CN114693193A - Equipment scientific research project risk factor evaluation system and method - Google Patents
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Abstract
The invention discloses a risk factor evaluation system for equipment scientific research projects, which comprises a server, a user terminal and a client terminal; the method comprises the steps that a user terminal decomposes a scientific research project of equipment to be evaluated into magnitude units, subdivides project risks into secondary risk factors, sends the magnitude units and the secondary risk factors to a server, receives risk magnitude values from the server, divides risk grades and outputs evaluation results; the client terminal endows the second-level risk factors of the project with evaluation values, outputs the evaluation values and transmits the evaluation values to the server; and the server receives the evaluation values from the client terminal, respectively calculates the magnitude unit risk values of different levels, and transmits the magnitude unit risk values to the user terminal. According to the method, the risk occurrence probability of each level of subsystem and the influence of the overall project completion condition are evaluated, the risk factors are sent to the designated objects with corresponding technical matching degrees to be evaluated and assigned, and the management efficiency and the result effectiveness of the risk factor evaluation of the equipment scientific research project are improved by utilizing an information technology.
Description
Technical Field
The invention relates to the technical field of risk evaluation of equipment scientific research projects, in particular to a system and a method for evaluating risk factors of the equipment scientific research projects.
Background
The equipment scientific research project is large in uncertainty and high in cost, and various researched risks can be conducted in a chain mode, so that effects on military and research units are finally achieved. The method comprises the steps of converting various risks in the project development process into quantifiable over-limit amounts, identifying main factors and occurrence conditions influencing the project risks, measuring and calculating the probability and the influence degree of the project risks by using an analysis method combining qualitative analysis and quantitative analysis according to the characteristics of the project, calculating the potential risk of a subsystem, finally determining the overall risk level of the project, and providing a basis for the design of incentive constraint terms and cost compensation schemes.
Research in the field of cost risk is currently focused on the use of simulation methods. In the aspect of risk estimation of construction cost of construction engineering, a learner provides methods such as Monte Carlo simulation and sensitivity analysis, identifies and analyzes time and cost risks in the construction engineering, and finds out cost variance to guide project decision making; the Wang Yinli and the like propose and establish a project progress-cost joint risk estimation model, and the risk probability distribution under the progress-cost combination is obtained through the statistical analysis of the simulation result; yangbaoseng et al propose to establish a dynamic random activity network simulation model, and emphatically study the influence of serial iteration on the risk of progress cost, and think that serial iteration is the main reason causing the distribution of construction period cost to present a right-hand tendency and positive correlation. In the aspect of estimating research and development cost of equipment scientific research projects, Bielecki predicts whether the research and development cost will increase by using logistic regression, and predicts the cost increase by using a multivariate regression model for the increased scientific research projects; xushi and the like propose a joint risk probability estimation method, and the risk estimation of scientific research project plans can not be completed under the joint constraint of cost and progress is realized by carrying out statistical analysis and regression analysis on Monte Carlo simulation output results; the Weidong Tao and the like propose a weighted regression measurement model based on an entropy theory to improve the cost prediction precision developed for large complex equipment so as to reduce the influence of cost variation in the actual development process; xujihui and the like propose risk modeling for processing airplane development cost by utilizing improved Monte Carlo based on a risk driving theory, and verify the rationality and effectiveness of the improved method; and the method proposes and constructs a large scientific research project cost risk prediction model based on gray correlation degree, and better solves the problems of similar project selection, project total cost and cost estimation in each period and cost fluctuation prediction.
The disadvantages of the above-mentioned research and technology are mainly reflected in: firstly, the research on project risks focuses on providing a quantitative analysis result by adopting a simulation method, does not pay attention to the analysis of risk related influence factors, is lack of identification on risk occurrence sources so that the result is difficult to verify, and parameters required by simulation also depend on subjective judgment; secondly, most researches only define the consequence of project development as success or failure, and simply determine the cost excess probability as cost risk and lack the research on the influence consequence; and thirdly, the project risk relates to multiple disciplines such as technology, economy, project management and the like, one expert is difficult to have multiple cross-discipline backgrounds and give accurate scores, the accuracy of the expert scoring directly influences the effectiveness of an evaluation result, the matching degree in the technical field is a key factor of the accuracy of the expert scoring, and the existing evaluation method is lack of a related technical scheme which can adapt the technical field of the expert to risk factors.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a system and a method for evaluating risk factors of equipment scientific research projects.
In order to achieve the purpose, the system comprises a server, at least one user terminal and at least one client terminal;
the user terminal: the system comprises a server, a risk classification unit and a risk classification unit, wherein the risk classification unit is used for decomposing equipment scientific research projects to be evaluated into a plurality of quantity-level units, subdividing project risks into a plurality of secondary risk factors, sending the quantity-level units and the secondary risk factors of the equipment scientific research projects to be evaluated to the server, receiving risk quantity values from the server, classifying risk grades and outputting evaluation results;
the client terminal: the system is used for downloading the magnitude unit and the secondary risk factor from the server, endowing an evaluation value to the secondary risk factor of the project, and outputting the evaluation value to the server;
the server: the server is used for sending the magnitude units and the secondary risk factors to the client terminals, wherein the secondary risk factors are of different types, and the server sends the magnitude units and the secondary risk factors to the client terminals of corresponding types according to the types of the secondary risk factors; and the server receives the evaluation quantity values from the client terminal, respectively calculates the magnitude unit risk quantity values of different levels, and transmits the magnitude unit risk quantity values to the user terminal.
