CN114529019A - Spare part guarantee probability determination method and device based on task success rate - Google Patents
Spare part guarantee probability determination method and device based on task success rate Download PDFInfo
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Abstract
The invention relates to a method and a device for determining spare part guarantee probability based on task success rate, wherein the method comprises the following steps: determining the whole machine backup number of the repairable units according to the task success model; calculating the equipment availability under the condition of the complete machine backup according to the complete machine backup quantity; determining the availability distribution value of each part according to the equipment composition and the equipment availability; and calculating the guarantee probability of each part to determine the spare number of each part. Firstly, establishing an equipment availability model based on the whole machine backup, thereby defining the relationship between the system task success rate and the equipment availability; and then, distributing the equipment availability layer by layer, and finally determining the requirement of the spare part guarantee index of the part to which the equipment belongs.
Description
Technical Field
The invention belongs to the field of ship maintenance and prediction, and particularly relates to a spare part guarantee probability determination method and device based on task success rate.
Background
The research on the usability problem has been the foundation of the fields of reliability mathematics, reliability engineering and comprehensive equipment guarantee for a long time. Repairable systems can be broadly classified into Markov processes and non-Markov processes according to the types of life and repair time distribution after failure of the components that make up the system. The former is mainly researched by applying Markov process theory; the latter are typically studied using tools such as the update process, the markov update process, and the complementary variable method. Based on the assumption of 'complete repair', the reliability analysis of many repairable systems such as single-component repairable systems, series systems, parallel systems, voting systems, cold reserve systems and the like has been well studied.
In some techniques, the availability of a single component system that has been repaired k-1 times (replaced after the k-th failure) is studied to give a calculation of the availability of the system. And on the premise that the service life distribution and the repair time distribution are known (complete repair or replacement is carried out after the k +1 failure), a new method different from the conventional method for solving the instantaneous availability by using a Markov process or an updating process is provided by using a round-robin integral correlation theory. The transient availability of the equipment under certain maintenance strategies is provided by researching the transient availability.
However, on the premise of a given task success rate, the complete machine backup requirements of each unit (i.e., equipment) are determined, but from the perspective of ship maintenance and guarantee, ship maintenance mainly uses spare parts to replace and maintain faulty equipment, so specific spare part requirements need to be determined. There is no relevant technical solution to this problem.
Disclosure of Invention
In order to solve the problem of determining the complete machine backup requirement of each unit on the premise of a given ship (ship) task success rate, the invention provides a method for determining the spare part guarantee probability based on the task success rate in a first aspect, which comprises the following steps: determining the whole machine backup number of the repairable units according to the task success model; calculating the equipment availability under the condition of the complete machine backup according to the complete machine backup quantity; determining the availability distribution value of each part according to the equipment composition and the equipment availability; and calculating the guarantee probability of each part to determine the spare number of each part.
In some embodiments of the present invention, the calculating the availability of the device under the condition of the complete machine backup according to the number of the complete machine backups includes the following steps: determining a maintenance resource constraint; and determining the availability of the equipment according to the maintenance resource constraint and the whole machine backup quantity.
Further, the method for calculating the availability of the equipment comprises the following steps:
Aini(t)＝Ai∞(t)*Pini(t)；
wherein A isiniThe number of the backup of the whole machine is niInstantaneous availability of device i at time t, Ai∞(t) denotes the inherent availability of device i at time t, Pini(t) indicates the number of backups is niThe probability of guarantee of device i at time t represents the convolution.
In some embodiments of the present invention, the determining the availability allocation value of each component according to the equipment composition and the equipment availability comprises the following steps:
determining the availability distribution value of each subsystem according to the connection relation and the task time of each device: recording the task time as T0When the equipment is formed by connecting m component subsystems in series, the availability assigned value of each component subsystem is Aj *＝[As(T0)]1/mWherein A iss(.) indicates the equipment availability, m is the number of the parts of the equipment; when the equipment is formed by connecting m component subsystems in parallel, the availability distribution value of each component subsystem is Aj *＝1-[1-As(T0)]1/m。
Further, the calculating the guarantee probability of each component to determine the spare part number of each component includes the following steps: determining a reliability function of each part subsystem according to the service life distribution of the parts; and calculating the guarantee probability distribution value of each component according to the reliability function and the total number of the components of each component subsystem.
