Method and device for calculating average consumption of spare parts for mechanical general parts

Abstract

The application provides a kind of calculating method and device for the average consumption of spare parts of mechanical general parts, the method comprises: determining the life probability density function based on the normal distribution that the life of each mechanical unit of mechanical general parts is subject to, and determining the repair time probability density function based on the normal distribution that the repair time of each mechanical unit is subject to;Based on the life probability density function, repair time probability density function and the task time of each mechanical unit, determine the task success probability and the support success probability corresponding to each mechanical unit when the spare parts consumption is 0, 1, …, l respectively;L is the total number of spare parts of mechanical general parts;Based on the task success probability and the support success probability, determine the probability corresponding to the spare parts consumption of 0, 1, …, l respectively;Based on the probability corresponding to the spare parts consumption of 0, 1, …, l respectively, determine the average consumption of spare parts of mechanical general parts, so as to realize the accurate evaluation of the average consumption of spare parts of mechanical general parts during the task.

Description

Technical Field

[0001] This invention belongs to the field of spare parts management technology for general mechanical parts, and more specifically, relates to a method and apparatus for calculating the average consumption of spare parts for general mechanical parts. Background Technology

[0002] Common mechanical parts refer to identical mechanical components that are installed on multiple pieces of equipment. Accurately estimating the spare parts consumption of common mechanical parts can help in developing a reasonable spare parts procurement plan, and by combining this with spare parts price information, it is possible to estimate the actual economic cost of spare parts availability.

[0003] If the consumption of spare parts for common mechanical components cannot be accurately estimated, accurate procurement quantities cannot be provided when ordering spare parts. Over-purchasing spare parts leads to idle parts tying up working capital and storage space; under-purchasing results in equipment downtime and serious consequences. Therefore, accurately estimating the average spare parts consumption of common mechanical components during a task has become a pressing technical challenge in the field of spare parts management. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of this invention is to provide a method and apparatus for calculating the average consumption of spare parts for general mechanical components, aiming to solve the problem of how to accurately estimate the average consumption of spare parts for general mechanical components during a task.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for calculating the average consumption of spare parts for general-purpose mechanical components, comprising:

[0006] Step 1: Determine the life probability density function based on the normal distribution of the life of each mechanical unit of the general mechanical parts, and determine the maintenance time probability density function based on the normal distribution of the maintenance time of each mechanical unit.

[0007] Step 2: Based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit, determine the task success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l; l is the total number of spare parts for the general mechanical parts.

[0008] Step 3: Based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit, determine the success probability of maintenance for each mechanical unit when the spare parts consumption is 0, 1, ..., l.

[0009] Step 4: Based on the task success probability and support success probability of each mechanical unit with spare parts consumption of 0, 1, ..., l, determine the probabilities corresponding to spare parts consumption of 0, 1, ..., l.

[0010] Step 5: Based on the probabilities corresponding to the spare parts consumption amounts of 0, 1, ..., l, determine the average spare parts consumption amount of the general mechanical parts.

[0011] In an optional example, step 4 specifically includes:

[0012] The success probability of the task and the success probability of the support for each mechanical unit are summed when the spare parts consumption is 0, 1, ..., l, respectively, to obtain the support probability for each mechanical unit when the spare parts consumption is 0, 1, ..., l, and a support probability sequence for each mechanical unit is formed.

[0013] The guarantee probability sequence corresponding to each mechanical unit is discretely convolved with respect to the spare parts consumption to obtain a convolution sequence, and the probabilities corresponding to the spare parts consumption of 0, 1, ..., l are obtained based on the convolution sequence.

[0014] In an optional example, step 2 specifically includes:

[0015] When the spare parts consumption ε is 0, the task success probability pm of each mechanical unit is determined based on the lifetime probability density function and the task time of each mechanical unit. i,ε :

[0016]

[0017] Given that the spare parts consumption ε is 1, 2, ..., l, the task success probability pm of each mechanical unit is determined based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. i,ε :

[0018]

[0019] Where i represents the number of the mechanical unit, i = 1, 2, ..., m, and m represents the number of mechanical units, T i Let represent the task time of the i-th mechanical unit, a represent the mean lifespan, b represent the root variance of lifespan, c represent the mean maintenance time, and d represent the root variance of maintenance time.