Further, the user terminal comprises a system decomposition module, a risk index module and a risk grade output module;
the system decomposition module: longitudinally decomposing equipment scientific research projects based on WBS technology to form magnitude units;
the risk indicator module: decomposing the scientific research project of the equipment to be evaluated into a plurality of secondary risk factors from two dimensions of project over-branch probability risk and influence consequence risk, wherein each secondary risk factor has a specified professional type and is used for matching with a client terminal of a corresponding type;
the risk level output module: and matching the risk value of the magnitude unit output by the server with a set risk curve to obtain a corresponding risk grade and a corresponding measure, and outputting an evaluation result.
Furthermore, the evaluation value of the secondary risk factor of the project given to the project risk by the client terminal is a weighted value of the action degree of the secondary factor on each project influence factor, and the higher the score is, the greater the risk is represented.
Furthermore, the server comprises an evaluation quantity value sending and collecting module, a project excess probability quantity value calculating module, a project influence consequence quantity value calculating module and a project risk quantity value calculating module;
the evaluation quantity value sending and collecting module: sending the magnitude unit and the secondary risk factor output by the user terminal to the client terminal of the corresponding type;
the item over-branch probability magnitude calculation module: respectively calculating the project over-support probability quantity values of the magnitude units of different levels in the magnitude units according to the magnitude units output by the user terminal and the evaluation quantity values output by the client terminalP f ；
Said itemThe eye influence consequence value calculation module: respectively calculating the item influence consequence quantity values of the magnitude units of different levels in the magnitude units according to the magnitude units output by the user terminal and the evaluation quantity values output by the client terminalC f ；
The item risk value calculation module: respectively calculating the item risk value of the magnitude units of different levels in the magnitude units according to the output magnitude units and the evaluation value output by the client terminalF f 。
Further, the item over-run probability measureP f The calculation method comprises the following steps:
in the formula (I), the compound is shown in the specification,W i is shown asiThe probability of occurrence of an item over-run of a factor,m ij is shown asiThe first of the individual factorsjThe proportion of the occurrence of the quantum unit,V j the evaluation quantity value is represented by the value,Wrepresents a set of hyper-branch occurrence probability weights,Ma probability evaluation matrix of the item over-run is represented,Vand (4) representing an item over-branch probability evaluation value vector, wherein T is a transposed symbol.
Still further, the item affects outcome magnitudeC f The calculation method comprises the following steps:
C f = E’·Y T
in the formula (I), the compound is shown in the specification,E’representing the fuzzy comprehensive evaluation matrix after the normalization processing,Yrepresenting the term impact consequence magnitude vector, T is the transposed symbol.
Further, the item risk valueF f The calculation method comprises the following steps:
F f =1-P s C s =1-(1-P f )(1-C f )= P f +C f - P f C f
in the formula: ps represents the occurrence probability of budget non-exceeding; cs represents the effect on the project that the budget is not exceeded.
Furthermore, the types of the secondary risk factors comprise technical factors, economic factors, progress factors and influence consequence factors, wherein the technical factors comprise technical advancement, technical innovation, technical inheritance, technical complexity and research unit conditions, the economic factors comprise national economic conditions and currency expansion rate, international situation and exchange rate change conditions, domestic policy guidance, industrial environment conditions and product supply and demand relationships, and the progress factors comprise subsystem progress and project overall progress; the factors influencing the consequence comprise the supplement of the overbooking, the reduction of indexes and the termination of projects.
The invention also provides an equipment scientific research project risk factor evaluation method, which is realized based on an equipment scientific research project risk factor evaluation system and comprises the following steps:
1) the user terminal decomposes the equipment scientific research project to be evaluated into a plurality of quantitative units, subdivides the project risk into a plurality of secondary risk factors, and sends the quantitative units and the secondary risk factors of the equipment scientific research project to be evaluated to the server;
2) the server sends the magnitude unit and the secondary risk factor to a client terminal with a corresponding type according to the type of the secondary risk factor;
3) the client terminal downloads the magnitude unit and the secondary risk factor from the server, gives an evaluation value to the secondary risk factor of the project, outputs the evaluation value and transmits the evaluation value to the server;
4) the server receives the evaluation quantity values from the client terminal, respectively calculates the magnitude unit risk quantity values of different levels, and transmits the magnitude unit risk quantity values to the user terminal;
5) and the user terminal receives the risk value from the server, divides the risk level and outputs an evaluation result.
Preferably, the server distributes the magnitude units and the secondary risk factors to corresponding client terminals according to a list sequence stored in advance, sets task time limits, and evaluates that a user sends a receiving confirmation instruction to the server through the client terminals; if the server does not receive the receiving confirmation instruction within the appointed time, the server sends the receiving confirmation instruction to the next corresponding client terminal in the list, and if the alternative client terminal in the list is 0, the server sends a distribution failure instruction and a request delay instruction to the user terminal.