Further, the step of calculating the guaranteed probability of each component according to the reliability and the total number of the components comprises the following steps: if the total number of the components is 1, the method for calculating the guarantee probability of the components comprises the following steps:
wherein, PN *Assigning a value, R (T), to the guaranteed probability of the component0) For a task time T0Component reliability;
if the total number of the parts is greater than 1, the method for calculating the guarantee probability of each part comprises the following steps:
wherein, PN *Assigning values, R, to the guaranteed probabilities of the respective componentss(T0) For a task time T0The reliability function of the component subsystem.
The invention also discloses a spare part guarantee probability determination device based on the task success rate, which comprises a first determination module, a first calculation module, a second determination module and a second calculation module, wherein the first determination module is used for determining the whole backup number of repairable units according to the task success rate model; the first calculating module is used for calculating the equipment availability under the condition of the complete machine backup according to the complete machine backup quantity; the second determining module is used for determining the availability distribution value of each part according to the equipment composition and the equipment availability; and the second calculating module is used for calculating the guarantee probability of each component so as to determine the spare number of each component.
Further, the second calculation module comprises a component reliability determination module and a guarantee probability calculation module, wherein the reliability determination module is used for determining the reliability of each component according to the service life distribution of the components; and the guarantee probability calculation module is used for calculating guarantee probability distribution values of all the components according to the reliability functions of all the component subsystems and the total number of the components.
In a third aspect of the present invention, there is provided an electronic device comprising: one or more processors; the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining the spare part guarantee probability based on the task success rate provided by the first aspect of the invention.
In a fourth aspect of the present invention, a computer-readable medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method for determining a spare part guarantee probability based on a task success rate according to the first aspect of the present invention.
The invention has the beneficial effects that:
firstly, establishing an equipment availability model based on the whole machine classification, thereby defining the relationship between the system task success rate and the equipment availability; and then, distributing the equipment availability layer by layer, and finally determining the requirement of the spare part guarantee index of the part to which the equipment belongs.
Drawings
FIG. 1 is a basic flow diagram of a method for spare part assurance probability determination based on task success rate in some embodiments of the invention;
FIG. 2 is a schematic diagram of a spare part assurance probability determination device based on task success rate according to some embodiments of the present invention;
fig. 3 is a schematic structural diagram of an electronic device in some embodiments of the invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth to illustrate, but are not to be construed to limit the scope of the invention.
Referring to fig. 1, a first aspect of the present invention provides a method for determining a spare part guarantee probability based on a task success rate, including the following steps: s101, determining the whole machine backup number of repairable units according to a task success model; s102, calculating equipment availability under the condition of the whole machine backup according to the whole machine backup quantity; s103, determining availability distribution values of all parts according to equipment composition and equipment availability; and S104, calculating the guarantee probability of each component to determine the spare number of each component.
It is understood that the task success probability is a probability measure of task success, and refers to the probability of completing task success in a specified task profile (task composition or division) within the specified task profile, and is the ratio of the total number of successful task completions to the total number of task executions, usually expressed as a percentage. The simulation method can simplify the calculation of the task completion probability, namely the task success rate P is the probability that the product can complete the specified task according to the total number of successful completion of the task/the total number of simulation.
In step S102 of some embodiments of the present invention, the calculating the availability of the device under the condition of the backup of the whole machine according to the backup number of the whole machine includes: determining a maintenance resource constraint; and determining the availability of the equipment according to the maintenance resource constraint and the whole machine backup quantity.
Specifically, when there are no repair resource constraints, the instantaneous availability of device i is:
when the backup number of the whole equipment is niThe instantaneous availability of the device is:
wherein R iss(t) is the reliability of the device. Comparing the above two equations yields:
It follows that the instantaneous availability of a device is lower than its intrinsic availability and also lower than its spare part guarantee probability, i.e. the probability of a spare part guarantee
This formula shows that the instantaneous availability of the equipment is influenced not only by its inherent reliability, maintainability, but also by its configured spare part securing capability. In particular, when Ai∞(t) at greater, the instantaneous availability of the device can be approximated as:
the formula 1 can calculate the equipment availability under the condition of complete machine backup, and for the sake of simplicity, when A is usedi∞And (t) when the total number of the backup copies is larger, calculating the equipment availability by using the formula 4, so as to convert the total number of the backup copies into the equipment availability requirement.
