System-level ship spare part guarantee modeling and configuration optimization method

Abstract

The invention discloses a system-level ship spare part guarantee modeling and configuration optimization method, and belongs to the technical field of water surface JT equipment guarantee, and the method comprises the steps: enabling non-exponential life distribution of spare parts to be equivalent to exponential distribution of which the failure rate is a constant according to a cumulative failure equality principle for a system composed of parts of different life distribution types; establishing a unit-level spare part guarantee rate and utilization rate model of exponential distribution; establishing a system-level spare part guarantee rate and utilization rate model according to the unit-level spare part guarantee rate and utilization rate model; establishing a ship spare part configuration optimization model under various constraint conditions based on the system-level spare part guarantee rate and utilization rate model; and solving the ship spare part configuration optimization model by adopting an improved discrete crow search algorithm to obtain a system-level spare part configuration optimization scheme. According to the invention, the system-level spare parts formed by different life distribution units are configured, so that the precision guarantee of the system-level ship spare parts is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of surface JT equipment support, and more specifically, relates to a system-level ship spare parts support modeling and configuration optimization method. Background Art

[0002] As an important component and material basis of maintenance and support resources, ship spare parts play a vital role in the ship support process. How to effectively and reasonably configure ship spare parts to ensure the normal operation of ships during long-term and long-distance missions is the focus of research on ship maintenance and support. However, the current research on ship spare parts support mainly focuses on unit-level support, and the spare parts life distribution type studied is mainly exponential distribution, with a single support effect, and it is impossible to efficiently and comprehensively evaluate the entire spare parts system.

[0003] In order to achieve accurate protection of ship spare parts, it is necessary to study the system-level spare parts protection composed of different life distribution units. At the same time, in view of the low utilization rate of spare parts in most ships, a reasonable spare parts configuration optimization plan can improve the utilization rate of spare parts and reduce the maintenance cost while ensuring the ship maintenance and protection capabilities. Summary of the invention

[0004] In view of the above defects or improvement needs of the prior art, the present invention proposes a system-level ship spare parts guarantee modeling and configuration optimization method, which configures system-level spare parts composed of different life distribution units to achieve precise guarantee of system-level ship spare parts.

[0005] To achieve the above object, the present invention provides a system-level ship spare parts guarantee modeling and configuration optimization method, comprising:

[0006] For systems composed of components with different life distribution types, the non-exponential life distribution of spare parts is equivalent to an exponential distribution with a constant failure rate according to the principle of equal cumulative failures;

[0007] Establish an exponentially distributed unit-level spare parts support rate and utilization rate model;

[0008] Establish a system-level spare parts guarantee rate and utilization rate model based on the unit-level spare parts guarantee rate and utilization rate model;

[0009] Based on the system-level spare parts guarantee rate and utilization rate model, a ship spare parts configuration optimization model under multiple constraints is established;

[0010] The improved discrete crow search algorithm is used to solve the ship spare parts configuration optimization model and obtain the system-level spare parts configuration optimization solution.

[0011] In some optional embodiments, for the system composed of components of different life distribution types, the non-exponential life distribution of spare parts is equivalent to an exponential distribution with a constant failure rate according to the cumulative failure equality principle, including:

[0012] Determine the distribution type and related parameters to which the life of system components and corresponding spare parts are subject;

[0013] Given a guarantee mission time T, the equivalent failure rate is calculated using the cumulative failure equality principle according to the distribution type and related parameters of the system components and corresponding spare parts life.

[0014] In some optional implementation schemes, if the life of system components and corresponding spare parts obeys Weibull distribution, then Get the equivalent failure rate Among them, the shape parameter is β, the scale parameter is η, μ is the average life of system components and corresponding spare parts units.

[0015] In some optional implementation schemes, if the life of system components and corresponding spare parts obeys the gamma distribution, then Get the equivalent failure rate Among them, the shape parameter is α, the scale parameter is λ, μ is the average life of system components and corresponding spare parts units, and Γ(α) is the gamma function.

[0016] In some optional implementation schemes, if the life of system components and corresponding spare parts obeys a normal distribution, then Get the equivalent failure rate Among them, the location parameter is μ, the scale parameter is σ, μ is the average life of system components and corresponding spare parts units.

[0017] In some optional implementation schemes, establishing an exponentially distributed unit-level spare parts guarantee rate and utilization rate model includes:

[0018] Single Component LRU k Configure s within the guarantee task time T k The unit-level spare parts guarantee rate is Among them, λ k Single component LRU k failure rate;

[0019] Single Component LRU k The unit-level spare parts utilization rate within the mission assurance time T is

[0020] For Weibull distribution, gamma distribution and normal distribution, according to the principle of equal cumulative failure, the equivalent failure rate is converted into an exponential distribution with a constant failure rate. and Substituting the guarantee probability and spare parts utilization calculation formulas of exponentially distributed spare parts respectively, the equivalent unit-level spare parts guarantee rate and unit-level spare parts utilization rate whose life obeys Weibull distribution, gamma distribution and normal distribution are obtained.