The risk factor evaluation system for equipment scientific research projects has the beneficial effects that:
1. according to the method, influence factor identification is carried out based on WBS, a risk factor concept is introduced according to the characteristic that project risk data is difficult to measure accurately, and a risk assessment means combining qualitative and quantitative is adopted;
2. the method directly converts the evaluation of the risk size into the evaluation of the risk factors, sends the risk factors to the designated objects with corresponding technical matching degrees for evaluation and assignment, and improves the management efficiency and result effectiveness of the risk factor evaluation of equipment scientific research projects by utilizing the information technology
3. The method carries out magnitude evaluation on the possibility of the occurrence of the overboost and the influence of project completion conditions; analyzing cost overboost probability from three angles of technology, economy and progress, and carrying out internal and external analysis on the possibility of overboost occurrence; the influence consequence of project completion condition, supplement and supplement the conditions such as over-support, index reduction, project termination and the like;
4. according to the method, risk levels are confirmed step by means of the equal risk curves, subsystem risk values are sequentially obtained, the subsystem risk values are weighted to obtain the overall risk value of the project, and reference is provided for the design of the excitation constraint coefficient;
5. according to the method and the system, the management efficiency and the result effectiveness of the equipment scientific research project risk factor evaluation are improved through information interaction among the client terminal, the user terminal and the server by utilizing an informatization technology.
Drawings
FIG. 1 is a block diagram of a risk factor evaluation system for equipment scientific research projects according to the present invention.
Fig. 2 is an exploded view of a certain type of mine-resistant system in embodiment 2.
Fig. 3 shows the weight of a certain type of anti-mine system in example 2.
Detailed Description
The invention is described in further detail below with reference to the figures and specific embodiments.
The equipment scientific research project system is complex in structure and comprises subsystems, components, assemblies and the like. The WBS technology is a common practice of project management, and is a modern management means suitable for major engineering project construction. The WBS technology is used for carrying out quantitative analysis on the equipment scientific research project cost, the system decomposition is carried out on the equipment scientific research projects step by step and item by item according to the characteristics of the task package, the investment direction and the investment amount of the equipment scientific research expenses can be displayed clearly, major risk sources are distinguished visually and effectively, a cost risk index system is established, and the prepositive process of equipment scientific research project cost risk assessment is completed.
The traditional equipment scientific research project risk assessment system directly simulates the original project assessment mode by software and aims to improve the communication efficiency of personnel and the management efficiency of affairs by utilizing an informatization technology. With the continuous development of information technology and the continuous improvement of software and hardware performance, a new-generation engineering project management system is constructed on the basis of new technologies represented by cloud computing, mobile internet, internet of things, artificial intelligence and the like, and the existing project risk assessment management mode and mechanism are influenced.
Example 1
As shown in fig. 1, the risk factor evaluation system for an equipment research project according to the present invention includes a server 3, at least one user terminal 1, and at least one client terminal 2. In the system, a user terminal 1 is used by project management personnel, and is used for creating a scientific research project to be evaluated, decomposing a magnitude unit of the project, determining a secondary risk factor, dividing a risk grade according to a risk magnitude value, and outputting an evaluation result. The user terminal 2 is used by project experts as evaluation users and used for endowing evaluation values to the secondary risk factors of projects, and the server 3 is used for data transmission and calculation.
The user terminal 1 comprises a system decomposition module 11, a risk index module 12 and a risk level output module 13. The system decomposition module 11: longitudinally decomposing equipment scientific research projects based on WBS technology to form magnitude units; risk indicator module 12: decomposing the scientific research project of the equipment to be evaluated into a plurality of secondary risk factors from two dimensions of project over-branch probability risk and influence consequence risk, wherein each secondary risk factor has a specified professional type and is used for matching with a client terminal 2 of a corresponding type; risk level output module 13: and matching the risk value of the magnitude unit output by the server 3 with a set risk curve to obtain a corresponding risk grade and a corresponding measure, and outputting an evaluation result.
The system decomposition module 11 decomposes into a plurality of magnitude units layer by applying WBS technology to form a task organization form of a tree structure. In the informatization management system for risk factor evaluation of equipment scientific research projects, the equipment scientific research projects are longitudinally decomposed according to magnitude units, and the decomposition process is deepened and progressed layer by layer until the granularity of the level of a working unit is not suitable for subdivision. The decomposition granularity is mainly three levels before the solidification from the top layer, and the three levels are decomposed layer by layer from the top layer to form a subsystem, a subsystem and a working unit, so that a magnitude unit system belonging to the whole system is formed. And carrying out risk decomposition to measure and calculate the risk value of each magnitude unit to form a multi-level structure system with the risk value corresponding to the scientific research work content. All the divided levels are regarded as the total system composition elements with independent attributes and are clearly defined in the evaluation index.
The risk indicator module 12 constructs a cost risk indicator system from two levels of the excess probability and the influence degree according to the definition of the project risk on the basis of the project system decomposition.
The overbranching probability risk index comprises a technical factor, an economic factor and a progress factor.
