CN104517233A - Spaceflight single-unit product maturity control method - Google Patents

Abstract

The invention relates to a spaceflight single-unit product maturity control method. The method comprises the following steps: step one, selecting a product, and formulating each index which should be satisfied; step two, determining each index which the product actually satisfies; step three, obtaining maturity grade vectors of sub-elements through aggregating the maturity grade of each sub-element; step four, obtaining a weight of each sub-element relative to the product accordingly; and step five, obtaining the maturity grade of the product through a weight method. According to the invention, the spaceflight single-unit product maturity control method is a product maturity quantification method for realizing rapid maturation by developing an aerospace product through a small subsample, and provides an effective approach for measurement of reasonability and completeness of all technical elements of such a full-life cycle as product development, production, application and the like, and quality stability under certain functions and performance level.

Description

A kind of method that space flight unit product degree of ripeness controls

Technical field

The present invention relates to a kind of method that space flight unit product degree of ripeness controls, the present invention is by controlling to carry out quantitatively evaluating to the degree of ripeness of space product, comprehensive measurement has been carried out to the development progress situation of product, quality and reliability working condition and products application technical risk, for building quantification propelling and the checking system of space product development work, the closed loop management of quality and reliability work and self-perfection provide an approach.

Background technology

The feature that space product has that application technology is new, the lead time is long, to launch that risk is high, small enterprises are suited to filling in the gaps in the manufacture by large enterprises of complete sets of equipment wide, for guarantee task once successfully proposes higher requirement, and current Space Equipment scale amounts constantly expands, transmission frequency increases year by year, technical merit entirety rises to, space flight research and production gradually by long period, single-piece development mode to mass grind product, high density launch transition, to space flight development, produce and application propose new contradiction, new problem and new challenge.

How to solve batch the contradiction of producing and grinding between product and space product high-quality, highly reliable requirement, promote space product fast-ripenin, build the closed loop management system of quality of space product and reliability Work, strengthening quality and reliability ensures operational totality ability, becomes the problem that China's space industry is in the urgent need to address.

Space product degree of ripeness concept is the experience based on space industry engineering development and quality management many decades, on strengthened research space system engineering theoretical method basis, according to space product development, application, perfect, the objective law of solidification and the basic ideas of strengthening quality of space product and reliability management, propose through furtheing investigate and repeatedly practising.

On traditional system engineering process basis, product degree of ripeness concept, method have not only fully merged successful experience and the technological achievement of existing aerospace engineering management, and by realizing the expansion of " total factor, overall process, total system ", enhance aerospace engineering managerial ability, thus for controlling engineering risk further, realize the high-quality of navigational system, highly reliable requirement lays the foundation.

Summary of the invention

In order to solve the problem, the object of the invention is the complicacy for space system engineering management and singularity, for the quality and reliability solved under space product excessive risk, Small Sample Conditions ensures a kind of provide space flight unit product degree of ripeness to control method, with guarantee space product in development, produce and the high-quality, highly reliable of the link such as use, promote space product fast-ripenin; The present invention considers the design of product, the key characteristic of production and use procedure and key project, with reference to product degree of ripeness deciding grade and level criterion, the sub-key element affecting product maturation is identified, proposes innovative approach for weak link, and controlled in the overall process of Realization of Product and use.

In order to achieve the above object, the present invention has following technical scheme:

The method that a kind of space flight unit product degree of ripeness of the present invention controls, has following steps:

According to the technical connotation of sub-key element i and key check points, step one: select product, determines that this sub-key element specifies the indices AA that should meet _i; Wherein, i=1,2 ..., 23;

Step 2: according to AA _idetermine the actual indices YAA met of product _i;

Step 3: adopt statistical theory quantization method and normalization processing method, to AA _iand YAA _iindices compare one by one, with reference to product degree of ripeness deciding grade and level criterion, degree indices being met Development Techniques requirement quantizes display, obtains the indices beginning-maturity ranking matrix Z of sub-key element i _i.Then with each index degree of association matrix Q _iwith the indices beginning-maturity ranking matrix Z of sub-key element i _icarry out orthogonal coupling, obtain the degree of ripeness grade P of sub-key element i _i, namely by gathering the degree of ripeness grade of each sub-key element, obtain sub-key element degree of ripeness ranking vector P=[P ₁, P ₂..., P ₂₃] ^t;

