CN114693193A - Equipment scientific research project risk factor evaluation system and method - Google Patents

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

A system and method for evaluating risk factors of equipment scientific research projects

technical field

The invention relates to the technical field of risk assessment of equipment scientific research projects, in particular to a risk factor assessment system and method for equipment scientific research projects.

Background technique

Equipment scientific research projects have great uncertainty and high costs, and all kinds of risks in the development will be transmitted in a chain, which will eventually affect the military and the research institutes. Convert various risks in the process of project development into quantifiable overspending limits, identify the main factors and conditions that affect project risks, and use qualitative and quantitative analysis methods according to their characteristics to measure the probability of project risks occurring And the impact degree, calculate the potential risk of the subsystem, and finally determine the overall risk level of the project, which can provide a basis for the design of incentive constraints and cost compensation schemes.

The current research in the field of expense risk mainly focuses on the application of simulation method. In terms of cost risk estimation of construction project cost, some scholars proposed to use methods such as Monte Carlo simulation and sensitivity analysis to identify and analyze the risks of time and cost in construction projects, and find out the cost variance to guide project decision-making; Wang Yinglei et al. A joint risk estimation model of project schedule and cost was established, and the risk probability distribution under the schedule cost combination was obtained by statistical analysis of the simulation results; Yang Baosen et al. It is believed that the serial iteration is the main reason for the right-biased tendency and positive correlation of the construction period cost distribution. In terms of estimating the R&D cost of equipment scientific research projects, Bielecki used logistic regression to predict whether the R&D cost would increase, and used a multiple regression model for the increasing scientific research projects to predict the cost increase; Xu Zhe et al. proposed a joint risk probability estimation method. Statistical analysis and regression analysis were carried out on the Monte Carlo simulation output results to realize the risk estimation of the inability to complete the scientific research project plan under the joint constraints of cost and schedule; Wei Dongtao et al. The accuracy of cost prediction can reduce the impact of cost changes in the actual development process; Xu Jihui et al. proposed an improved Monte Carlo method based on risk-driven theory to deal with the risk modeling of aircraft development costs, and conducted a study on the rationality and effectiveness of the improved method. He Ming et al. proposed to build a large-scale scientific research project cost risk prediction model based on gray correlation degree, which can better solve the problem of similar project selection, total project cost and cost estimation of each period, and cost fluctuation prediction.

The deficiencies of the above researches and technologies are mainly reflected in: (1) The research on project risk focuses on using simulation method to give quantitative analysis results, and does not pay attention to the analysis of risk-related influencing factors. The lack of identification of risk sources makes the results difficult. The parameters required for verification and simulation also rely more on subjective judgments; ② Most of the research only defines the consequences of project development as two situations of success or failure, and simply identifies the probability of cost overrun as cost risk, and there is insufficient research on impact consequences; ③ Projects Risk involves multiple disciplines such as technology, economics, project management, etc. It is difficult for an expert to have multiple interdisciplinary backgrounds and give accurate scores at the same time, and the accuracy of expert scores directly affects the validity of evaluation results. The key factor of scoring accuracy, existing evaluation methods lack relevant technical solutions that can adapt expert technical fields to risk factors.

SUMMARY OF THE INVENTION

The purpose of the present invention is to overcome the deficiencies of the prior art, and propose a risk factor evaluation system and method for equipment scientific research projects. The designated object corresponding to the technical matching degree is evaluated and assigned, and the information technology is used to improve the management efficiency and result effectiveness of the risk factor evaluation of equipment scientific research projects.

To achieve the above objects, the system designed by the present invention includes a server, at least one user terminal and at least one client terminal;

The user terminal: used to decompose the equipment scientific research project to be evaluated into several magnitude units, subdivide the project risk into several secondary risk factors, and divide the magnitude units and secondary risk factors of the equipment scientific research project to be evaluated. Send to the server, receive the risk value from the server, divide the risk level, and output the evaluation result;

The client terminal: used to download the magnitude unit and the secondary risk factor from the server, assign an evaluation value to the secondary risk factor of the project, and output the evaluation value and transmit it to the server;

The server: used to send the magnitude unit and the secondary risk factor to the client terminal, the secondary risk factor has different types, and the server sends to the client terminal with the corresponding type according to the type of the secondary risk factor; The server receives the evaluation value from the client terminal, calculates the risk value of the unit of magnitude at different levels, and transmits it to the user terminal.