The technical factors firstly predict the advancement of the technology required by the project, which is closely related to the tactical technical index, and the higher the tactical technical index is, the greater the implementation difficulty is, at this time, the proportion problem of the new technology and the old technology, namely the relationship between the technical innovation and the inheritance, is considered. If the target function cannot be realized by relying on the prior art, a new technology is developed, and a large amount of research and development cost and labor cost are invested to realize the breakthrough of the key technology; if the existing technology can meet the target requirement, the degree of association with the target technology should be considered, and whether material or process adjustment is needed to adapt to the new project system. Meanwhile, the complexity of the technology is also noticed, whether a plurality of technologies of different types can be simultaneously applied to the system to meet the requirements or not is judged, and if the technology joint debugging cannot pass, the cost is increased. In addition, the qualification conditions such as the qualification, work environment, organization structure and credit condition of the undertaking units also affect the level of realization of the technology in the project, and the passing period cost, equipment loss and the like are reflected in the cost. The secondary factors and evaluation criteria of the technical factors proposed in this example are shown in table 1.
The economic factor mainly causes the change of purchasing cost by external environments such as macroscopic economy, market industry, microscopic economy and the like. The currency expansion rate, the price rising amplitude and the currency depreciation rate in national economy can directly act on the change of project development and procurement cost; the reconstruction of the international pattern and the adjustment of the national relationship drive the rise and fall of the international exchange rate, and the exchange of currency required by import and export is an important factor influencing the cost of parts which cannot be localized; meanwhile, the state can indirectly reflect the transaction price by reducing tax related to the development of the project of the research unit, increasing the localization degree of the supporting equipment to be reduced, and encouraging the foreign cooperation unit to improve the service guarantee level. In addition, the number of the competent research units in the industry is related to the purchasing mode, for example, only one competent research unit exists, the military has to purchase from a single source, and the research units can utilize the inequality of cost information to grasp, so that the equipment research price deviates from the actual cost and inclines towards the favorable direction. The supply and demand in the market environment determines the price, once the requirement of the military exceeds the normal level of the supply of the research unit, the military is in a weak position in the dynamic game process of the supply and demand parties, and the military has to pay more to meet the requirement of the research unit. The secondary factors and evaluation criteria of the economic factors proposed in this example are shown in table 2.
The progress factor aspect refers to that the system structure is decomposed before the project is developed, and a progress plan is made according to the construction period of the whole project and each sub-project so as to ensure that project activities can be pushed forward according to the plan. The network planning map can clearly reflect the progress of the project in each stage, the required quantity of various resources, the cost expenditure and the key activities and the key routes of the whole project, integrate the progress of each subsystem to realize the overall planning and reasonable arrangement of the whole project of the project, and achieve the expected goal of completing the project with the least time and resources. If the prophase progress planning of a certain subsystem is unreasonable, the development of other related subsystems can be influenced, and the whole progress of a project is interrupted in the actual development process; the matching of the subsystem schedule and the overall project schedule is also of great importance, and the optimal scheme can be found through the key path only by realizing reasonable configuration. Once a project is postponed or even interrupted, a chain effect of increased costs is induced, resulting in additional staff compensation, production equipment operation, default fees, and other miscarriage costs. The secondary factor and evaluation criteria of the progress factor proposed in this embodiment are shown in table 3.
Risk index of impact outcome:
in practice, the influence caused by cost overbtribution is not only in two states of successful development and failure, but also relates to the expression forms of overbtribution supplement, overbtribution reduction, project termination and the like.
The excessive compensation means that the technical attack and the technical coordination and related tests need to be organized due to the reasons of overhigh technical attack and difficulty, change of economic conditions or delay of construction period and the like, corresponding test equipment or external coordination needs to be added when necessary, and direct development cost is increased, so that the existing actual expenditure cost is overhigh and exceeds the preset approximate calculation limit. At this time, the project can meet the expected development requirement only by adding manpower, material resources and financial resources to make up for the excess amount caused by the cost increase.
The index reduction means that the expected requirements cannot be met by delaying the progress and adding expenses within the expected time limit, and only the performance can be reduced. The technical bottleneck is difficult to overcome by the research and development conditions of the existing production process, equipment and facilities, or imported components are difficult to obtain due to the influence of the international political structure, the components cannot be localized in a short time, the finished products of the scientific research projects cannot reach the specified performance level, the original technical requirements cannot be met, and the project development can be completed only by reducing the performance indexes.
The project stopping means that due to the fact that the difficulty of technical attack and customs is too high, the expected fund chain is insufficient in supply, the project development cannot be completed within the specified time, and the project development is meaningless due to too much progress delay and additional expenditure; or the cost effectiveness ratio of the finished product function developed under the existing conditions is too low, new more low-price substitutes are already appeared, and only the project is stopped to evaluate whether the value of the continuous development exists.
Risk level output module 13: and matching the risk value of the magnitude unit output by the server 3 with the set risk curve by means of the equal risk curve to obtain the risk grade of the whole project and form a risk evaluation result. And dividing the project risks into low risks, medium risks and high risks, and determining the grade of the project risks of the equipment scientific research project. It is generally believed that the first and second electrodes,F f <0.3the risk is low, the influence on the development plan target of the equipment is small, and the phenomena of performance reduction, purchase cost increase and progress interruption are few; between0.3<F f <0.7The risk between the two is medium, and the target of equipment development plan is influenced, so that certain performance is reduced, and certain purchasing cost is increased;F f >0.7the risk is high, the risk occurrence probability is high, the equipment development plan target is greatly influenced, and obvious performance reduction, purchase cost increase and progress interruption phenomena are caused.