[0020] In an optional example, step 3 specifically includes:

[0021] When the spare parts consumption ε is 0, the success rate of maintenance for each mechanical unit is pg. i,ε =0;

[0022] Given that the spare parts consumption ε is 1, 2, ..., l, the success probability pg of each mechanical unit is determined based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. i,ε :

[0023]

[0024] Secondly, the present invention provides a device for calculating the average consumption of spare parts for general mechanical components, comprising:

[0025] The probability density function determination module is used to determine the life probability density function based on the normal distribution of the life of each mechanical unit of the general mechanical parts, and to determine the maintenance time probability density function based on the normal distribution of the maintenance time of each mechanical unit.

[0026] The task success probability determination module is used to determine the task success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l, based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit; l is the total number of spare parts for the general mechanical parts.

[0027] The success probability determination module is used to determine the success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l, based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit.

[0028] The consumption probability determination module is used to determine the probability corresponding to spare parts consumption of 0, 1, ..., l based on the task success probability and support success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l.

[0029] The spare parts average consumption determination module is used to determine the average spare parts consumption of the general mechanical parts based on the probabilities corresponding to the spare parts consumption of 0, 1, ..., l.

[0030] In an optional example, the consumption probability determination module is specifically used to accumulate the task success probability and the corresponding support success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l, to obtain the support probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l, and to form a support probability sequence for each mechanical unit; and to perform discrete convolution on the support probability sequence for each mechanical unit with respect to the spare parts consumption to obtain a convolution sequence, and to obtain the probability corresponding to the spare parts consumption of 0, 1, ..., l based on the convolution sequence.

[0031] In an optional example, the task success probability determination module is specifically used to determine the task success probability pm of each mechanical unit based on the lifetime probability density function and the task time of each mechanical unit when the spare parts consumption ε is 0. i,ε :

[0032]

[0033] And, when the spare parts consumption ε is 1, 2, ..., l, respectively, it is used to determine the task success probability pm corresponding to each mechanical unit based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. i,ε :

[0034]

[0035] Where i represents the number of the mechanical unit, i = 1, 2, ..., m, and m represents the number of mechanical units, T i Let represent the task time of the i-th mechanical unit, a represent the mean lifespan, b represent the root variance of lifespan, c represent the mean maintenance time, and d represent the root variance of maintenance time.

[0036] In an optional example, the guarantee success probability determination module is specifically used to determine the guarantee success probability pg of each mechanical unit when the spare parts consumption ε is 0. i,ε =0;

[0037] And, when the spare parts consumption ε is 1, 2, ..., l, respectively, it is used to determine the success probability pg of each mechanical unit based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. i,ε :

[0038]

[0039] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0040] This invention provides a method and apparatus for calculating the average consumption of spare parts for general-purpose mechanical components. By determining the probability density functions of the mechanical unit's lifespan and maintenance time based on the normal distributions they follow, the method combines the task time of each mechanical unit to determine the task success probability and maintenance success probability for each mechanical unit under various possible spare parts consumption levels. Based on this, the method determines the probability corresponding to each possible spare parts consumption level and then calculates the average spare parts consumption of the general-purpose mechanical components. This achieves an accurate assessment of the average spare parts consumption of general-purpose mechanical components during a task, which is beneficial for developing reasonable spare parts procurement plans and avoiding unnecessary time and resource waste. Attached Figure Description

[0041] Figure 1 This is a flowchart illustrating the method for calculating the average consumption of spare parts for general mechanical components provided by the present invention.

[0042] Figure 2 This is a simulation verification result diagram of the method for calculating the average consumption of spare parts for general mechanical parts provided by the present invention;

[0043] Figure 3 This is a module structure diagram of the device for calculating the average consumption of spare parts for general mechanical components provided by the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0045] This invention uses the planned working time of a general-purpose mechanical component over a period of time as the task time. During the task period, if the component malfunctions, and the fault is promptly resolved through spare parts repair, restoring the component to operation until the task ends, the spare parts are considered to have successfully ensured the task's success. However, the time spent on repair and troubleshooting consumes the originally planned task time, and in many application scenarios, repair time is significant. Therefore, repair time should not be ignored when calculating the average spare parts consumption, otherwise, it will lead to substantial calculation errors. To address this, this invention provides a method for calculating the average spare parts consumption of general-purpose mechanical components, taking repair time into account.