Further, the method for calculating the availability of the equipment comprises the following steps:
wherein the content of the first and second substances,
the number of the whole machine backups is niInstantaneous availability of device i at time t, Ai∞(t) represents the inherent availability of device i at time t,
indicating that the number of backups is niThe probability of guarantee of device i at time t represents the convolution.
It will be appreciated that for convenience it is assumed that the task unit has only two categories, working and fault conditions, since the unit standby condition is actually the condition in which the unit is in good storage. Let the task unit Ai alternately switch between an active state and a fault state, and have a working life in the k-th use period of
The maintenance time in the fault state is
Suppose that
Are independently and identically distributed, and have a distribution function of Fi(t)；
Also independently and identically distributed, the distribution thereofThe function is Gi(t), then task Unit AiAvailable at time t, when k operating cycles have elapsed, the unit is in the available state at time t, which is expressed as:
when there is no maintenance resource constraint, Unit AiThe instantaneous availability of (c) is:
wherein the content of the first and second substances,
is that
Is actually a distribution function of
K is deconvoluted. If task unit AiHas a working life and maintenance time parameter of lambdaiAnd uiI.e.:
then the unit AiThe instantaneous availability of (c) is:
in particular, when t is large, Ai∞(t) approaches a constant AiII.e. the steady state availability of the cell is:
Wherein the content of the first and second substances,
in step S103 according to some embodiments of the present invention, the determining the availability allocation value of each component according to the device composition and the device availability includes the following steps: determining the availability distribution value of each subsystem according to the connection relation and the task time of each device: recording the task time as T0When the equipment is formed by connecting m component subsystems in series, the availability assigned value of each component subsystem is Aj *＝[As(T0)]1/mWherein A iss(.) represents the equipment availability, m is the component type number or the total number of component subsystems of the equipment; when the equipment is formed by connecting m component subsystems in parallel, the availability distribution value of each component subsystem is Aj *＝1-[1-As(T0)]1/m。
In particular, assuming that a device is made up of m components, the instantaneous availability of the device is actually its task reliability, i.e. R, without the provision of spare partss(t)＝f(R1(t),…，Rm(t)) (equation 5);
wherein R iss(t) represents the task reliability of the device, Rj(t) represents the reliability of the jth component (j ═ 1,2, …, m), and f (.) is a reliability structure function of the device.
When each part is equipped with spare parts, the instantaneous availability of the part is recorded as A1(t),…，Am(t), then the equipment availability As(t) is: a. thes(t)＝f(A1(t),…，Am(t)) (equation 6);
for example, when a plant consists of m components in series, its instantaneous availability is:
therefore, under the condition that the importance of each part is the same, when the task time is T0The instantaneous availability assignment for a component is:
Aj *＝[As(T0)]1/m(formula 8);
when the equipment is composed of m components in parallel, the instantaneous availability is as follows:
therefore, when the task time is T0When, the component usage degree assignment value is:
Aj *＝1-[1-As(T0)]1/m(equation 10).
Further, in step S104 of some embodiments of the present invention, the calculating the guarantee probability of each component to determine the spare part number of each component includes the following steps: determining a reliability function of each part subsystem according to the service life distribution of the parts; and calculating the guarantee probability distribution value of each component according to the reliability function and the total number of the components of each component subsystem.
Further, the step of calculating the guaranteed probability of each component according to the reliability and the total number of the components comprises the following steps:
if the total number of the components is 1, the method for calculating the guarantee probability of the components comprises the following steps:
wherein, PN *Assigning a value, R (T), to the guaranteed probability of the component0) For a task time T0Component reliability in time;
if the total number of the components is greater than 1, the method for calculating the guarantee probability of each component comprises the following steps:
wherein, PN *Assigning values, R, to the guaranteed probabilities of the respective componentss(T0) For a task time T0The reliability function of the component subsystem.