Evaluation value of secondary risk factor of project to project risk endowing of client terminal 2The weight value of the action degree of the secondary factor on each item influence factor. The client terminal 2 is used by technical field experts, economic cost experts and progress analysis experts, and is used as the second-level risk factor corresponding to the technical field in the project by the experts in different technical fields in [0,1 ]]Scoring in intervals, wherein the higher the score is, the higher the risk is, and the score is respectivelyV j1,V j2,V i3,(j=1,2,3,4,5;i=1,2,3)。
The server 3 comprises an evaluation quantity value sending and collecting module 31, a project excess probability quantity value calculating module 32, a project influence consequence quantity value calculating module 33 and a project risk quantity value calculating module 34. The evaluation quantity value sending and collecting module 31: and sending the magnitude unit and the secondary risk factor output by the user terminal 1 to the client terminal 2 of the corresponding type.
The evaluation quantity value sending and collecting module 31 sends the magnitude units and the secondary risk factors output by the user terminal 1 to the client terminals 2 of the corresponding types. The evaluation quantity value sending and collecting module 31 distributes the magnitude units and the secondary risk factors to the corresponding client terminals 2 according to the list sequence stored in advance, sets task time limits, and sends a receiving confirmation instruction to the server 3 through the client terminals 2 by an evaluation user; if the server 3 does not receive the receiving confirmation instruction within the specified time, the receiving confirmation instruction is sent to the next corresponding client terminal 2 in the list, and if the alternative client terminal 2 in the list is 0, the distributing failure instruction and the request delay instruction are sent to the user terminal 1.
Item hyper-branch probability magnitude calculation module 32: respectively calculating the project overdraft probability magnitude of the magnitude units of different levels in the magnitude units according to the magnitude units output by the user terminal 1 and the evaluation magnitudes output by the client terminal 2P f 。
The probability of expense risk occurrence is mainly influenced by technical dependence, purchasing cost variation amplitude and scheduling period. Therefore, the influence factor set of the occurrence probability of the hyper-branches is setA= technical, economic, progress } = ∑ mediumA 1 , A 2 ,A 3 And giving different weights by combining the action degrees of all influence factors in equipment scientific research project typesThe specific weight value is set by the expert according to the actual condition of the project, and the weight set corresponding to each factor is assumedW={W 1 ,W 2 ,W 3 }，W 1 +W 2 +W 3 =1。
The influence factor set can be further subdivided into:A 1 = technical advancement, technical innovation, technical inheritance, technical complexity, unit condition of research } =a 11 ,a 12 ,a 13 ,a 14 ,a 15 }，A 2 = national economic situation, international situation, domestic policy guidance, industry environment change, product supply and demand relationship } = retaining openinga 21 ,a 22 ,a 23 ,a 24 ,a 25 }，A 3 = subsystem progress, project overall progress } = facial gesturea 31 ,a 32 }. Each second-order factor weightW ij According to the importance degree, the importance degree is set to satisfy sigmaW j1=1，∑W j2=1，∑W i3=1，(j=1,2,3,4,5;i=1,2,3)。
The project overbooking probability magnitude calculation module 32 receives an evaluation magnitude given to the project risk by a secondary risk factor of the project, which is sent by the client terminal 2, constructs a joint evaluation result of an expert group through a weighting method on the basis of an evaluation result of the overbooking occurrence probability of the expert, and obtains magnitudes of a technical index, an economic index and a progress index through weighting calculation.
Set of endowing factorsACorresponding evaluation setVMagnitude vectorV =(V 1,V 2,V 3,V 4,V 5) = (0,0.25,0.5,0.75,1), evaluation set is set according to index systemVThe magnitude descriptions are shown in table 4.
The evaluation values were measuredv i Corresponding to the corresponding evaluation valueV j Counting the ratio of the number of experts with different evaluation quantity values, only setting 5 quantity values for simplifying the calculation process, and classifying the scoring results into more similar quantity value ratiosiThe first of the individual factorsjThe quantitative level appears in the proportion of expertsm ij (j =1,2,3,4,5; i =1,2,3) the available evaluation matrix is:
the item over-run probability magnitude calculation module 32 calculates item over-run probability magnitudes for different levels of magnitude units in the magnitude unitsP f ：
The item influence consequence value calculation module 33: according to the magnitude units output by the user terminal 1 and the evaluation magnitude values output by the client terminal 2, respectively calculating the item influence consequence magnitude values of the magnitude units of different levels in the magnitude unitsC f 。
The invention adopts a fuzzy analysis method to lead a plurality of expert scoring results output by different client terminals 2 to be brought into an evaluation matrix to be integrated, the integrated result is expressed by fuzzy number to calculate various possibility degrees of risks, the fuzziness in the evaluation is quantized, the fuzzy information is converted into determined decision information to obtain the value of the risk valueC f 。
Assuming a set of project completion influencing factorsB= { over-fill, drop index, item stop } = penB 1 ,B 2 ,B 3 And } weight set corresponding to each factorX=(X 1,X 2,X 3)，X 1+X 2+X 3=1, the specific weight may also be set by the expert depending on the actual situation of the equipment research project. Set of factorsBCorresponding evaluation setYMagnitude vector ofY=(Y 1,Y 2,Y 3,Y 4,Y 5) = (0,0.25,0.5,0.75,1), quantity value description as listed in table 5.