[0021] In some optional implementation schemes, establishing a system-level spare parts guarantee rate and utilization rate model from a unit-level spare parts guarantee rate and utilization rate model includes:

[0022] Assuming LRU k The number of single-machine installations of the unit is N k (N k ≥1), where at least N ki Only when the system is working properly can it ensure trouble-free operation. When N k LRU k The units form a series structure relationship, then the equivalent Failure rate for when When N k LRU k The units form a k / N voting structure relationship, then the equivalent Failure rate for set up Configurations k When there are spare parts, the general spare parts guarantee rate model with a series structure relationship or a voting structure relationship within a given guarantee task time T is obtained as follows: The system-level spare parts guarantee rate model is established as K is the type of spare parts;

[0023] Depend on Build a system-level spare parts utilization model.

[0024] In some optional implementation schemes, the ship spare parts configuration optimization model under multiple constraint conditions is established based on the system-level spare parts guarantee rate and utilization rate model, including:

[0025] Select system-level spare parts utilization as the objective function maxY s ;

[0026] Select given space, quality, guarantee cost and system-level spare parts guarantee rate threshold as constraints Among them, v k 、m k 、c k LRUk (1≤k≤K) volume, quality and required maintenance cost of spare parts; V given 、M given , C given , P given They are respectively the given total space, quality, support cost and system-level spare parts support rate threshold constraints.

[0027] The overall system spare parts configuration optimization model is determined based on the selected objective function and constraints.

[0028] In some optional implementation schemes, the improved discrete crow search algorithm is used to solve the ship spare parts configuration optimization model to obtain a system-level spare parts configuration optimization scheme, including:

[0029] Input the basic information of the spare parts configuration optimization model, including the given space, quality, guarantee cost and system spare parts guarantee rate threshold, set the search range of feasible solutions for spare parts configuration optimization, and set adjustable parameters;

[0030] The improved crow search algorithm is used to iteratively solve the spare parts configuration optimization model under multiple constraints. The improved part is to establish a continuous space to discrete space encoding mechanism for the crow position and the spare parts feasible solution. At the same time, some parameters of the algorithm are adaptively adjusted during the iterative solution process and the search direction of the feasible solution is adjusted.

[0031] Output the best spare parts configuration optimization plan and its corresponding system-level spare parts utilization.

[0032] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0033] (1) The present invention provides a support index modeling method for ship spare parts with various life distributions.

[0034] (2) The present invention provides a variety of unit-level and system-level spare parts guarantee rates and spare parts utilization rates with equivalent life distribution, and provides a calculation method. The system-level spare parts configuration is applicable to the overall system, the first-level system, the second-level system, etc.

[0035] (3) Based on the system-level spare parts guarantee rate and spare parts utilization rate, the present invention establishes a spare parts configuration optimization model under multiple constraints such as given space, quality and guarantee cost, which can provide support for realizing precise guarantee of ship spare parts.

[0036] (4) The present invention has made some improvements to the solution algorithm used in the spare parts configuration optimization model, so that it can better solve large-scale, multi-variable, nonlinear spare parts configuration discrete optimization problems under multiple constraints. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of modeling a multi-life distribution ship spare parts guarantee index according to an embodiment of the present invention;

[0038] Figure 2 A redundant system (i.e., LRU) provided by an embodiment of the present invention k Series structure) physical structure diagram after equivalent life;

[0039] Figure 3 An LRU provided by an embodiment of the present invention k Physical structure after equivalent life of redundant structure;

[0040] Figure 4 It is a flow chart of constructing a ship spare parts configuration optimization model under multiple constraints provided by an embodiment of the present invention;

[0041] Figure 5 The present invention provides a flow chart of solving a ship spare parts configuration optimization model based on an improved crow search algorithm. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0043] like Figure 1 , Figure 2 and Figure 3 As shown in the figure, the modeling process of ship spare parts guarantee indicators with various life distributions is as follows:

[0044] Step 1: For the system composed of components with different life distribution types, the spare parts configuration calculation formula is relatively complicated. According to the cumulative failure equality principle, the non-exponential life distribution of spare parts is equivalent to an exponential distribution with a constant failure rate;

[0045] Step 2: Establish an exponentially distributed unit-level spare parts support rate and utilization rate model. The medium unit level refers to the smallest unit in the equipment decomposition structure that can be replaced and repaired after a failure or damage occurs during the actual ship's mission;

[0046] Step 3: Establish a system-level spare parts guarantee rate and utilization rate model. The system-level spare parts configuration is applicable to the overall system, primary system, secondary system, etc.