Step 4: the weight size adopting Fuzzy AHP shared in product Capability Maturity Model to each sub-key element processes, and first processes " product-key element " layer and obtains the weight vectors W of each key element relative to product ₁, then " key element-sub-key element " layer is processed and obtains the weight vectors W of each sub-key element relative to key element ₂, and then obtain the weights W of each sub-key element relative to product, W=W ₂× W ₁;

Step 5: the degree of ripeness grade being obtained product by the method for weighting, namely $\mathrm{PRL}=W^T\×P=\underset{i=1}{\overset{23}{\mathrm{\Σ}}}{w}_i\×P_i,$ Wherein:

(1) sub-key element degree of ripeness factor:

The degree of ripeness grade P of sub-key element i _iaccording to each index degree of association matrix Q _iwith the indices beginning-maturity ranking matrix Z of sub-key element i _i, the degree of ripeness grade P of sub-key element i _ifuntcional relationship expression formula be $P_i=Q_i^T\×Z_i:$

$Q_i=\left[\begin{array}{c}{Q}_{i1}\\ Q_{i2}\\ .\\ .\\ .\\ Q_{\mathrm{in}}\end{array}\right],Z_i=\left[\begin{array}{c}\mathrm{fun}({\mathrm{YAA}}_{i1}-{\mathrm{AA}}_{i1})\\ \mathrm{fun}({\mathrm{YAA}}_{i2}-{\mathrm{AA}}_{i2})\\ .\\ .\\ .\\ \mathrm{fun}({\mathrm{YAA}}_{\mathrm{in}}-{\mathrm{AA}}_{\mathrm{in}})\end{array}\right]=\left[\begin{array}{c}{Z}_{i1}\\ Z_{i2}\\ .\\ .\\ .\\ Z_{\mathrm{in}}\end{array}\right],$

Wherein, fun () represents the product degree of ripeness deciding grade and level criterion to indices matching degree quantification treatment; AA _inrepresent the n-th index of the sub-key element regulation of this product i-th, YAA _inrepresent the actual index met of this product i-th sub-key element; Z _inrepresent quantification treatment result, according to product Capability Maturity Model and deciding grade and level criterion, Z _in∈ [1,2 ..., 8];

The degree of ripeness grade P of sub-key element i _icalculating completed by computing machine;

(2) the weighted value factor of sub-key element:

First " product-key element " layer is processed, compare between each key element between two, the fuzzy judgment matrix R of " product-key element " layer according to 0.1-0.9 scale successively scale, can be obtained ₁as follows:

$R_1=\left[\begin{array}{cccccc}{r}_{11}& r_{12}& .& .& .& r_{18}\\ r_{21}& r_{22}& .& .& .& r_{28}\\ .& .& & .& & .\\ .& .& & .& & .\\ .& .& & .& & .\\ r_{81}& r_{82}& .& .& .& r_{88}\end{array}\right];$

Wherein, (1) r _ij=0.5, i=1,2 ..., 8;

(2)r _ij=1-r _ji，i，j=1，2，…，8；

(3)r _ij=r _ik-r _jk，i，j，k=1，2，…，8；

Adopting least square method and method of Lagrange multipliers, obtaining weight vectors by solving:

W ₁=[w ₁，w ₂,…，w ₈] ^T;

Then " key element-sub-key element " layer is processed, this layer comprises 8 judgment matrixs, compare between each sub-key element in each judgment matrix between two, according to 0.1-0.9 scale successively scale, obtain 8 fuzzy judgment matrix respectively, according to least square method and method of Lagrange multipliers, try to achieve the weight vectors of each judgment matrix respectively, by aggregating, obtain the weight matrix W of sub-key element relative to key element ₂;

Pass through W=W ₂× W ₁obtain the weight of each sub-key element relative to product, each sub-key element is completed by computing machine relative to the calculating of the weight of product;

By calculating the degree of ripeness grade PRL of product above.