Referring to the evaluation criteria in the table 5, according to the characteristics of the equipment scientific research project, the expert scores the excess branch, the index reduction and the project termination in 3 aspects by combining the actual situation through the client terminal 2, and the higher the score is, the greater the influence degree on the project completion condition is represented. Then, the proportion of the experts with different grade of score is counted, only 5 grade of score are set for simplifying the calculation process, and the scoring result is classified into the proportion of more similar grade, theniThe first of the individual factorsjThe quantitative level appears in the proportion of expertsd ij (j =1,2,3,4,5; i =1,2,3), the evaluation matrix can be derived as
Estimating the influence of the project completion condition with strong ambiguity by adopting a fuzzy evaluation method to obtain a fuzzy comprehensive evaluation matrix of the influence degree of the project completion conditionEIs thatYIs to be read.
To pairEIs subjected to normalization processing to obtainE’=(e 1 ’,e 2 ’,e 3 ’,e 4 ’,e 5 ’). The item affects the outcome valueC f Is shown as
C f = E’·Y T =0d 1 ’+0.25d 2 ’+0.5d 3 ’+0.75d 4 ’+1d 5 ’
Item risk value calculation module 34: respectively calculating the item risk value of each unit in the magnitude units according to the output magnitude units and the evaluation values output by the client terminal 2F f . The project risks generally exist in equipment research projects, the complexity of the equipment and the uncertainty of internal and external conditions enable the research of the equipment research projects to have great risks, and the cost is changed to further act on final transaction expenses.
Cost risk value from the perspective of project risk definitionF f Is composed of
F f =1-P s C s =1-(1-P f )(1-C f )= P f +C f - P f C f
In the formula:P S representing the occurrence probability of budget non-exceeding;C S indicating the impact that the budget is not over-paid on the project.
Example 2
Based on the equipment scientific research project risk factor evaluation system, the invention provides an equipment scientific research project risk factor evaluation method, which comprises the following steps:
1) the user terminal 1 decomposes the equipment scientific research project to be evaluated into a plurality of quantity-level units, subdivides the project risk into a plurality of second-level risk factors, and sends the quantity-level units and the second-level risk factors of the equipment scientific research project to be evaluated to the server 3;
2) the server 3 sends the magnitude units and the secondary risk factors to the client terminals 2 with corresponding types according to the types of the secondary risk factors;
3) the client terminal 2 downloads the magnitude unit and the secondary risk factor from the server 3, gives an evaluation value to the secondary risk factor of the project, outputs the evaluation value and transmits the evaluation value to the server 3;
4) the server 3 receives the evaluation quantity values from the client terminal 2, respectively calculates the magnitude unit risk quantity values of different levels, and transmits the magnitude unit risk quantity values to the user terminal 1;
5) the user terminal 1 receives the risk value from the server 3, classifies the risk level, and outputs the evaluation result.
Taking a certain type of anti-mine system as an example, 30 experts are invited to participate in the demonstration of system risk through the client terminal 2, project personnel decompose the subsystem into six parts through the user terminal 1, wherein each subsystem can be decomposed into 3-6 subsystems, as shown in fig. 2. For privacy reasons, certain fuzzy processing is carried out on the data, but the credibility and the authenticity are not influenced.
The related system has more complex structure and longer space for one-by-one evaluation, and only the ship-borne comprehensive control systemAMedium anti-mine display control stationA 1A detailed evaluation is deployed.
1) Carrier-borne comprehensive control systemAProject overboost probability magnitude evaluation
Taking technical factors as an example, experts assign values to the secondary factor weights through the client terminal 2, and the method has the advantages of technical advancement (0.2), technical innovation (0.2), technical inheritance (0.3), technical complexity (0.1) and research unit condition (0.2). The ue 1 calculates the technical factor score =0.36 × 0.2+0.28 × 0.2+ 0.41 × 0.3+0.55 × 0.1+0.19 × 0.2=0.344 according to the scoring result of each secondary factor output by a certain ue 2, and the result is closer to the resultv 2=0.25, so the results are includedv 2The ratio of (a) to (b). Similarly, the user terminal 1 calculates evaluation values given by the three indexes.
