A trade-off optimization method for spacecraft design schemes based on value analysis

Abstract

The present invention discloses a method for weighing and optimizing spacecraft design schemes based on value analysis, which belongs to the technical field of value analysis. The method comprises the following steps: establishing an evaluation index system from the functional dimension of value, and determining the weight of each index in the evaluation index system; determining the satisfaction score value of a candidate scheme for each index and the satisfaction coefficient of the candidate scheme for each index, and calculating the satisfaction value of the candidate scheme for each index; calculating the value factor of the candidate scheme for each index, and summing the value factors corresponding to all the indexes of the candidate scheme to obtain the total value of the candidate scheme; calculating the cost factor of the development of the candidate scheme; calculating the value of the candidate scheme based on the total value of the candidate scheme and the cost factor of the development; and finally selecting the candidate scheme with the highest value as the preferred one. The present invention can weigh the candidate schemes for spacecraft design from the perspective of value, propose a quantitative weighing strategy, and then select the optimal candidate scheme.

Description

Technical Field

[0001] The present invention belongs to the technical field of value analysis, and in particular relates to a method for weighing and optimizing spacecraft design schemes based on value analysis. Background Art

[0002] Currently, the trade-offs in spacecraft design often rely on subjective decision-making, making it difficult to quantify candidate designs. While quantitative evaluation methods such as the Analytic Hierarchy Process (AHP) and fuzzy evaluation methods are currently available, simply defining and classifying indicators makes it difficult to assess the maturity of existing models. Since spacecraft development is typically a small-batch product, with each model having a different mission, developing each spacecraft from scratch would inevitably lead to high costs for the entire spacecraft. This, in an increasingly competitive market, would significantly weaken the competitiveness and market share of the development company. Summary of the Invention

[0003] In view of this, in order to overcome the shortcomings of traditional subjective decision-making methods, the present invention provides a spacecraft design scheme weighing and optimization method based on value analysis, which can weigh the candidate schemes of spacecraft design from the perspective of value, propose a quantitative weighing strategy, and then select the optimal candidate scheme.

[0004] The present invention is achieved through the following technical solutions:

[0005] A method for weighing and optimizing spacecraft design options based on value analysis is proposed. The specific steps of the method are as follows:

[0006] Step 1: Establish an evaluation index system based on the functional dimension of value and determine the weight of each index in the evaluation index system. i ;

[0007] Step 2: Determine the satisfaction score p of each indicator for the kth candidate solution k,i And the satisfaction coefficient δ of the kth candidate solution for each indicator k,i , calculate the satisfaction value s of each indicator of the kth candidate solution k,i , s k,i =p k,i *δ k,i ;

[0008] Step 3: Calculate the value factor λ of the kth candidate solution for each indicator k,i ,λ k,i =s k,i *t i And sum up the value factors corresponding to all indicators of the k-th candidate solution to obtain the total value Q of the k-th candidate solution k :

[0009] Step 4: Calculate the maturity of the entire spacecraft of the kth candidate solution δ k , the cost factor for the development of the kth candidate solution

[0010] Step 5: The total value Q of the kth candidate solution obtained in step 3 k And the cost factor τ of the development of k candidate solutions obtained in step 4 k , the value of the kth candidate solution can be calculated: Similarly, the value of all candidate solutions can be obtained; finally, the candidate solution with the highest value is selected as the preferred one.

[0011] Furthermore, in step 1, the evaluation index system consists of j indicators, where

[0012] Furthermore, in step 2, p k,i ≤100, k=1,2,...,h, h means there are a total of h candidate solutions.

[0013] Furthermore, in step 2, δ k,i ≥1.