Wherein, described allocation of computer is CPU:Intel Duo i33220 box, mainboard: Asus P8B75, internal memory: 4GB, hard disk 500GB, display 19 cun; The matrix software for calculation that described computing machine adopts is the MATLAB business mathematics software of U.S. MathWorks Company.

Owing to taking above technical scheme, the present invention has the following advantages:

(1) Whole Process Control and the fine-grained management of product development is strengthened, 23 sub-key elements of product Capability Maturity Model cover the main project paid close attention to of Life cycle domestic demand of product design, manufacture, application, by controlling 23 sub-key elements and evaluate, can reflect the development progress situation of product, the effective prevention and control of actualizing technology risk and overall process become more meticulous quality management comprehensively; (2) unified metric is provided, selects the standard of product and method, product Capability Maturity Model is applicable to that space flight is at different levels, various product, 8 grades of product Capability Maturity Model meet the general flow of space product development, therefore product degree of ripeness can as a kind of instrument of like product development progress situation measuring not commensurate, for administrative authority provides reference frame; (3) quantified controlling product development situation, quick identification weak link, product Capability Maturity Model provides a kind of method of quantified controlling product development progress, by the expection matching degree of comparative product Current developments degree and task object, provide the quantitative evaluation result of each sub-key element, and identify product weak link and deficiency, offer help for evading product development technical risk as early as possible.

Accompanying drawing explanation

Fig. 1 is the block diagram of product degree of ripeness of the present invention, key element, sub-key element.

Embodiment

The present invention is the product degree of ripeness quantization method of a kind of System in Small Sample Situation development aerospace Realization of Product fast-ripenin, for rationality, the completeness of all technology essential factors of Life cycle such as product development, production and use, and the tolerance of quality stability provides effective way under certain function, performance level.

The present invention presses the development process of space product, product degree of ripeness is divided into 8 grades, progressively goes forward one by one according to principle prototype, engineering prototype, flying product, flight examination, repeatedly fly examination, three grades of sizings, secondary is shaped, one-level is shaped order.

The present invention presses the Life cycle of the design of product, production and use, product degree of ripeness is divided into 8 key elements, 23 sub-key elements, as shown in Figure 1

The method that a kind of space flight unit product degree of ripeness of the present invention controls, has following steps:

According to the technical connotation of sub-key element i and key check points, step one: select product, determines that this sub-key element specifies the indices AA that should meet _i; Wherein, i=1,2 ..., 23;

Step 2: according to AA _idetermine the actual indices YAA met of product _i;

Step 3: adopt statistical theory quantization method and normalization processing method, to AA _iand YAA _iindices compare one by one, with reference to product degree of ripeness deciding grade and level criterion, degree indices being met Development Techniques requirement quantizes display, obtains the indices beginning-maturity ranking matrix Z of sub-key element i _i.Then with each index degree of association matrix Q _iwith the indices beginning-maturity ranking matrix Z of sub-key element i _icarry out orthogonal coupling, obtain the degree of ripeness grade P of sub-key element i _i, namely by gathering the degree of ripeness grade of each sub-key element, obtain sub-key element degree of ripeness ranking vector P=[P ₁, P ₂..., P ₂₃] ^t;

Step 4: the weight size adopting Fuzzy AHP shared in product Capability Maturity Model to each sub-key element processes, and first processes " product-key element " layer and obtains the weight vectors W of each key element relative to product ₁, then " key element-sub-key element " layer is processed and obtains the weight vectors W of each sub-key element relative to key element ₂, and then obtain the weights W of each sub-key element relative to product, W=W ₂× W ₁;

Step 5: the degree of ripeness grade being obtained product by the method for weighting, namely $\mathrm{PRL}=W^T\×P=\underset{i=1}{\overset{23}{\mathrm{\Σ}}}{w}_i\×P_i,$ Wherein:

(1) sub-key element degree of ripeness factor:

The degree of ripeness grade P of sub-key element i _iaccording to each index degree of association matrix Q _iwith the indices beginning-maturity ranking matrix Z of sub-key element i _i, the degree of ripeness grade P of sub-key element i _ifuntcional relationship expression formula be $P_i=Q_i^T\×Z_i:$