[0046] The lifespan of mechanical parts generally follows a normal distribution, such as busbars, gearboxes, and reducers. If a random variable follows a normal distribution N(μ,σ), where μ is the mean and σ is the root variance, its probability density function is:

[0047] In this invention, a certain general-purpose mechanical component has its mechanical units installed on m devices, with one mechanical unit installed on each device. The total number of mechanical units installed is m, and the task time for each is T. i Let i = 1, 2, ..., m. The lifespan of the mechanical unit follows a normal distribution N(a, b), where a is the mean lifespan and b is the root variance of the lifespan. The total number of spare parts is l. If the mechanical unit fails, it needs to be replaced for repair. The repair time follows a normal distribution N(c, d), where c is the mean repair time and d is the root variance of the repair time.

[0048] Figure 1 This is a flowchart illustrating the method for calculating the average consumption of spare parts for general-purpose mechanical components provided by this invention. Figure 1 As shown, the method includes:

[0049] Step 1: Determine the life probability density function based on the normal distribution of the life of each mechanical unit of the general mechanical parts, and determine the maintenance time probability density function based on the normal distribution of the maintenance time of each mechanical unit.

[0050] Step 2: Based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit, determine the task success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l; l is the total number of spare parts for general mechanical parts.

[0051] Step 3: Based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit, determine the success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l.

[0052] Step 4: Based on the task success probability and support success probability of each mechanical unit with spare parts consumption of 0, 1, ..., l, determine the probabilities corresponding to spare parts consumption of 0, 1, ..., l.

[0053] Step 5: Determine the average spare parts consumption of general mechanical parts based on the probabilities corresponding to spare parts consumption of 0, 1, ..., l.

[0054] It is understandable that general-purpose mechanical parts include identical mechanical units installed on multiple devices. Since these mechanical units are of the same type, their lifespans and maintenance times follow the same normal distribution. If the lifespan of a mechanical unit follows a normal distribution N(a,b), then the probability density function of its lifespan is: If the maintenance time of a mechanical unit follows a normal distribution N(c,d), then the probability density function of the maintenance time of the mechanical unit is: However, due to the different equipment they are installed on, the workload of each mechanical unit will vary depending on the equipment on which they are installed. Therefore, the task time of each mechanical unit is generally not the same during the same period of protection.

[0055] The total number of spare parts for general mechanical components is l. The spare parts consumption of general mechanical components should be less than or equal to l, that is, the spare parts consumption can be 0, 1, ..., l. By evaluating the success probability of the task and the success probability of the guarantee for each mechanical unit under the conditions of spare parts consumption of 0, 1, ..., l, we can iterate and evaluate the probability corresponding to each possible spare parts consumption. Thus, we can evaluate the average spare parts consumption of general mechanical components based on the total number of spare parts of l.

[0056] In addition, the spare parts consumption here is actually each possibility of spare parts consumption based on the total number of spare parts, while the final calculated average spare parts consumption of general mechanical parts is an estimated result, which can be the average number of spare parts consumed by this type of general mechanical parts during the mission.

[0057] The method provided in this invention determines the probability density function of the mechanical unit's lifespan and the probability density function of its maintenance time based on the normal distributions that the lifespan and maintenance time of the mechanical unit follow, respectively. Combined with the task time of each mechanical unit, the success probability and guarantee probability of each mechanical unit under various possible spare parts consumption levels are determined. Based on this, the probability corresponding to each possible spare parts consumption level is determined, and the average spare parts consumption of general-purpose mechanical parts is calculated. This achieves an accurate assessment of the average spare parts consumption of general-purpose mechanical parts during a task, which is beneficial for formulating reasonable spare parts procurement plans and avoiding unnecessary time and resource consumption.

[0058] In one embodiment, to accurately calculate the probabilities corresponding to spare parts consumption amounts of 0, 1, ..., l, step 4 specifically includes:

[0059] The success probability of the task and the success probability of the support for each mechanical unit are summed when the spare parts consumption is 0, 1, ..., l, respectively, to obtain the support probability for each mechanical unit when the spare parts consumption is 0, 1, ..., l, and a support probability sequence for each mechanical unit is formed.

[0060] The guarantee probability sequence corresponding to each mechanical unit is discretely convolved with respect to the spare parts consumption to obtain the convolution sequence, and the probabilities corresponding to spare parts consumption of 0, 1, ..., l are obtained based on the convolution sequence.