[0014] Furthermore, in step 4, the kth candidate solution is decomposed from top to bottom according to its components to identify the maturity of each part of the spacecraft; the spacecraft is composed of a platform and a payload, the platform is composed of m subsystems, each subsystem is composed of several single machines; the payload is composed of e single machines;

[0015] For the platform and payload, the corresponding reuse factors are T1 and T2, where T1+T2=1;

[0016] (1) Maturity of the computing platform

[0017] For m subsystems under the platform, the reuse factors corresponding to all subsystems are M1, M2, ..., M y ,…,M m ,

[0018] For any subsystem y, it contains n single machines, of which the number of single machines that can be reused is b y , then the maturity of subsystem y is γ y for: The maturity of the platform

[0019] (2) Calculate the maturity of the load

[0020] For the load, there are e single machines in total, of which the number of single machines that can be reused is b p , then the maturity of the load is:

[0021] Then the maturity of the entire spacecraft of the kth candidate solution is δ k =δ k1 +δ k2 , the cost factor for the development of the kth candidate solution is

[0022] Beneficial effects:

[0023] (1) In view of the problem that the traditional spacecraft design scheme weighing method is difficult to evaluate the maturity of existing spacecraft models, the present invention provides a spacecraft design scheme weighing and optimization method based on value analysis. According to the steps of establishing an index system, calculating satisfaction, calculating the total value of candidate schemes, calculating the maturity of candidate schemes, and optimizing design schemes, the reuse degree of existing spacecraft models is quantified from the perspective of value, that is, the existing platform and architecture are utilized as much as possible, and mature products and technologies are adopted to achieve the optimization of design schemes. The present invention evaluates design schemes from the perspective of value analysis, avoiding traditional subjective decision-making methods. The design scheme weighing and evaluation results are more objective and accurate, and the proposed method is highly practical, especially for the development of large and complex products such as aerospace and aviation. It has good adaptability.

[0024] (2) The satisfaction coefficient δ of the kth candidate solution for the ith indicator in step 2 of the present invention k,i ≥1, if δ k,i <1 indicates that the kth candidate solution does not meet the requirements and is directly removed, which avoids subsequent calculations of the candidate solution and improves the trade-off efficiency of the candidate solution.

[0025] (3) In step 4 of the present invention, by defining a reuse factor and taking the reuse quantity of a single machine, subsystems, and platform / payload integration as cost considerations, the maturity of the entire spacecraft of the candidate solution and the cost factor of development are calculated. This calculation method quantifies the cost of the spacecraft and improves the reliability of the final preferred candidate solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Diagram of the evaluation indicator system established for the value-based functional dimension;

[0027] Figure 2 This is a diagram of the spacecraft structure. DETAILED DESCRIPTION

[0028] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0029] Example 1:

[0030] This embodiment provides a method for weighing and optimizing spacecraft design solutions based on value analysis. The specific steps of the method are as follows:

[0031] Step 1: Establish an evaluation index system based on the functional dimension of value. The evaluation index system consists of j indicators and determines the weight t of the i-th indicator. i ,in The set of weights of all indicators is t=(t1,t2,…,t i );

[0032] Step 2: Based on the evaluation index system and the weight of each index determined in step 1, i , for h candidate solutions, determine the satisfaction of each indicator, that is, score the satisfaction of each indicator of the candidate solution, and get p k,i , p k,i represents the score of the kth candidate solution for the i-th indicator, p k,i ≤100, k=1,2,...,h; therefore, the set of scores of satisfaction of all indicators of the kth candidate solution is p k =(p k,1 , p k,2 ,…,p k,i );

[0033] Let the minimum index of user satisfaction be 1. If the minimum index is exceeded, the satisfaction coefficient δ greater than 1 is multiplied according to the actual situation. k,i , δ k,i represents the satisfaction coefficient of the kth candidate solution for the i-th indicator, δ k,i ≥1, if δ k,i <1 means that the kth candidate solution does not meet the requirements and should be removed. Therefore, the set of satisfaction coefficients of all indicators of the kth candidate solution is δ k =(δ k,1 ,δ k,2 ,...,δ k,i );