$Q_i=\left[\begin{array}{c}{Q}_{i1}\\ Q_{i2}\\ .\\ .\\ .\\ Q_{\mathrm{in}}\end{array}\right],Z_i=\left[\begin{array}{c}\mathrm{fun}({\mathrm{YAA}}_{i1}-{\mathrm{AA}}_{i1})\\ \mathrm{fun}({\mathrm{YAA}}_{i2}-{\mathrm{AA}}_{i2})\\ .\\ .\\ .\\ \mathrm{fun}({\mathrm{YAA}}_{\mathrm{in}}-{\mathrm{AA}}_{\mathrm{in}})\end{array}\right]=\left[\begin{array}{c}{Z}_{i1}\\ Z_{i2}\\ .\\ .\\ .\\ Z_{\mathrm{in}}\end{array}\right],$

Wherein, fun () represents the product degree of ripeness deciding grade and level criterion to indices matching degree quantification treatment; AA _inrepresent the n-th index of the sub-key element regulation of this product i-th, YAA _inrepresent the actual index met of this product i-th sub-key element; Z _inrepresent quantification treatment result, according to product Capability Maturity Model and deciding grade and level criterion, Z _in∈ [1,2 ..., 8];

The degree of ripeness grade P of sub-key element i _icalculating completed by computing machine;

(2) the weighted value factor of sub-key element:

First " product-key element " layer is processed, compare between each key element between two, the fuzzy judgment matrix R of " product-key element " layer according to 0.1-0.9 scale successively scale, can be obtained ₁as follows:

$R_1=\left[\begin{array}{cccccc}{r}_{11}& r_{12}& .& .& .& r_{18}\\ r_{21}& r_{22}& .& .& .& r_{28}\\ .& .& & .& & .\\ .& .& & .& & .\\ .& .& & .& & .\\ r_{81}& r_{82}& .& .& .& r_{88}\end{array}\right];$

Wherein, (1) r _ii=0.5, i=1,2 ..., 8;

(2)r _ij=1-r _ji，i，j=1，2，…，8；

(3)r _ij=r _ik-r _jk,i,j，k=1，2，…，8；

Adopting least square method and method of Lagrange multipliers, obtaining weight vectors by solving:

W ₁=[w ₁,w ₂，…，w ₈] ^T；

Then " key element-sub-key element " layer is processed, this layer comprises 8 judgment matrixs, compare between each sub-key element in each judgment matrix between two, according to 0.1-0.9 scale successively scale, obtain 8 fuzzy judgment matrix respectively, according to least square method and the bright mouth multiplier method of glug, try to achieve the weight vectors of each judgment matrix respectively, by aggregating, obtain the weight matrix W of sub-key element relative to key element ₂;

Pass through W=W ₂× W ₁obtain the weight of each sub-key element relative to product, each sub-key element is completed by computing machine relative to the calculating of the weight of product;

By calculating the degree of ripeness grade PRL of product above.

Described allocation of computer is CPU:Intel Duo i33220 box, mainboard: Asus P8B75, internal memory: 4GB, hard disk 500GB, display 19 cun; The matrix software for calculation that described computing machine adopts is the MATLAB business mathematics software of U.S. MathWorks Company.

embodiment 1

By test and site assessment, determine the indices that certain type solar array driving mechanism product development technical requirement specifies and the actual indices reached as shown in the table.