[0047] Step 4: Establish a ship spare parts configuration optimization model under multiple constraints based on indicators such as system-level spare parts guarantee rate and spare parts utilization rate;

[0048] Step 5: Use the improved discrete crow search algorithm to solve the ship spare parts configuration optimization model and obtain the system-level spare parts configuration optimization solution.

[0049] Furthermore, the specific operations of step 1 include:

[0050] Step 1.1: Determine the distribution type and related parameters that the system components and corresponding spare parts life obey;

[0051] Step 1.2: Given the guarantee task time T;

[0052] Step 1.3: According to the distribution type of the life of system components and corresponding spare parts, including exponential distribution, Weibull distribution, gamma distribution and normal distribution. For system components and corresponding spare parts whose life distribution obeys Weibull distribution, gamma distribution and normal distribution, the equivalent failure rate λ is calculated using the cumulative failure equality principle. eq , and its calculation formula is:

[0053]

[0054] Where μ is the average life of system components and corresponding spare parts units.

[0055] Furthermore, according to the principle of cumulative failure equality, the non-exponential life distribution of spare parts including Weibull distribution, gamma distribution and normal distribution are equivalent to exponential distribution with a constant failure rate. The equivalent failure rate is calculated by the equivalent failure rate calculation formula, specifically:

[0056] If the life of system components and corresponding spare parts follows Weibull distribution, its shape parameter is β, scale parameter is η, and its average life is μ w =ηΓ(1+1 / β), its probability density function is:

[0057]

[0058] The distribution function is:

[0059]

[0060] The available failure efficiency function is:

[0061]

[0062] According to the cumulative failure equalization calculation formula, the equivalent failure rate can be obtained as follows:

[0063]

[0064] If the life of system components and corresponding spare parts follows the gamma distribution, its shape parameter is α, scale parameter is λ, and its average life is μ g =α / λ, its probability density function is:

[0065]

[0066] Similarly, according to the cumulative failure equalization calculation formula, the equivalent failure rate can be obtained as follows:

[0067]

[0068] In the formula, is the gamma function.

[0069] If the life of system components and corresponding spare parts follows a normal distribution, with position parameter μ and scale parameter σ, the average life is μ n =μ, similarly, according to the cumulative failure equal calculation formula, the equivalent failure rate can be obtained as:

[0070]

[0071] Furthermore, an exponentially distributed unit-level spare parts guarantee rate and spare parts utilization rate model is established, including:

[0072] (1) Probabilistic model of unit-level spare parts utilization

[0073] Assume that the system has K types of LRU spare parts, LRU k (1≤k≤K) The number of spare parts configuration is s k , then the spare parts inventory configuration plan is s=[s1,s2,…,s K ], according to the redundant spare parts model in reliability theory, we can get LRU k The unit-level spare parts support rate within the support mission time T is:

[0074]

[0075] The unit spare parts utilization model can be composed of single component LRU k The number of failures within the mission assurance time T follows the Poisson distribution, taking the first s k The cumulative sum of the +1 items is essentially equivalent to the overall reliability of the spare parts redundancy model in reliability theory.

[0076] (2) Probabilistic model of unit-level spare parts utilization

[0077] When a single component LRU k The configuration quantity is s k When , the spare parts utilization rate within the specified support mission time T is statistically defined as:

[0078]

[0079] In the formula, x k To ensure LRU within task time T k The actual number of spare parts used.

[0080] The spare parts utilization rate definition model given from a statistical perspective requires a large amount of statistical data, which will bring difficulties to the formulation of ship spare parts configuration plans in practical applications. In engineering practice, the mathematical expectation of spare parts utilization rate is usually introduced to replace the spare parts utilization rate. k The calculation method of unit-level spare parts utilization is:

[0081]

[0082] Furthermore, according to the functional connection relationship of the smallest unit that can be replaced and repaired in the equipment decomposition structure hierarchy after a failure or damage occurs when the actual ship is performing a mission, a system-level spare parts guarantee rate and spare parts utilization rate model is established.

[0083] In the actual configuration of ship spare parts support, the ship system is composed of multiple components and subsystems, and adopts a mixed connection method. These components and subsystems have both series and parallel relationships in terms of function. At the same time, backup redundancy and fault-tolerant design strategies are adopted in some systems to improve the overall reliability and fault-tolerant capability of the system, ensuring that the system can continue to operate and maintain stability when facing a single point failure.