The evaluation value sending and collecting module 31 obtains the excess probability value of
The project overstuffer probability magnitude calculation module 32 calculates the risk according to the risk output by the risk indicator module 12Index calculationA 1Technical, economic and progress scoring of modules
The project over-branch probability value is calculated by the project over-branch probability value calculation module 32A 1The plate hyper-branch probability magnitude is
2) Carrier-borne comprehensive control systemAImpact outcome assessment
The expert assigns the weights of the supplementary excess support, the reduction index and the project suspension influence degree through the client terminal 2, and the evaluation value sending and collecting module 31 obtains a weight set:
the project effect consequence value calculation module 33 calculates according to the criteria of table 5AScoring of modules
The fuzzy comprehensive judgment matrix of the risk influence degree calculated by the project influence consequence value calculation module 33 is
Is normalized to obtain
E’=(0.121, 0.219, 0.366, 0.219, 0.075)
The item influence consequence value calculation module 33 calculatesA 1The effect of the module on the project completion is
3) Risk grading of certain type anti-mine system
The project risk value calculation module 34 calculatesA 1Module cost risk value:
F f A 1= P f A1+ C f A1- P f A1 C f A1=0.263+0.477-0.263*0.477=0.615
by the same way, calculate to obtainF f A2=0.258、F f A3=0.314、F f A4= 0.764. Determining the influence degree of the subsystems A1, A2, A3 and A4 on the subsystem A by using an analytic hierarchy process, and further obtaining a weight vector
Q A =(q A1, q A2, q A3, q A4)=(0.40,0.20,0.15,0.25)
Hence subsystemAHas a risk value of
F f 1= F f A1 q A1+ F f A2 q A2+ F f A3 q A3+ F f A4 q A4=
0.615*0.40+0.258*0.20+0.314*0.15+0.764*0.25=0.5357
Similarly, the risk value calculation module 34 calculates risk values of other subsystemsF f B =0.8563、F f C =0.7837、F f D =0.3984、F f E =0.4197、F f F = 0.2958. Determining the influence degree of the sub-system B, C, D, E, F on the total system by using an analytic hierarchy process to obtain a weight vector
Q’=(Q A ,Q B ,Q C ,Q D ,Q E ,Q F )=(0.15,0.20,0.30,0.15,0.15,0.05,)
The weight of a certain type of anti-mine system can be arranged to obtain a figure 3, and the project risk value calculation module 34 calculates the total cost risk value of the system
F f ’ = F f A Q A +F f B Q B +…+ F f F Q F =0.62423<0.7
The risk level output module 13 receives the calculation result of the item risk value calculation module 34, and classifies the risk level because of 0.3<F f A1 <And 0.7, according to the equal risk curve, the anti-mine display and control system belongs to the medium risk level, and an evaluation result is output. The cost risk of the whole anti-mine system belongs to a medium and high level, the problem of the cost risk needs to be highly emphasized from the development and establishment stage, the development proportion in the project is reduced, or the project establishment is delayed, and the development is formally carried out after further pre-development results are obtained. Meanwhile, a higher incentive coefficient and a compensation scheme are set in the contract clause making link to encourage development of research units.
In order to promote scientific formation of prices of equipment scientific research projects, incentive constraint pricing contracts need to be designed according to the risks of the projects. The method starts from the definition of project risks, combines the characteristics of equipment scientific research projects, constructs a project risk factor evaluation system on the basis of project system structure decomposition, and carries out magnitude evaluation on the possibility of occurrence of the excess branches and the influence of project completion conditions. The method comprises the steps of establishing a cost overboost probability risk index with three dimensions of technology, economy and progress, carrying out internal and external analysis on the possibility of overboost occurrence, supplementing different influence consequences such as overboost supplement, overboost reduction index and project suspension, evaluating the influence of the cost overboost occurrence probability of each subsystem and the overall project completion condition, directly converting the grading of the risk size into the grading of the risk factor, further carrying out weighted calculation on the overall project score, and finally determining the overall cost risk level.
Finally, it should be noted that the above detailed description is only for illustrating the technical solution of the patent and not for limiting, although the patent is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the patent can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the patent, which should be covered by the claims of the patent.
Claims (10)
1. A risk factor evaluation system for equipment scientific research projects is characterized in that: the system comprises a server (3), at least one user terminal (1) and at least one client terminal (2);
the user terminal (1): the system is used for decomposing equipment scientific research projects to be evaluated into a plurality of quantity-level units, subdividing project risks into a plurality of secondary risk factors, sending the quantity-level units and the secondary risk factors of the equipment scientific research projects to be evaluated to the server (3), receiving the risk quantity values from the server (3), dividing risk grades and outputting evaluation results;
the client terminal (2): the system is used for downloading the magnitude unit and the secondary risk factor from the server (3), giving an evaluation value to the secondary risk factor of the project, outputting the evaluation value and transmitting the evaluation value to the server (3);
the server (3): the server (3) is used for sending the magnitude units and the secondary risk factors to the client terminal (2), the secondary risk factors are of different types, and the server is used for sending the magnitude units and the secondary risk factors to the client terminal (2) of the corresponding type according to the type of the secondary risk factors; and the server (3) receives the evaluation values from the client terminal (2), respectively calculates the magnitude unit risk values of different levels, and transmits the magnitude unit risk values to the user terminal (1).
2. The equipment scientific research project risk factor evaluation system of claim 1, wherein: the user terminal (1) comprises a system decomposition module (11), a risk index module (12) and a risk grade output module (13);
the system decomposition module: longitudinally decomposing equipment scientific research projects based on WBS technology to form magnitude units;
the risk indicator module (12): decomposing the scientific research project of the equipment to be evaluated into a plurality of secondary risk factors from two dimensions of project over-branch probability risk and influence consequence risk, wherein each secondary risk factor has a specified professional type and is used for matching with a client terminal (2) of a corresponding type;
the risk level output module (13): and matching the risk value of the magnitude unit output by the server (3) with a set risk curve to obtain a corresponding risk level and a corresponding measure, and outputting an evaluation result.