Specifically, as can be seen from equation (equation 4), for a single component with an installed number of 1, the availability of the spare part to operate at time t is quantitatively composed of two parts: the first part is the reliability of the part at the time t, namely the probability of working without carrying a spare part to the time t; the second part represents the availability of the spare part carried along, taking into account the replacement maintenance. Thus, the single part availability may be expressed as:
As(t,N)≈R(t)+(1-R(t))PN(t) (equation 11);
wherein, PN(t) guarantee probability when the part is provided with spare parts, r (t) reliability of the part, r (t) e when the part is subjected to an exponential distribution with a parameter λ-λt. Therefore, when the task time is T0When the number of installed components is 1, if the availability is assigned with A, the component number is the jth componentj *Then its guaranteed probability requirement is
It is understood that when the component is a common component, assuming that the number of parts installed is M for the jth component, the M components form a common component system by the voting relationship k/M (g), and the common component system is equipped with N spare parts. The reliability R of the generic part systems(t) is:
where R (t) is the part reliability, and R (t) e when the part life follows an exponential distribution with a parameter λ-λt。
The instantaneous availability of the universal system is As(t,N)≈Rs(t)+(1-Rs(t))PN(t), equation 14);
therefore, when the task time is T0When the number of installed parts is M, if the availability score is Aj *Then, the guarantee probability requirement is as follows:
wherein R iss(T0) For the reliability function of the generic part system, when the part life follows an exponential distribution with the parameter λ, there is
Referring to fig. 2, the second aspect of the present invention further discloses a spare part guarantee probability determination apparatus 1 based on task success rate, including a first determination module 11, a first calculation module 12, a second determination module 13, and a second calculation module 14, where the first determination module 11 is configured to determine the whole backup number of repairable units according to a task success model; the first calculating module 12 is configured to calculate the equipment availability under the condition of the whole machine backup according to the number of the whole machine backups; the second determining module 13 is configured to determine availability allocation values of the components according to the device composition and the device availability; and the second calculating module 14 is used for calculating the guarantee probability of each component so as to determine the spare number of each component.
Further, the second calculating module 14 includes a component reliability determining module, a guarantee probability calculating module, and a spare part determining module, where the reliability determining module is configured to determine the reliability of each component according to the component life distribution; the guarantee probability calculation module is used for calculating the guarantee probability of each component according to the reliability of each component and the total number of the components; and the spare part determining module is used for determining the spare part number of each part according to the guarantee probability of each part.
In a third aspect of the invention, an electronic device 500 is provided, comprising: one or more processors; the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining the spare part guarantee probability based on the task success rate provided by the first aspect of the invention.
Referring to fig. 3, an electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following devices may be connected to the I/O interface 505 in general: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; a storage device 508 including, for example, a hard disk; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may be alternatively implemented or provided. Each block shown in fig. 3 may represent one device or may represent multiple devices, as desired.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of embodiments of the present disclosure. It should be noted that the computer readable medium described in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, however, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer-readable medium carries one or more computer programs which, when executed by the electronic device, cause the electronic device to:
computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, Python, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, which is intended to cover any modifications, equivalents, improvements, etc. within the spirit and scope of the present invention.
Claims (10)
1. A method for determining spare part guarantee probability based on task success rate is characterized by comprising the following steps:
determining the whole machine backup number of the repairable units according to the task success model;
calculating the equipment availability under the condition of the complete machine backup according to the complete machine backup quantity;
determining the availability distribution value of each part according to the equipment composition and the equipment availability;
and calculating the guarantee probability of each part to determine the spare number of each part.
2. The method for determining the probability of guaranteeing the spare parts based on the task success rate as claimed in claim 1, wherein the step of calculating the availability of the equipment under the condition of the complete machine backup according to the number of the complete machine backups comprises the following steps:
determining a maintenance resource constraint;
and determining the availability of the equipment according to the maintenance resource constraint and the whole machine backup quantity.
3. The method for determining the spare part guarantee probability based on the task success rate as claimed in claim 2, wherein the method for calculating the availability of the equipment comprises the following steps:
wherein
The number of the whole machine backups is niInstantaneous availability of device i at time t, Ai∞(t) represents the inherent availability of device i at time t,
indicating that the number of backups is niThe probability of guarantee of device i at time t represents the convolution.