[0084] Assume that the system has LRU k The number of single-machine installations of the unit is N k (N k ≥1), of which at least Only when the system is operating normally can it ensure trouble-free operation of the system.

[0085] (1) For this LRU k Unit, when When N k LRU k The units form a series structure in the entire system. For series structure components, as long as one component fails during the mission working cycle, the system will shut down. According to the memorylessness of exponential distribution, the series structure components can be treated as single components using the equivalent life part method, such as Figure 2 shown.

[0086] Equivalence Failure rate for:

[0087]

[0088] (2) When When N k components form a k / N voting structure relationship in the entire system. For voting structure components, that is, redundant structure components, when the number of faulty components does not exceed The system will not shut down due to component failure. To avoid system shutdown due to replacement of faulty parts, there is no need to replace spare parts at this time. However, if the number of faulty parts exceeds When a fault occurs, replacement repair must be performed, that is, the corresponding spare parts are used to replace the faulty parts. For redundant structural parts, the equivalent life parts method can be used to treat them as single parts, such as Figure 3 shown.

[0089] Equivalence Failure rate for:

[0090]

[0091] (3) Assume that Configurations k When there are spare parts, the general spare parts guarantee rate model with a series structure relationship or a voting structure relationship within a given guarantee task time T can be obtained as follows:

[0092]

[0093] (4) Establish the system-level spare parts guarantee rate model as follows:

[0094]

[0095] (5) Establish a system-level spare parts utilization model. The system-level spare parts utilization is the ratio of the number of spare parts actually used to the total number of spare parts configured within a given guarantee time T. Its calculation formula is:

[0096]

[0097] Furthermore, if Figure 4 As shown in the figure, the construction process of the ship spare parts configuration optimization model is as follows:

[0098] By considering the actual constraints of spare parts configuration when the ship performs tasks and the needs of the ship support department, the system spare parts utilization rate is selected as the objective function, and the given space, quality, support cost and system spare parts support rate threshold are selected as constraints. The ship spare parts configuration optimization model is established as follows:

[0099] max Y s

[0100]

[0101] Furthermore, if Figure 5As shown in the figure, the solution process of the ship spare parts configuration optimization model based on the improved crow search algorithm is as follows:

[0102] The ship spare parts configuration model in the present invention requires large-scale, multi-variable, nonlinear relationships to describe, and multiple constraints must be considered to solve the optimization solution that maximizes the total spare parts utilization. The optimization process using the improved crow search algorithm is:

[0103] (1) Input the basic information of the spare parts configuration optimization model, including the given space, quality, guarantee cost, and the threshold value of the system spare parts guarantee rate. According to the initial spare parts plan, set the upper and lower bounds of the decision variables to determine the search range of feasible solutions for spare parts configuration optimization, and set the adjustable parameters of the algorithm.

[0104] (2) Initialize the position and memory of the crows in the algorithm and generate an initial feasible solution.

[0105] (3) Evaluate the fitness function value. For the system spare parts configuration optimization problem, the system spare parts utilization function is used as the fitness function.

[0106] (4) Generate new positions for the crows using the fitness distance balance strategy and roulette pair method, and check the feasibility of the new positions.

[0107] (5) Evaluate the fitness function value of the new position, update the crow’s memory, and adjust the flight step size and perception probability.

[0108] (6) Repeat (3)(4)(5) until the maximum number of iterations is reached. When the termination condition is reached, output the spare parts optimization solution corresponding to the maximum system spare parts utilization.

[0109] The improvement is to establish a continuous-to-discrete encoding mechanism for crow positions and spare parts feasible solutions, so that it is better suitable for solving the spare parts configuration optimization model proposed in this invention. At the same time, some parameters of the algorithm are adaptively adjusted during the iterative solution process, and the search direction of the feasible solution is adjusted. Figure 3 shown.

[0110] A person of ordinary skill in the art may understand that to implement all or part of the processes in the above-mentioned embodiment method, the process may be completed by a computer program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium. When the program is executed, it may include the processes of the above-mentioned method embodiments.

[0111] It should be pointed out that, according to the needs of implementation, the various steps / components described in this application can be split into more steps / components, and two or more steps / components or partial operations of steps / components can be combined into new steps / components to achieve the purpose of the present invention.

