity of the worn part corresponding to the target equipment and the maintenance data;

the first determining module, when performing determining the failure probability of each device to be maintained in the maintenance data corresponding to at least two devices to be maintained, is specifically configured to: determining the failure rate of each device to be maintained according to the average fault interval time corresponding to the device to be maintained; the failure rate corresponding to the equipment to be maintained and the mean fault interval time are in a reciprocal relation; and determining the fault probability of each device to be maintained in the maintenance data corresponding to at least two devices to be maintained according to the failure rate and the working time of each device to be maintained.

5. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 3 when executing the computer program.

6. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 3.