[0061] It is understandable that the guarantee probability sequences corresponding to each mechanical unit have the same variable, namely the spare parts consumption amount ε, and discrete convolution can be performed on the spare parts consumption amount ε. The length of each guarantee probability sequence is l+1, and the length of the convolution sequence pr obtained by discrete convolution is ml+1. The probabilities corresponding to the spare parts consumption amounts ε of the 1st, 2nd, ..., l+1st elements in the convolution sequence are taken as 0, 1, ..., l, respectively.

[0062] Furthermore, after obtaining the probabilities corresponding to the spare parts consumption ε of 0, 1, ..., l, the average spare parts consumption v of general mechanical parts can be calculated:

[0063]

[0064] Among them, pr ε This represents the (ε+1)th element in the convolution sequence pr.

[0065] In one embodiment, to accurately calculate the task success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l, step 2 specifically includes:

[0066] With spare parts consumption ε equal to 0, the success probability pm of each mechanical unit is determined based on the lifetime probability density function and the task time of each mechanical unit. i,ε :

[0067]

[0068] Given spare parts consumption ε as 1, 2, ..., l, the success probability pm of each mechanical unit is determined based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. i,ε :

[0069]

[0070] Where i represents the number of the mechanical unit, i = 1, 2, ..., m, and m represents the number of mechanical units, T i Let represent the task time of the i-th mechanical unit, a represent the mean lifespan, b represent the root variance of lifespan, c represent the mean maintenance time, and d represent the root variance of maintenance time.

[0071] It is understandable that when the spare parts consumption ε is 0, it means that no spare parts maintenance is involved during the task. Therefore, the calculation of the task success probability for each mechanical unit does not require maintenance time. The task success probability here can characterize the task completion capability of the mechanical unit.

[0072] In one embodiment, to accurately calculate the success rate of each mechanical unit when the spare parts consumption is 0, 1, ..., l, step 3 specifically includes:

[0073] When the spare parts consumption ε is 0, the success rate pg of each mechanical unit is as follows: i,ε =0;

[0074] Given spare parts consumption ε as 1, 2, ..., l, the success probability pg of each mechanical unit is determined based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. i,ε :

[0075]

[0076] As above, i represents the number of the mechanical unit, i = 1, 2, ..., m, where m represents the number of mechanical units, T i Let represent the task time of the i-th mechanical unit, a represent the mean lifespan, b represent the root variance of lifespan, c represent the mean maintenance time, and d represent the root variance of maintenance time.

[0077] Here, the mean lifespan is the mean of the normal distribution that lifespan follows, the root variance of lifespan is the root variance of the normal distribution that lifespan follows, the mean maintenance time is the mean of the normal distribution that maintenance time follows, and the root variance of maintenance time is the root variance of the normal distribution that maintenance time follows.

[0078] It is understandable that when the spare parts consumption ε is 0, it means that no spare parts maintenance is involved during the mission, and the success rate of each mechanical unit is 0. The success rate here can characterize the spare parts support capability of the mechanical unit.

[0079] In one embodiment, the present invention provides a method for calculating the average consumption of spare parts for general mechanical components, taking into account maintenance time factors. The specific process is as follows:

[0080] S1. Parameter initialization: Let the mechanical unit number i = 1, the number of mechanical units m, the spare parts consumption ε for traversal ε = 0, the total number of spare parts equipped with the mechanical general parts l, and obtain the mean life parameter a, the root variance of life parameter b, the mean maintenance time c, and the root variance of maintenance time d.

[0081] S2. Calculate the task success probability pm for each mechanical unit under different spare parts consumption levels ε. i,ε .

[0082]

[0083] S3. Calculate the success rate pg of each mechanical unit under different spare parts consumption ε. i,ε .

[0084]

[0085] S4. Update ε = ε + 1. If ε ≤ l, return to S2; otherwise, jump to S5.

[0086] S5, Composition of the task success probability sequence pm i and the success probability sequence pg i Calculate the guaranteed probability sequence ps i =pm i +pg i If i = 1, then let pr = ps i Otherwise, let pr = pr * ps i .

[0087] S6. Update i = i + 1. If i ≤ m, set spare parts consumption ε = 0 and return to S2. Otherwise, jump to S7.

[0088] S7. Based on the obtained pr convolution sequence, calculate and output the average number of spare parts consumed, v.

[0089]

[0090] As an example, it is known that the lifespan of a certain mechanical part follows a normal distribution N(100,30), and it is installed on 3 machines. The working time of each mechanical part is 140, 180, and 220 hours, respectively. A total of 5 spare parts are provided, and the maintenance time follows a normal distribution N(10,3). Calculate the average number of spare parts consumed.