Sub-key element	Set quota	Actual index
			The identification of 1-1-1 product development technical requirement and examination	AA 1	YAA 1
1-1-2 product design input identification with determine	AA 2	YAA 2
			1-2-1 product technology flow process and planning procedures and control thereof	AA 3	YAA 3
1-2-2RMS ensures work program and control thereof	AA 4	YAA 4
			1-2-3 basic product ensures work program and control thereof	AA 5	YAA 5
1-2-4 software development and software product ensure plan and control	AA 6	YAA 6
			The identification of 1-3-1 key characteristic and key project and control	AA 7	YAA 7
1-3-2 product RMS design and analysis and checking	AA 8	YAA 8
			1-3-3 can not the identification of test event and control	AA 9	YAA 9
The project implementation of 1-3-4 verification experimental verification and result	AA 10	YAA 10
			1-3-5 turning quality problem to zero	AA 11	YAA 11
1-3-6 state of the art controls	AA 12	YAA 12
			The accordance that 1-3-7 design exports and document integrity	AA 13	YAA 13
2-1-1 technical papers is formulated and change controls	AA 14	YAA 14
			2-1-2 process selection and taboo/limit the use of technology controlling and process	AA 15	YAA 15
The identification of 2-2-1 personnel, equipment and environmental requirement and guarantee	AA 16	YAA 16
			2-2-2 outsourcing, the external coordination project control	AA 17	YAA 17
2-3-1 production planning management	AA 18	YAA 18
			The 2-3-2 quality of production manages	AA 19	YAA 19
3-1-1 product pays formulation and the management of file	AA 20	YAA 20
			3-1-2 product bug prediction scheme is formulated	AA 21	YAA 21

The planning of 3-2-1 product usage data and collection	AA 22	YAA 22
			The analysis of 3-2-2 product usage data and utilization	AA 23	YAA 23

In the present invention, statistical theory quantization method and normalization processing method is adopted, to AA _iand YAA _iindices compare one by one, with reference to product degree of ripeness deciding grade and level criterion, degree indices being met Development Techniques requirement quantizes display, obtains the indices beginning-maturity ranking matrix Z of sub-key element i _i.Then with each index degree of association matrix Q _iwith the indices beginning-maturity ranking matrix Z of sub-key element i _icarry out orthogonal coupling, obtain the degree of ripeness grade P of sub-key element i _i, namely

Due to $Q_i=\left[\begin{array}{c}{Q}_{i1}\\ Q_{i2}\\ .\\ .\\ .\\ Q_{\mathrm{in}}\end{array}\right],Z_i=\left[\begin{array}{c}\mathrm{fun}({\mathrm{YAA}}_{i1}-{\mathrm{AA}}_{i1})\\ \mathrm{fun}({\mathrm{YAA}}_{i2}-{\mathrm{AA}}_{i2})\\ .\\ .\\ .\\ \mathrm{fun}({\mathrm{YAA}}_{\mathrm{in}}-{\mathrm{AA}}_{\mathrm{in}})\end{array}\right]=\left[\begin{array}{c}{Z}_{i1}\\ Z_{i2}\\ .\\ .\\ .\\ Z_{\mathrm{in}}\end{array}\right],P_i=Q_i^T\×Z_i,$

By gathering, the degree of ripeness grade obtaining each sub-key element is as shown in the table.

Sub-key element 1-1-1	Sub-key element 1-1-2	Sub-key element 1-2-1	Sub-key element 1-2-2	Sub-key element 1-2-3	Sub-key element 1-2-4
						3	4	2	4	5	5
Sub-key element 1-3-1	Sub-key element 1-3-2	Sub-key element 1-3-3	Sub-key element 1-3-4	Sub-key element 1-3-5	Sub-key element 1-3-6
						2	2	4	4	3	4
Sub-key element 1-3-7	Sub-key element 2-1-1	Sub-key element 2-1-2	Sub-key element 2-2-1	Sub-key element 2-2-2	Sub-key element 2-3-1
						3	3	3	4	2	2
Sub-key element 2-3-2	Sub-key element 3-1-1	Sub-key element 3-1-2	Sub-key element 3-2-1	Sub-key element 3-2-2
						4	3	2	2	3

In the present invention, the weight size adopting Fuzzy AHP shared in product Capability Maturity Model to each sub-key element processes, and first processes " product-key element " layer and obtains the weight vectors W of each key element relative to product ₁, then " key element-sub-key element " layer is processed and obtains the weight vectors W of each sub-key element relative to key element ₂, adopt least square method and method of Lagrange multipliers, obtain weight vectors obtain by solving:

