CN116579572A

CN116579572A - Maintenance time-consuming mechanical part spare part analysis method and device obeying normal distribution

Info

Publication number: CN116579572A
Application number: CN202310587754.0A
Authority: CN
Inventors: 邵松世; 胡俊波; 莫小杰; 李华
Original assignee: Naval University of Engineering PLA
Current assignee: Naval University of Engineering PLA
Priority date: 2023-05-23
Filing date: 2023-05-23
Publication date: 2023-08-11

Abstract

The application provides a method and a device for analyzing mechanical spare parts with maintenance time consumption obeying normal distribution, comprising the following steps: step (1), setting the spare part quantity i=0 of mechanical parts and the spare part guarantee probability pb=0; the mechanical part life obeys a first normal distribution; step (2), calculating joint probability p by combining the first normal distribution parameters; step (3), updating the spare part guarantee probability as follows: pb=pb+p; step (4), if the updated spare part guarantee probability is smaller than a preset value, updating the number of spare parts to be: i=i+1; otherwise, executing the step (7); step (5), determining a second normal distribution obeyed when the maintenance time of the mechanical part is not 0, calculating p based on the first normal distribution parameter and the second normal distribution parameter, and then executing the step (3) and then entering the step (6); step (6), if the updated spare part guarantee probability is smaller than a preset value, updating the number of spare parts to be: i=i+1, and executing step (5), otherwise executing step (7); and (7) taking the final spare part number as the spare part demand.

Description

Maintenance time-consuming mechanical part spare part analysis method and device obeying normal distribution

Technical Field

The application belongs to the field of mechanical spare part analysis, and particularly relates to a method and a device for analyzing mechanical spare parts, which are time-consuming to maintain and obey normal distribution.

Background

Patent document CN109508792a discloses a method for determining a supply list of consumable supplies for aircraft inspection, which discloses a method for determining the supply demand of consumable supplies, so as to ensure that the inspection consumable supplies are accurately and sufficiently provided.

However, in the method of the above patent document, the total task time and maintenance time of the aircraft are not considered, and it is conceivable that if the maintenance time is not negligible, the time for actually performing the task by the aircraft will be shortened, and if the spare parts consumable is prepared according to the task time originally specified, the preparation of the spare parts of the aircraft will inevitably exceed the actual demand, and a large amount of consumable will be wasted.

Disclosure of Invention

Aiming at the defects of the prior art, the application aims to provide a mechanical spare part analysis method and device with maintenance time consumption obeying normal distribution, and aims to solve the problem that the existing mechanical spare part analysis method does not consider task time and actual maintenance time consumption, so that spare parts are wasted.

To achieve the above object, in a first aspect, the present application provides a method for analyzing a mechanical spare part, which is time-consuming to repair and obeys normal distribution, comprising the steps of:

step (1), initializing, namely setting the spare part quantity i=0 of the mechanical parts, and setting the spare part guarantee probability Pb=0; wherein the lifetime of the mechanical part follows a first normal distribution;

step (2), calculating the joint probability p of the service life of the mechanical part and the maintenance time consumption by combining the first normally distributed parameters;

step (3), updating the spare part guarantee probability as follows: pb=pb+p;

step (4), if the updated spare part guarantee probability is smaller than a preset value, updating the number of spare parts to be: i=i+1; otherwise, executing the step (7);

step (5), determining a second normal distribution obeyed when the maintenance time consumption of the mechanical part is not 0, calculating the joint probability p based on the parameters of the first normal distribution and the parameters of the second normal distribution, and then entering step (6) after the step (3) is executed;

step (6), if the updated spare part guarantee probability is smaller than a preset value, updating the number of spare parts to be: i=i+1, and executing step (5), otherwise executing step (7);

and (7) taking the finally determined spare part quantity i as the spare part demand of the mechanical part.

In one possible example, the step (2) is specifically:

wherein a and b correspond to the mean and root variance of the first normal distribution, respectively; t represents the task time of the machine, and x represents the life variable of the machine.

In one possible example, the step (5) is specifically:

wherein c and d correspond to the mean and root variance of the second normal distribution, respectively; t represents a time variable in general sense; y represents a maintenance time-consuming variable of the machine.

In a second aspect, the present application provides a machine part spare part analysis device for maintaining time consumption compliant with normal distribution, comprising:

the initialization module is used for initializing, setting the spare part quantity i=0 of the mechanical parts and the spare part guarantee probability pb=0; wherein the lifetime of the mechanical part follows a first normal distribution;

the joint probability first calculation module is used for calculating joint probability p of service life and maintenance time consumption of the mechanical part by combining the parameters of the first normal distribution;

the first updating module of the guarantee probability is used for updating the spare part guarantee probability into: pb=pb+p;

the first updating module of spare part quantity is used for updating the spare part quantity into if the updated spare part guarantee probability is smaller than a preset value: i=i+1; otherwise, the demand determining module is instructed to execute related operations;

the joint probability second calculation module is used for determining a second normal distribution obeyed when the maintenance time of the mechanical part is not 0, calculating the joint probability p based on the parameters of the first normal distribution and the parameters of the second normal distribution, then updating the guarantee probability by referring to the updating mode of the first updating module of the guarantee probability, and indicating the second updating module of the number of spare parts to execute related operations;

the second updating module of spare part quantity is used for updating the spare part quantity into if the updated spare part guarantee probability is smaller than a preset value: i=i+1, and instructs the joint probability second calculation module to update and calculate the joint probability, otherwise instructs the demand determination module to execute the related operation;

and the demand determining module is used for taking the finally determined spare part quantity i as the spare part demand of the mechanical part.