[0091] First, we can perform initialization by setting the mechanical unit number i = 1 and the spare parts consumption ε = 0.

[0092] Subsequently, steps S2-S6 are executed multiple times to finally obtain the task success probability sequence pm for each mechanical unit. i , guarantee success probability sequence pg i and the guaranteed probability sequence ps i Thus, a two-dimensional array of task success probability pm, guaranteed success probability array pg, and guaranteed success probability array ps can be formed, as shown in Table 1. The convolutional sequence pr is shown in Table 2.

[0093] Table 1

[0094]

[0095] Table 2 Convolutional Sequences pr

[0096]

[0097] Finally, calculate the average number of spare parts consumed.

[0098] Furthermore, a simulation model for spare parts support of general-purpose mechanical parts is established to verify the method provided by this invention through simulation. For such general-purpose mechanical parts composed of identical mechanical components installed on multiple devices, with spare parts number l ranging from 1 to 13, Figure 2 This is a comparison chart of the average spare parts consumption results obtained using the method provided by this invention and the simulation method. Figure 2 It can be seen that the calculation results of the method provided by the present invention are in excellent agreement with the simulation results.

[0099] In one embodiment, the present invention provides a device for calculating the average consumption of spare parts for general-purpose mechanical components. Figure 3 This is a module structure diagram of the device for calculating the average consumption of spare parts for general mechanical components provided by the present invention, as shown in the figure. Figure 3 As shown, the device includes:

[0100] The probability density function determination module 310 is used to determine the life probability density function based on the normal distribution of the life of each mechanical unit of the general mechanical parts, and to determine the maintenance time probability density function based on the normal distribution of the maintenance time of each mechanical unit.

[0101] The task success probability determination module 320 is used to determine the task success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l, based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit; l is the total number of spare parts for general mechanical parts.

[0102] The success probability determination module 330 is used to determine the success probability of each mechanical unit when the spare parts consumption is 0, 1, ..., l, based on the life probability density function, the maintenance time probability density function and the task time of each mechanical unit.

[0103] The consumption probability determination module 340 is used to determine the probability corresponding to the consumption of spare parts when the consumption of spare parts is 0, 1, ..., l, based on the success probability of the task and the success probability of the support corresponding to each mechanical unit when the consumption of spare parts is 0, 1, ..., l.

[0104] The spare parts average consumption determination module 350 is used to determine the average consumption of spare parts for general mechanical parts based on the probabilities corresponding to spare parts consumption of 0, 1, ..., l.

[0105] The apparatus provided in this invention determines the probability density function of the mechanical unit's lifespan and the probability density function of its maintenance time based on the normal distributions that the lifespan and maintenance time of the mechanical unit follow, respectively. Combined with the task time of each mechanical unit, it determines the probability of task success and the probability of maintenance success for each mechanical unit under various possible spare parts consumption levels. Based on this, it determines the probability corresponding to each possible spare parts consumption level, and then calculates the average spare parts consumption of general-purpose mechanical parts. This achieves an accurate assessment of the average spare parts consumption of general-purpose mechanical parts during a task, which is beneficial for formulating a reasonable spare parts procurement plan and avoiding unnecessary time and resource consumption.

[0106] It should be understood that the above-described device is used to execute the methods in the above embodiments. The implementation principle and technical effect of the corresponding program modules in the device are similar to those described in the above methods. The working process of the device can be referred to the corresponding process in the above methods, and will not be repeated here.

[0107] Based on the methods described in the above embodiments, this application provides an electronic device. The device may include at least one memory for storing a program and at least one processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor performs the methods described in the above embodiments.

[0108] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0109] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