4. The method for determining spare part guarantee probability based on task success rate as claimed in claim 1, wherein the determining the availability distribution value of each part according to the equipment composition and the equipment availability comprises the following steps:
determining the connection relation of each device, and regarding the same component in the same device as a component subsystem;
determining the availability distribution value of each subsystem according to the connection relation and the task time of each device: recording the task time as T0When the equipment is formed by connecting m component subsystems in series, the availability assigned value of each component subsystem is Aj *＝[As(T0)]1/mWherein A iss(.) indicates the equipment availability, m is the number of the parts of the equipment; when the equipment is formed by connecting m component subsystems in parallel, the availability distribution value of each component subsystem is Aj *＝1-[1-As(T0)]1/m。
5. The method for determining spare part guarantee probability based on task success rate as claimed in claim 4, wherein the calculating of each part guarantee probability comprises the following steps:
determining a reliability function of each part subsystem according to the service life distribution of the parts;
and calculating the guarantee probability distribution value of each component according to the reliability function and the total number of the components of each component subsystem.
6. The method for determining spare part guarantee probability based on task success rate according to claim 5, wherein the step of calculating guarantee probability distribution values of each part according to the reliability function and the total number of the parts of each part subsystem comprises the following steps:
if the total number of parts1, the method for calculating the guarantee probability of the component is as follows:
wherein, PN *Assigning a value, R (T), to the guaranteed probability of the component0) For a task time T0Component reliability in time;
if the total number of the components is greater than 1, the method for calculating the guarantee probability of each component comprises the following steps:
wherein, PN *Assigning values, R, to the guaranteed probabilities of the respective componentss(T0) For a task time T0The reliability function of the component subsystem.
7. A spare part guarantee probability determination device based on task success rate is characterized by comprising a first determination module, a first calculation module, a second determination module and a second calculation module,
the first determining module is used for determining the whole machine backup number of the repairable unit according to the task success model;
the first calculating module is used for calculating the equipment availability under the condition of the complete machine backup according to the complete machine backup quantity;
the second determining module is used for determining the availability distribution value of each part according to the equipment composition and the equipment availability;
and the second calculating module is used for calculating the guarantee probability of each component so as to determine the spare number of each component.
8. The parts and spare parts determination apparatus for task success rate according to claim 7, wherein the second calculation module comprises a parts reliability determination module, a guarantee probability calculation module, and a spare parts determination module,
the reliability determining module is used for determining the reliability of each component according to the service life distribution of the components;
the guarantee probability calculation module is used for calculating the guarantee probability of each component according to the reliability of each component and the total number of the components;
and the spare part determining module is used for determining the number of spare parts of each part according to the guarantee probability of each part.
9. An electronic device, comprising: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the spare part securing probability determination method based on task success rate according to any one of claims 1 to 6.
10. A computer-readable medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the spare part securing probability determination method based on task success rate according to any one of claims 1 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116579494A (en) * | 2023-05-23 | 2023-08-11 | 中国人民解放军海军工程大学 | Spare part inventory prediction method and system based on electromechanical equipment under maintenance time consumption |
| CN116843231A (en) * | 2023-07-20 | 2023-10-03 | 中国人民解放军海军工程大学 | Mechanical equipment use availability quantification method and system considering maintenance time consumption |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116579494A (en) * | 2023-05-23 | 2023-08-11 | 中国人民解放军海军工程大学 | Spare part inventory prediction method and system based on electromechanical equipment under maintenance time consumption |
| CN116579494B (en) * | 2023-05-23 | 2024-03-19 | 中国人民解放军海军工程大学 | Spare part inventory prediction method and system based on electromechanical equipment under maintenance time consumption |
| CN116843231A (en) * | 2023-07-20 | 2023-10-03 | 中国人民解放军海军工程大学 | Mechanical equipment use availability quantification method and system considering maintenance time consumption |
| CN116843231B (en) * | 2023-07-20 | 2024-03-19 | 中国人民解放军海军工程大学 | Mechanical equipment use availability quantification method and system considering maintenance time consumption |
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