[0034] Thus, the index satisfaction value s of the kth candidate solution is obtained k,i , s k,i =p k,i *δ k,i , s k,i represents the satisfaction value of the ith indicator of the kth candidate solution, so the set of satisfaction values ​​of all indicators of the kth candidate solution is s k =(s k,1 ,s k,2 ,...,s k,i );

[0035] Step 3: Calculate the total value of the candidate solution: For each candidate solution, use the satisfaction value s of the candidate solution's indicator k,i and the weight of the indicator t i Multiply them together to get the value factor λ of each indicator k,i ,λ k,i =s k,i *t i ,λ k,i represents the value factor of the i-th indicator of the k-th candidate solution, so the set of all indicator value factors of the k-th candidate solution is λ k =(λ k,1 ,λ k,2 ,...,λ k,i );

[0036] Then sum up the value factors corresponding to all indicators of the k-th candidate solution to obtain the total value Q of the k-th candidate solution. k :

[0037] Step 4: Calculate the maturity of candidate solutions and the cost factor of development: Decompose the kth candidate solution from top to bottom according to its components, and identify the maturity of each part of the spacecraft; for a specific spacecraft, the spacecraft consists of a platform and a payload, see the attached Figure 2 The platform consists of m subsystems, which are subsystem 1, subsystem 2, ..., subsystem m. Each subsystem consists of several stand-alone machines. The stand-alone machines in subsystem 1 are stand-alone machines S 1,1 , Standalone S 1,2 ,…, Single Machine S 1,x1 , the single machines in subsystem 2 are single machine S 2,1 , Standalone S 2,2 ,…, Single Machine S 2,x2 ,…, the single machines in subsystem m are single machine S m,1 , Standalone S m,2 ,…, Single Machine S m,n Therefore, the number of units corresponding to each subsystem is {x1, x2, ..., n}; the load consists of e units, each of which is a unit S p,1 , Standalone S p,2 ,…, Single Machine S p,e Spacecraft reuse can be divided into the following four types according to their maturity: 1) star-level reuse (i.e., entire spacecraft reuse); 2) platform / payload-level reuse; 3) subsystem-level reuse; 4) equipment-level reuse (i.e., single-machine reuse);

[0038] For full-star reuse, it is just the complete reuse of existing achievements. Only targeted verification and testing of key links are required. It has the highest maturity and the lowest development cost.

[0039] In the maturity rating process, in addition to the number of single-machine reuses, which is a cost factor, the integration of subsystems and platforms / payloads is also an important cost factor. That is, several single-machine component systems and subsystems must undergo integration testing, and platforms / payloads also need to undergo sufficient integration testing. Therefore, the reuse factor is defined as follows:

[0040] For the platform and payload, the corresponding reuse factors are T1 and T2, where T1+T2=1;

[0041] (1) Maturity of the computing platform

[0042] For m subsystems under the platform, the reuse factors corresponding to all subsystems are M1, M2, ..., M y ,…,

[0043] For any subsystem y, it contains n single machines, of which the number of single machines that can be reused is b y , then the maturity of subsystem y is γ y for: Therefore, the maturity set of m subsystems is γ=(γ1,γ2,...,γ y ,...,γ m ) and the maturity of the platform

[0044] (2) Calculate the maturity of the load

[0045] For the load, there are e single machines in total, of which the number of single machines that can be reused is b p , then the maturity of the load is:

[0046] Then the maturity of the entire spacecraft of the kth candidate solution is δ k =δ k1 +δ k2 , the cost factor for the development of the kth candidate solution is

[0047] Step 5: Optimize the design solution based on value analysis: The total value Q of the kth candidate solution obtained in step 3 k And the cost factor τ of the development of k candidate solutions obtained in step 4 k , the value of the kth candidate solution can be calculated: That is, the value of the candidate solution = total value / cost factor; the set of the value of all candidate solutions is η = (η1, η2, ..., η k ), the higher the value, the better the balance between the candidate's advancement and economy; finally, the candidate with the highest value is selected as the preferred one.