3. The equipment scientific research project risk factor evaluation system of claim 1, wherein: the evaluation value of the secondary risk factor of the project, which is given to the project risk by the client terminal (2), is a weighted value of the action degree of the secondary factor on each project influence factor, and the higher the score is, the greater the risk is represented.
4. The equipment scientific research project risk factor evaluation system of claim 1, wherein: the server (3) comprises an evaluation quantity value sending and collecting module (31), a project excess probability quantity value calculating module (32), a project influence consequence quantity value calculating module (33) and a project risk quantity value calculating module (34);
the evaluation quantity value sending and collecting module (31): sending the magnitude unit and the secondary risk factor output by the user terminal (1) to the client terminal (2) of the corresponding type;
the item hyper-Branch probability magnitude calculationModule (32): respectively calculating the item over-support probability quantity values of the magnitude units of different levels in the magnitude units according to the magnitude units output by the user terminal (1) and the evaluation quantity values output by the client terminal (2)P f ；
The item impact outcome magnitude calculation module (33): according to the magnitude units output by the user terminal (1) and the evaluation magnitude values output by the client terminal (2), respectively calculating the item influence consequence magnitude values of the magnitude units of different levels in the magnitude unitsC f ；
The project risk magnitude calculation module (34): according to the output magnitude units and the evaluation magnitudes output by the client terminal (2), respectively calculating the item risk magnitudes of the magnitude units of different levels in the magnitude unitsF f 。
5. The equipment scientific research project risk factor assessment system of claim 4, wherein: the item over-run probability magnitudeP f The calculation method comprises the following steps:
in the formula (I), the compound is shown in the specification,W i is shown asiThe probability of occurrence of an item over-run of a factor,m ij is shown asiThe first of the individual factorsjThe proportion of the magnitude unit that appears,V j the evaluation quantity value is represented by the value,Wrepresents a set of hyper-branch occurrence probability weights,Ma probability evaluation matrix of the exceeding branch of the item is represented,Vand (4) representing an item over-branch probability evaluation value vector, wherein T is a transposed symbol.
6. The equipment scientific research project risk factor assessment system of claim 4, wherein: said item impact outcome measureC f The calculation method comprises the following steps:
in the formula (I), the compound is shown in the specification,E’representing the fuzzy comprehensive evaluation matrix after the normalization processing,Yrepresenting the term impact consequence magnitude vector, T is the transposed symbol.
7. The equipment scientific research project risk factor assessment system of claim 4, wherein: the item risk valueF f The calculation method comprises the following steps:
F f =1-P s C s =1-(1-P f )(1-C f )= P f +C f - P f C f
in the formula:P s representing the occurrence probability of budget non-exceeding;C s indicating the effect of not exceeding the budget on the project.
8. The system for risk factor assessment of equipment research projects according to claim 3, wherein: the types of the secondary risk factors comprise technical factors, economic factors, progress factors and influence consequence factors, wherein the technical factors comprise technical advancement, technical innovation, technical inheritance, technical complexity and research unit conditions, the economic factors comprise national economic conditions and currency expansion rate, international situation conditions and exchange rate change conditions, domestic policy guidance, industrial environment conditions and product supply and demand relationships, and the progress factors comprise subsystem progress and project overall progress; the factors influencing the consequence comprise the supplement of the overbooking, the reduction of indexes and the termination of projects.
9. A risk factor evaluation method for equipment scientific research projects is realized based on an equipment scientific research project risk factor evaluation system, the system comprises a server (3), at least one user terminal (1) and at least one client terminal (2), and the method comprises the following steps:
1) the user terminal (1) decomposes the equipment scientific research project to be evaluated into a plurality of quantitative units, subdivides the project risk into a plurality of secondary risk factors, and sends the quantitative units and the secondary risk factors of the equipment scientific research project to be evaluated to the server (3);
2) the server (3) sends the magnitude units and the secondary risk factors to the client terminals (2) with corresponding types according to the types of the secondary risk factors;
3) the client terminal (2) downloads the magnitude unit and the secondary risk factor from the server (3), gives an evaluation value to the secondary risk factor of the project, outputs the evaluation value and transmits the evaluation value to the server (3);
4) the server (3) receives the evaluation quantity values from the client terminal (2), respectively calculates the magnitude unit risk quantity values of different levels, and transmits the magnitude unit risk quantity values to the user terminal (1);
5) the user terminal (1) receives the risk value from the server (3), divides the risk level and outputs an evaluation result.
10. The equipment scientific research project risk factor assessment method of claim 9, wherein: the server (3) distributes the magnitude units and the secondary risk factors to corresponding client terminals (2) according to a list sequence stored in advance, sets task time limit, and evaluates that a user sends a receiving confirmation instruction to the server (3) through the client terminals (2); if the server (3) does not receive the receiving confirmation instruction within the appointed time, the receiving confirmation instruction is sent to the next corresponding client terminal (2) in the list, and if the alternative client terminal (2) in the list is 0, the distributing failure instruction and the request delay instruction are sent to the user terminal (1).
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