$W_1=\left[\begin{array}{c}0.124\\ 0.163\\ 0.392\\ 0.092\\ 0.068\\ 0.068\\ 0.053\\ 0.04\end{array}\right],W_2=\left[\begin{array}{cccccccc}0.5& 0& 0& 0& 0& 0& 0& 0\\ 0.5& 0& 0& 0& 0& 0& 0& 0\\ 0& 0.25& 0& 0& 0& 0& 0& 0\\ 0& 0.26& 0& 0& 0& 0& 0& 0\\ .& .& .& .& .& .& .& .\\ .& .& .& .& .& .& .& .\\ .& .& .& .& .& .& .& .\\ 0& 0& 0& 0& 0& 0& 0.64& 0\\ 0& 0& 0& 0& 0& 0& 0.36& 0\\ 0& 0& 0& 0& 0& 0& 0& 0.3\\ 0& 0& 0& 0& 0& 0& 0& 0.7\end{array}\right]$

Each sub-key element is relative to the weights W=W of product ₂× W ₁, through calculating, obtain each sub-key element as shown in the table relative to the weight of product.

Sub-key element 1-1-1	Sub-key element 1-1-2	Sub-key element 1-2-1	Sub-key element 1-2-2	Sub-key element 1-2-3	Sub-key element 1-2-4
						0.062	0.062	0.040	0.043	0.040	0.040
Sub-key element 1-3-1	Sub-key element 1-3-2	Sub-key element 1-3-3	Sub-key element 1-3-4	Sub-key element 1-3-5	Sub-key element 1-3-6
						0.050	0.050	0.056	0.053	0.059	0.062
Sub-key element 1-3-7	Sub-key element 2-1-1	Sub-key element 2-1-2	Sub-key element 2-2-1	Sub-key element 2-2-2	Sub-key element 2-3-1
						0.062	0.046	0.046	0.034	0.034	0.031
Sub-key element 2-3-2	Sub-key element 3-1-1	Sub-key element 3-1-2	Sub-key element 3-2-1	Sub-key element 3-2-2
						0.037	0.034	0.019	0.012	0.028

In the present invention, the degree of ripeness grade of product is obtained by the method for weighting, namely according to aerospace enterprise group standard " aerospace unit product degree of ripeness deciding grade and level regulation ", Q/QJA53-2010 and Q/QJA146-2013, judge that this type solar array driving mechanism product is as " flying product " (product degree of ripeness grade name), by comparing discovery, the present invention truly reflects the development progress situation of product, and objectively respond out the weak link of product development process, be conducive to aerospace product fast lifting product degree of ripeness

As can be seen from the explanation of principle and system of the present invention and example, the invention provides one and process image file system based on image display, map display module, MIM message input module, information writing module, track generation and sharing module, this method and system have simply, flexibly, the feature such as interactive and recreational strong, applied range.But more than illustrate and can not limit the enforceable scope of the present invention, the obvious or unconspicuous change that every professional person does on basis of the present invention, modify or improvement, all should be considered as not departing from Spirit Essence of the present invention.

Claims (2)

1. a method for space flight unit product degree of ripeness control, is characterized in that: have following steps:

According to the technical connotation of sub-key element i and key check points, step one: select product, determines that this sub-key element specifies the indices AA that should meet _i; Wherein, i=1,2 ..., 23;

Step 2: according to AA _idetermine the actual indices YAA met of product _i;

Step 3: adopt statistical theory quantization method and normalization processing method, to AA _iand YAA _iindices compare one by one, with reference to product degree of ripeness deciding grade and level criterion, degree indices being met Development Techniques requirement quantizes display, obtains the indices beginning-maturity ranking matrix Z of sub-key element i _i.Then with each index degree of association matrix Q _iwith the indices beginning-maturity ranking matrix Z of sub-key element i _icarry out orthogonal coupling, obtain the degree of ripeness grade P of sub-key element i _i, namely by gathering the degree of ripeness grade of each sub-key element, obtain sub-key element degree of ripeness ranking vector P=[P ₁, P ₂..., P ₂₃] ^t;