[0112] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A system-level ship spare parts support modeling and configuration optimization method, characterized in that: include: For systems composed of components with different life distribution types, the non-exponential life distribution of spare parts is equivalent to an exponential distribution with a constant failure rate according to the principle of equal cumulative failures; Establish an exponentially distributed unit-level spare parts support rate and utilization rate model; Establish a system-level spare parts guarantee rate and utilization rate model based on the unit-level spare parts guarantee rate and utilization rate model; Based on the system-level spare parts guarantee rate and utilization rate model, a ship spare parts configuration optimization model under multiple constraints is established; The improved discrete crow search algorithm is used to solve the ship spare parts configuration optimization model and obtain the system-level spare parts configuration optimization solution.

2. The method according to claim 1, characterized in that: For the system composed of components of different life distribution types, the non-exponential life distribution of spare parts is equivalent to an exponential distribution with a constant failure rate according to the cumulative failure equality principle, including: Determine the distribution type and related parameters to which the life of system components and corresponding spare parts are subject; Given a guarantee mission time T, the equivalent failure rate is calculated using the cumulative failure equality principle according to the distribution type and related parameters of the system components and corresponding spare parts life.

3. The method according to claim 2, characterized in that If the life of system components and corresponding spare parts obeys Weibull distribution, then Get the equivalent failure rate Among them, the shape parameter is β, the scale parameter is η, μ is the average life of system components and corresponding spare parts units.

4. The method according to claim 3, characterized in that If the life of system components and corresponding spare parts obeys the gamma distribution, then Get the equivalent failure rate Among them, the shape parameter is α, the scale parameter is λ, μ is the average life of system components and corresponding spare parts units, and Γ(α) is the gamma function.

5. The method according to claim 4, characterized in that If the life of system components and corresponding spare parts obeys normal distribution, then Get the equivalent failure rate Among them, the location parameter is μ, the scale parameter is σ, μ is the average life of system components and corresponding spare parts units.

6. The method according to claim 5, characterized in that The method of establishing an exponentially distributed unit-level spare parts guarantee rate and utilization rate model includes: Single Component LRU k Configure s within the guarantee task time T k The unit-level spare parts guarantee rate is Among them, λ k Single component LRU k failure rate; Single Component LRU k The unit-level spare parts utilization rate within the mission assurance time T is For Weibull distribution, gamma distribution and normal distribution, according to the principle of equal cumulative failure, the equivalent failure rate is converted into an exponential distribution with a constant failure rate. and Substituting the guarantee probability and spare parts utilization calculation formulas of exponentially distributed spare parts respectively, the equivalent unit-level spare parts guarantee rate and unit-level spare parts utilization rate whose life obeys Weibull distribution, gamma distribution and normal distribution are obtained.

7. The method according to claim 6, characterized in that The system-level spare parts guarantee rate and utilization rate model is established from the unit-level spare parts guarantee rate and utilization rate model, including: Assuming LRU k The number of single-machine installations of the unit is N k ,N k ≥1, of which at least Normal operation can ensure the system runs smoothly. ki =N k When N k LRU k The units form a series structure relationship, then the equivalent Failure rate for When 1≤N ki <N k When N k LRU k The units form a k / N voting structure relationship, then the equivalent Failure rate for set up Configurations k When there are spare parts, the general spare parts guarantee rate model with a series structure relationship or a voting structure relationship within a given guarantee task time T is obtained as follows: The system-level spare parts guarantee rate model is established as K is the type of spare parts; Build a system-level spare parts utilization model.

8. The method according to claim 7, characterized in that The ship spare parts configuration optimization model under various constraints is established based on the system-level spare parts guarantee rate and utilization rate model, including: Select system-level spare parts utilization as the objective function maxY s ; Select given space, quality, guarantee cost and system-level spare parts guarantee rate threshold as constraints Among them, v k 、m k 、c k LRU k , 1≤k≤K The volume, quality and required maintenance cost of spare parts, V given 、M given , C given , P given They are respectively the given total space, quality, support cost and system-level spare parts support rate threshold constraints. The overall system spare parts configuration optimization model is determined based on the selected objective function and constraints.

9. The method according to claim 8, characterized in that The improved discrete crow search algorithm is used to solve the ship spare parts configuration optimization model to obtain a system-level spare parts configuration optimization solution, including: Input the basic information of the spare parts configuration optimization model, including the given space, quality, guarantee cost and system spare parts guarantee rate threshold, set the search range of feasible solutions for spare parts configuration optimization, and set adjustable parameters; The improved crow search algorithm is used to iteratively solve the spare parts configuration optimization model under multiple constraints. The improved part is to establish a continuous space to discrete space encoding mechanism for the crow position and the spare parts feasible solution. At the same time, some parameters of the algorithm are adaptively adjusted during the iterative solution process and the search direction of the feasible solution is adjusted. Output the best spare parts configuration optimization plan and its corresponding system-level spare parts utilization.

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