In one possible example, the formula adopted by the first calculation module of joint probability is specifically:

In one possible example, the formula adopted by the joint probability second calculation module is specifically:

In a third aspect, the present application provides an electronic device comprising: at least one memory for storing a program; at least one processor for executing a memory-stored program, the processor being adapted to perform the method of the first aspect or any one of the possible examples of the first aspect when the memory-stored program is executed.

In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which, when run on a processor, causes the processor to perform the method described in the first aspect or any one of the possible examples of the first aspect.

In a fifth aspect, the application provides a computer program product which, when run on a processor, causes the processor to perform the method described in the first aspect or any one of the possible examples of the first aspect.

In general, the above technical solutions conceived by the present application have the following beneficial effects compared with the prior art:

the application provides a method and a device for analyzing mechanical spare parts, which are subjected to normal distribution of maintenance time consumption.

Drawings

FIG. 1 is a flow chart of a method for analyzing mechanical spare parts, which is provided by an embodiment of the application and is time-consuming to maintain and obeys normal distribution;

FIG. 2 is a comparative schematic diagram of the results of an example provided by an embodiment of the present application;

FIG. 3 is a schematic diagram of a system for analyzing mechanical parts with normal distribution of maintenance time consumption according to an embodiment of the present application.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

The term "and/or" in the present application is an association relation describing an association object, and indicates that three relations may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In the present application, the symbol "/" indicates that the associated object is or is a relationship, for example, A/B indicates A or B.

The terms first and second and the like in the description and in the claims, are used for distinguishing between different objects and not necessarily for describing a particular sequential or chronological order of the objects. For example, the first response message and the second response message, etc. are used to distinguish between different response messages, and are not used to describe a particular order of response messages.

In embodiments of the application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "e.g." in an embodiment should not be taken as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.

In the description of the embodiments of the present application, unless otherwise specified, the meaning of "plurality" means two or more, for example, the meaning of a plurality of processing units means two or more, or the like; the plurality of elements means two or more elements and the like.

FIG. 1 is a flow chart of a method for analyzing mechanical spare parts, which is provided by an embodiment of the application and is time-consuming to maintain and obeys normal distribution; as shown in fig. 1, the method comprises the following steps:

step (3), updating the spare part guarantee probability as follows: pb=pb+p;

In one particular embodiment, the life of the mechanical part is generally subject to a normal distribution, such as: a confluence ring, a gear box, a speed reducer and the like. If the random variable is subjected to normal distribution N (mu, sigma), mu is the mean value, sigma is the root variance, and the probability density function is

The task time T, the spare part guarantee probability index P and the service life of a certain mechanical part are known, the service life of the mechanical part is subjected to normal distribution N (a, b), the mechanical part is repaired after the mechanical part fails, the maintenance time consumption is subjected to normal distribution N (c, d), c is the maintenance time consumption average value, and d is the maintenance time consumption root variance.

The application provides a spare part demand quantity calculating method considering maintenance time consumption, which comprises the following specific steps:

(1) Initializing, namely enabling the number i=0 of spare parts and the spare part guarantee probability Pb=0;

(2) Calculating the joint probability p of service life and maintenance time consumption corresponding to the number of spare parts

When i=0, the number of the cells,

when i is greater than 0, the method comprises,

(3) Updating spare part guarantee probability pb=pb+p;

(4) If Pb < P, updating i=i+1, executing (2), otherwise executing (4);

(5) Let spare part demand s=i, pb be its spare part guarantee probability, output s and Pb.

Calculating: the service life of a certain mechanical part is subjected to normal distribution N (90,28), the task time is 300h, the time for repairing faults is subjected to normal distribution N (10, 4), the spare part guarantee probability is required to be not lower than 0.9, and the spare part demand at the moment is calculated.

Solution: (1) Initializing, namely enabling the number i=0 of spare parts and the spare part guarantee probability Pb=0;

and (4) performing the steps (2) - (4) repeatedly, and obtaining the relevant results shown in table 1.

TABLE 1

Spare parts number i	Joint probability p	Spare part guarantee probability Pb
			0	3.19E-14	3.19E-14
1	0.003	0.003
			2	0.416	0.419
3	0.526	0.945

(5) The spare part demand is 3, the corresponding spare part guarantee probability is 0.945, and the index requirement of not lower than 0.9 is met.