Claims

1. A method for calculating the average consumption of spare parts for general-purpose mechanical components, characterized in that, include: Step 1: Determine the life probability density function based on the normal distribution of the life of each mechanical unit of the general mechanical parts, and determine the maintenance time probability density function based on the normal distribution of the maintenance time of each mechanical unit. Step 2: Based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit, determine the spare parts consumption as follows: The probability of task success for each mechanical unit under the given conditions; This refers to the total number of spare parts for the aforementioned general-purpose mechanical parts; Step 3: Based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit, determine the spare parts consumption as follows: The probability of successful protection for each mechanical unit under the given circumstances; Step 4: Based on the spare parts consumption, respectively Given the task success probability and guarantee success probability of each mechanical unit, the spare parts consumption is determined as follows: The corresponding probability; Step 5: Based on the aforementioned spare parts consumption amounts, Based on the corresponding probability, determine the average spare parts consumption of the general mechanical parts; Step 4 specifically includes: The spare parts consumption will be respectively In this case, the success probability of the task corresponding to each mechanical unit and the success probability of the corresponding support are added together to obtain the result when the spare parts consumption is respectively Under the given circumstances, the guarantee probability corresponding to each mechanical unit is determined, and a guarantee probability sequence corresponding to each mechanical unit is formed. The guarantee probability sequence corresponding to each mechanical unit is discretely convolved with respect to the spare parts consumption amount to obtain a convolution sequence, and the spare parts consumption amount is obtained based on the convolution sequence. The corresponding probability; Step 2 specifically includes: The amount of spare parts consumed When the value is 0, the success probability of the task for each mechanical unit is determined based on the lifetime probability density function and the task time of each mechanical unit. : The amount of spare parts consumed They are respectively In this case, based on the lifetime probability density function, the maintenance time probability density function, and the task time of each mechanical unit, the task success probability of each mechanical unit is determined. : in, Indicates the number of the mechanical unit. , Indicates the number of mechanical units. Indicates the first Task time of each mechanical unit This represents the average lifespan. Represents the root variance of lifetime. This represents the average repair time. This represents the root variance of repair time; Step 3 specifically includes: The amount of spare parts consumed When the value is 0, the success rate of the guarantee for each mechanical unit =0; The amount of spare parts consumed They are respectively In this case, based on the lifetime probability density function, the maintenance time probability density function, and the task time of each mechanical unit, the success probability of maintenance for each mechanical unit is determined. : 。 2. A device for calculating the average consumption of spare parts for general-purpose mechanical components, characterized in that, include: The probability density function determination module is used to determine the life probability density function based on the normal distribution of the life of each mechanical unit of the general mechanical parts, and to determine the maintenance time probability density function based on the normal distribution of the maintenance time of each mechanical unit. The task success probability determination module is used to determine the spare parts consumption based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. The probability of task success for each mechanical unit under the given conditions; This refers to the total number of spare parts for the aforementioned general-purpose mechanical parts; The success probability determination module is used to determine the spare parts consumption based on the life probability density function, the maintenance time probability density function, and the task time of each mechanical unit. The probability of successful protection for each mechanical unit under the given circumstances; The consumption probability determination module is used to determine the consumption probability based on the following: Given the task success probability and guarantee success probability of each mechanical unit, the spare parts consumption is determined as follows: The corresponding probability; The spare parts average consumption determination module is used to determine the average consumption of spare parts based on the respective consumption amounts of the spare parts. Based on the corresponding probability, determine the average spare parts consumption of the general mechanical parts; The consumption probability determination module is specifically used to determine the spare parts consumption as follows: In this case, the success probability of the task corresponding to each mechanical unit and the success probability of the corresponding support are added together to obtain the result when the spare parts consumption is respectively In the case of each mechanical unit, the guarantee probability corresponding to each mechanical unit is calculated, and a guarantee probability sequence corresponding to each mechanical unit is formed; and, the guarantee probability sequence corresponding to each mechanical unit is discretely convolved with respect to the spare parts consumption to obtain a convolution sequence, and the spare parts consumption is obtained based on the convolution sequence. The corresponding probability; The task success probability determination module is specifically used to determine the spare parts consumption. When the value is 0, the success probability of the task for each mechanical unit is determined based on the lifetime probability density function and the task time of each mechanical unit. : And, for use in the spare parts consumption They are respectively In this case, based on the lifetime probability density function, the maintenance time probability density function, and the task time of each mechanical unit, the task success probability of each mechanical unit is determined. : in, Indicates the number of the mechanical unit. , Indicates the number of mechanical units. Indicates the first Task time of each mechanical unit This represents the average lifespan. Represents the root variance of lifetime. This represents the average repair time. This represents the root variance of repair time; The success probability determination module is specifically used to determine the spare parts consumption. When the value is 0, the success rate of the guarantee for each mechanical unit =0; And, for use in the spare parts consumption They are respectively In this case, based on the lifetime probability density function, the maintenance time probability density function, and the task time of each mechanical unit, the success probability of maintenance for each mechanical unit is determined. : 。

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