[0048] Example 2:

[0049] This embodiment, based on Example 1, provides a specific embodiment of a method for weighing and optimizing spacecraft design solutions based on value analysis. In this embodiment, the platform consists of five subsystems, namely, structural mechanism, GNC, measurement and control data transmission, power supply and distribution, and thermal control. The number of units corresponding to each subsystem is {20, 30, 25, 40, 15} respectively; the payload consists of eight units.

[0050] The specific steps of this embodiment are as follows:

[0051] Step 1, see attached Figure 1 The evaluation index system includes key characteristic compliance index, ease of use index, test verification index, reliability index and processability index. The weights of the five indicators are t = (t1, t2, t3, t4, t5) = (0.2, 0.2, 0.15, 0.35, 0.1);

[0052] In step 2, there are four candidate solutions. The first candidate solution scores the satisfaction of the five indicators in step 1, and obtains p1 = (70, 80, 90, 95, 90). The second candidate solution scores the satisfaction of the five indicators in step 1, and obtains p2 = (80, 60, 95, 75, 80). The third candidate solution scores the satisfaction of the five indicators in step 1, and obtains p3 = (85, 70, 80, 70, 86). The fourth candidate solution scores the satisfaction of the five indicators in step 1, and obtains p4 = (75, 78, 90, 80, 88).

[0053] Let the satisfaction coefficient of the first candidate solution for the five indicators of step 1 be δ1 = (1.1, 1.3, 1.2, 1.5, 1.6), the satisfaction coefficient of the second candidate solution for the five indicators of step 1 be δ2 = (1.3, 1.2, 1.3, 1.4, 1.5), the satisfaction coefficient of the third candidate solution for the five indicators of step 1 be δ3 = (1.1, 1.3, 1.2, 1.5, 1.5), and the satisfaction coefficient of the fourth candidate solution for the five indicators of step 1 be δ4 = (1.3, 1.2, 1.1, 1.4, 1.3);

[0054] The satisfaction values ​​of the four candidate solutions are s1 = (77, 104, 135, 142.5, 144), s2 = (104, 72, 123.5, 105, 120), s3 = (93.5, 91, 96, 105, 129), and s4 = (97.5, 93.6, 99, 112, 114.4).

[0055] Step 3: Calculate the value factor of the first candidate solution for the five indicators in step 1 as λ1 = (15.4, 20.8, 20.25, 49.875, 14.4), the value factor of the second candidate solution for the five indicators in step 1 as λ2 = (20.8, 14.4, 18.525, 36.75, 12), the value factor of the third candidate solution for the five indicators in step 1 as λ3 = (18.7, 18.2, 14.4, 36.75, 12.9), and the value factor of the fourth candidate solution for the five indicators in step 1 as λ4 = (19.5, 18.72, 14.85, 39.2, 11.44);

[0056] Then, the value factors corresponding to all evaluation indicators of each candidate solution are summed to obtain the total value of the four candidate solutions, namely Q1 = 120.725, Q2 = 102.475, Q3 = 100.95, Q4 = 103.95;

[0057] Step 4: Set the reuse factors of the platform and payload to T1 = 0.7 and T2 = 0.3 respectively; the reuse factors of the five subsystems under the platform to M1 = 0.2, M2 = 0.1, M3 = 0.1, M4 = 0.3, and M5 = 0.3 respectively;

[0058] For the first candidate solution, the number of units that can be reused by the five subsystems is {10, 12, 20, 15, 5}, and the number of units that can be reused by the payload is 4. The maturity of the five subsystems is γ = (0.1, 0.08, 0.16, 0.075, 0.08), and the platform maturity δ1 = 0.3465, the payload maturity δ2 = 0.15, and the development cost factor τ = 2.01.

[0059] For the second candidate, the number of units that can be reused by the five subsystems is {12, 15, 15, 10, 9}, and the number of units that can be reused by the payload is 6. The maturity of the subsystem is γ = (0.12, 0.1, 0.12, 0.05, 0.12), and the maturity of the platform is δ1 = 0.357, the maturity of the payload is δ2 = 0.225, and the development cost factor is τ = 1.72.