Step 4: the weight size adopting Fuzzy AHP shared in product Capability Maturity Model to each sub-key element processes, and first processes " product-key element " layer and obtains the weight vectors W of each key element relative to product ₁, then " key element-sub-key element " layer is processed and obtains the weight vectors W of each sub-key element relative to key element ₂, and then obtain the weights W of each sub-key element relative to product, W=W ₂× W ₁;

Step 5: the degree of ripeness grade being obtained product by the method for weighting, namely $\mathrm{PRL}=W^T\×P=\underset{i=1}{\overset{23}{\mathrm{\Σ}}}{w}_i\×P_i,$ Wherein:

(1) sub-key element degree of ripeness factor:

The degree of ripeness grade P of sub-key element i _iaccording to each index degree of association matrix Q _iwith the indices beginning-maturity ranking matrix Z of sub-key element i _i, the degree of ripeness grade P of sub-key element i _ifuntcional relationship expression formula be $P_i=Q_i^T\×Z_i:$

$Q_i=\left[\begin{array}{c}{Q}_{i1}\\ Q_{i2}\\ .\\ .\\ .\\ Q_{\mathrm{in}}\end{array}\right],Z_i=\left[\begin{array}{c}\mathrm{fun}({\mathrm{YAA}}_{i1}-{\mathrm{AA}}_{i1})\\ \mathrm{fun}({\mathrm{YAA}}_{i2}-{\mathrm{AA}}_{i2})\\ .\\ .\\ .\\ \mathrm{fun}({\mathrm{YAA}}_{\mathrm{in}}-{\mathrm{AA}}_{\mathrm{in}})\end{array}\right]=\left[\begin{array}{c}{Z}_{i1}\\ Z_{i2}\\ .\\ .\\ .\\ Z_{\mathrm{in}}\end{array}\right],$

Wherein, fun () represents the product degree of ripeness deciding grade and level criterion to indices matching degree quantification treatment; AA _inrepresent the n-th index of the sub-key element regulation of this product i-th, YAA _inrepresent the actual index met of this product i-th sub-key element; Z _inrepresent quantification treatment result, according to product Capability Maturity Model and deciding grade and level criterion, Z _in∈ [1,2 ..., 8];

The degree of ripeness grade P of sub-key element i _icalculating completed by computing machine;

(2) the weighted value factor of sub-key element:

First " product-key element " layer is processed, compare between each key element between two, the fuzzy judgment matrix R of " product-key element " layer according to 0.1-0.9 scale successively scale, can be obtained ₁as follows:

$R_1=\left[\begin{array}{cccccc}{r}_{11}& r_{12}& .& .& .& r_{18}\\ r_{21}& r_{22}& .& .& .& r_{28}\\ .& .& & .& & .\\ .& .& & .& & .\\ .& .& & .& & .\\ r_{81}& r_{82}& .& .& .& r_{88}\end{array}\right];$

Wherein, (1) r _ij=0.5, i=1,2 ..., 8;

(2)r _ij=1-r _ji,i，j=1,2，…，8；

(3)r _ij=r _ik-r _jk,i，j，k=1，2，…，8；

Adopting least square method and method of Lagrange multipliers, obtaining weight vectors by solving:

W ₁=[w ₁,w ₂，…，w ₈] ^T；

Then " key element-sub-key element " layer is processed, this layer comprises 8 judgment matrixs, compare between each sub-key element in each judgment matrix between two, according to 0.1-0.9 scale successively scale, obtain 8 fuzzy judgment matrix respectively, according to least square method and method of Lagrange multipliers, try to achieve the weight vectors of each judgment matrix respectively, by aggregating, obtain the weight matrix W of sub-key element relative to key element ₂;

Pass through W=W ₂× W ₁obtain the weight of each sub-key element relative to product, each sub-key element is completed by computing machine relative to the calculating of the weight of product;

By calculating the degree of ripeness grade PRL of product above.

2. the method for a kind of space flight unit product degree of ripeness control as claimed in claim 1, is characterized in that: described allocation of computer is CPU:Intel Duo i33220 box, mainboard: Asus P8B75, internal memory: 4GB, hard disk 500GB, display 19 cun; The matrix software for calculation that described computing machine adopts is the MATLAB business mathematics software of U.S. MathWorks Company.