The key of the method is to calculate the spare part guarantee probability corresponding to the number of spare parts. The method of the application considering maintenance time consumption, the simulation method considering maintenance time consumption and the former method in the industry under the ideal condition of neglecting maintenance time consumption are adopted respectively, and 3 spare part guarantee probability results of 0-4 of the number of spare parts of the above example are shown in fig. 2. Fig. 2 shows that: the evaluation result and the simulation result of the method are very consistent, and the practical situation that the working time during the task occupation period due to time consuming maintenance is well reflected, the spare part requirement is reduced, and the spare part guarantee probability is higher when the number of the spare parts is the same is well reflected. In the face of the same index requirement that the spare part guarantee probability is not lower than 0.9, the spare part demand which is neglected and considered to be maintained is 4 and 3 respectively. When the actual situation that the maintenance time is relatively long is faced, the method can more reasonably determine the spare part demand, and effectively solve the problem of excessive spare part preparation caused by the prior method in the industry.

FIG. 3 is a schematic diagram of a system for analyzing a mechanical spare part with maintenance time consumption subject to normal distribution according to an embodiment of the present application, as shown in FIG. 3, including:

an initialization module 301, configured to initialize, set a spare part number i=0 of the mechanical parts, and a spare part guarantee probability pb=0; wherein the lifetime of the mechanical part follows a first normal distribution;

a joint probability first calculation module 302, configured to calculate a joint probability p of a service life of the mechanical part and a maintenance time consumption in combination with the parameters of the first normal distribution;

the guarantee probability first updating module 303 is configured to update the spare part guarantee probability to: pb=pb+p;

the first update module 304 of the number of spare parts is configured to update the number of spare parts to: i=i+1; otherwise, the demand determining module is instructed to execute related operations;

the joint probability second calculation module 305 is configured to determine a second normal distribution obeyed when the maintenance time of the mechanical part is not 0, calculate the joint probability p based on the parameter of the first normal distribution and the parameter of the second normal distribution, and then update the guarantee probability with reference to the update mode of the guarantee probability first update module 302, and instruct the spare part number second update module 306 to perform a related operation;

the second update module 306 for updating the number of spare parts to be: i=i+1, and instructs the joint probability second calculation module 305 to update the calculated joint probability, and otherwise instructs the demand determination module 307 to perform the relevant operation;

the demand determining module 307 is configured to take the finally determined number i of spare parts as the spare part demand of the mechanical part.

It should be understood that, the foregoing apparatus is used to perform the method in the foregoing embodiment, and corresponding program modules in the apparatus implement principles and technical effects similar to those described in the foregoing method, and reference may be made to corresponding processes in the foregoing method for the working process of the apparatus, which are not repeated herein.

Based on the method in the above embodiment, the embodiment of the application provides an electronic device. The apparatus may include: at least one memory for storing programs and at least one processor for executing the programs stored by the memory. Wherein the processor is adapted to perform the method described in the above embodiments when the program stored in the memory is executed.

Based on the method in the above embodiment, the embodiment of the present application provides a computer-readable storage medium storing a computer program, which when executed on a processor, causes the processor to perform the method in the above embodiment.

Based on the method in the above embodiments, an embodiment of the present application provides a computer program product, which when run on a processor causes the processor to perform the method in the above embodiments.

It is to be appreciated that the processor in embodiments of the application may be a central processing unit (centralprocessing unit, CPU), other general purpose processor, digital signal processor (digital signalprocessor, DSP), application specific integrated circuit (application specific integrated circuit, ASIC), field programmable gate array (field programmable gate array, FPGA) or other programmable logic device, transistor logic device, hardware components, or any combination thereof. The general purpose processor may be a microprocessor, but in the alternative, it may be any conventional processor.

The method steps in the embodiments of the present application may be implemented by hardware, or may be implemented by executing software instructions by a processor. The software instructions may be comprised of corresponding software modules that may be stored in random access memory (random access memory, RAM), flash memory, read-only memory (ROM), programmable ROM (PROM), erasable programmable PROM (EPROM), electrically erasable programmable EPROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted across a computer-readable storage medium. The computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.

It will be appreciated that the various numerical numbers referred to in the embodiments of the present application are merely for ease of description and are not intended to limit the scope of the embodiments of the present application.

It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the application and is not intended to limit the application, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.

Claims

1. The method for analyzing the mechanical spare parts with maintenance time consumption obeying normal distribution is characterized by comprising the following steps of:

step (3), updating the spare part guarantee probability as follows: pb=pb+p;

2. The method according to claim 1, wherein the step (2) is specifically:

3. The method according to claim 2, wherein the step (5) is specifically:

4. A maintenance time consuming normal distribution compliant mechanical part spare part analysis device, comprising:

5. The apparatus of claim 4, wherein the joint probability first calculation module employs a formula specifically including:

6. The apparatus of claim 5, wherein the joint probability second calculation module employs a formula specifically including:

7. An electronic device, comprising:

at least one memory for storing a program;

at least one processor for executing the memory-stored program, which processor is adapted to perform the method according to any of claims 1-3, when the memory-stored program is executed.

8. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when run on a processor, causes the processor to perform the method according to any of claims 1-3.

9. A computer program product, characterized in that the computer program product, when run on a processor, causes the processor to perform the method according to any of claims 1-3.