[0060] For the third candidate, the number of units that can be reused by the five subsystems is {8, 9, 10, 15, 9}, and the number of units that can be reused by the payload is 6. The maturity of the subsystem is γ = (0.08, 0.06, 0.08, 0.075, 0.12), and the platform maturity is δ1 = 0.2905, the payload maturity is δ2 = 0.225, and the development cost factor is τ = 1.94.

[0061] For the fourth candidate, the number of units that can be reused by the five subsystems is {16, 15, 15, 20, 9}, and the number of units that can be reused by the payload is 4. The maturity of the subsystem is γ = (0.16, 0.1, 0.12, 0.1, 0.12), the platform maturity is δ1 = 0.42, the payload maturity is δ2 = 0.15, and the development cost factor is τ = 1.75.

[0062] Step 5: Calculate the value of the four candidate solutions as η = (59.93, 59.64, 52.04, 59.11). Therefore, the optimal ranking of the candidate solutions is: the first candidate solution > the second candidate solution > the fourth candidate solution > the third candidate solution, that is, the first candidate solution is the best.

[0063] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for weighing and optimizing spacecraft design schemes based on value analysis, characterized in that: The specific steps of this method are as follows: Step 1: Establish an evaluation index system based on the functional dimension of value and determine the weight of each index in the evaluation index system ti ; When the evaluation index system includes five indicators, the five indicators are: key characteristic compliance index, ease of use index, test verification index, reliability index and processability index; Step 2: Determine the satisfaction score of each indicator for the kth candidate solution And the satisfaction coefficient of the kth candidate solution for each indicator , calculate the first k The satisfaction value of each indicator for each candidate solution , ; Step 3: Calculate the k The value factor of each candidate solution for each indicator , And sum up the value factors corresponding to all indicators of the k-th candidate solution to obtain the total value of the k-th candidate solution : ; Step 4: Calculate the maturity of the entire spacecraft of the kth candidate solution , the cost factor for the development of the kth candidate solution ; Decompose the kth candidate solution from top to bottom according to its components and identify the maturity of each part of the spacecraft; let the spacecraft consist of a platform and a payload, the platform consists of m subsystems, each subsystem consists of several single units; the payload consists of e single units; For the platform and payload, the corresponding reuse factors are T1 and T2 ,in T1 + T2 =1; (1) Maturity of computing platform For m subsystems under the platform, the reuse factors corresponding to all subsystems are M1, M2, ..., M y ,…,M m， ,y=1,2,...,m; For any subsystem y In terms of n stand-alone machines, of which the number of reusable stand-alone machines is b y , then the subsystem y maturity for: ; and thus the maturity of the platform ; (2) Calculation of load maturity For load, it includes e stand-alone machines, of which the number of reusable stand-alone machines is b p , then the maturity of the load is: ; Then the maturity of the entire spacecraft of the kth candidate solution is , the cost factor for the development of the kth candidate solution is ; When the platform consists of five subsystems, the five subsystems are: structural mechanism, GNC, measurement and control data transmission, power supply and distribution, and thermal control; Step 5: The total value of the kth candidate solution obtained in step 3 and the cost factors of the development of the k candidate solutions obtained in step 4 , the value of the kth candidate solution can be calculated: ; Similarly, the value of all candidate solutions can be obtained; finally, the candidate solution with the highest value is selected as the preferred one.

2. The method for weighing and optimizing spacecraft design solutions based on value analysis as claimed in claim 1, characterized in that: In step 1, the evaluation index system consists of j indicators, among which , i=1,2,...,j.

3. The method for weighing and optimizing spacecraft design solutions based on value analysis as claimed in claim 1, characterized in that: In step 2, , k=1,2,...,h, h means there are h candidate solutions in total.

4. The method for weighing and optimizing spacecraft design solutions based on value analysis as claimed in claim 1, characterized in that: In step 2, .

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