Further, the user terminal includes a system decomposition module, a risk index module, and a risk level output module;

The system decomposition module: based on the WBS technology, the equipment scientific research projects are longitudinally decomposed to form units of magnitude;

The risk index module: decomposes the equipment scientific research project to be evaluated into several secondary risk factors from the two dimensions of project overrun probability risk and impact consequence risk, and each secondary risk factor has a designated professional type to match the corresponding type of risk factor. client terminal;

The risk level output module: matches the risk magnitude of the magnitude unit output by the server with the set risk curve, obtains the corresponding risk level and countermeasures, and outputs the evaluation result.

Further, the evaluation value assigned by the client terminal to the project risk by the secondary risk factor of the project is the weight value of the effect degree of the secondary factor on the influencing factors of each project, and the higher the score, the greater the risk.

Further, the server includes an evaluation value sending and collecting module, a project overrun probability value calculation module, a project impact consequence value calculation module, and a project risk value calculation module;

The evaluation value sending and collecting module: sending the magnitude unit and the secondary risk factor output by the user terminal to the corresponding type of client terminal;

The project overrun probability magnitude calculation module: according to the magnitude unit output by the user terminal and the evaluation magnitude output by the client terminal, respectively calculate the project overrun probability magnitude P _f of the magnitude units of different levels in the magnitude unit;

Described project influence consequence magnitude calculation module: according to the magnitude unit output by the user terminal and the evaluation magnitude output by the client terminal, respectively calculate the item influence consequence magnitude C _f of the magnitude units of different levels in the magnitude unit;

The project risk value calculation module: according to the output magnitude unit and the evaluation value output by the client terminal, respectively calculate the project risk value F _f of the magnitude units at different levels in the magnitude unit.

Further, the calculation method of the project overrun probability value P _f is:

In the formula, Wi represents the probability of project overrun of the ith factor, m _ij represents the proportion of the jth _{unit of magnitude of the ith factor, V j} represents the _evaluation value, W represents the weight set of the probability of overrun, M Represents the project overrun probability evaluation matrix, V represents the project overrun probability evaluation value vector, and T is the transpose symbol.

Further, the calculation method of the project impact consequence value C _f is:

C _f = E' · Y ^T

In the formula, E' represents the fuzzy comprehensive evaluation matrix after normalization, Y represents the magnitude vector of project impact consequences, and T represents the transpose symbol.

Further, the calculation method of the project risk value F _f is:

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 probability of budget overruns; Cs represents the impact of budget overruns on the project.

Further, the types of the secondary risk factors include technical factors, economic factors, progress factors and impact and consequence factors, wherein the technical factors include technological advancement, technological innovation, technological inheritance, technological complexity, and the situation of the research unit. , economic factors include national economic situation and inflation rate, international situation and exchange rate changes, domestic policy orientation, industry environment, product supply and demand relationship, progress factors include subsystem progress, overall project progress; Decrease the target and stop the project.

The present invention also provides a risk factor evaluation method for equipment scientific research projects. The method is implemented based on a risk factor evaluation system for equipment scientific research projects, and includes the following steps:

1) The user terminal decomposes the equipment scientific research project to be evaluated into several magnitude units, subdivides the project risk into several secondary risk factors, and sends the magnitude unit and secondary risk factors of the equipment scientific research project to be evaluated to the server ;

2) The server sends the magnitude unit and the second-level risk factor to the client terminal with the corresponding type according to the type of the second-level risk factor;

3) The client terminal downloads the magnitude unit and the secondary risk factor from the server, assigns the evaluation value to the secondary risk factor of the project, and transmits the output evaluation value to the server;

4) The server receives the evaluation value from the client terminal, calculates the magnitude unit risk value of different levels, and transmits it to the user terminal;

5) The user terminal receives the risk value from the server, divides the risk level, and outputs the evaluation result.

Preferably, the server distributes the order of magnitude units and secondary risk factors to the corresponding client terminals according to the pre-stored list sequence, and sets the task period, and the evaluation user sends the confirmation reception instruction to the server through the client terminal; If the confirmation reception instruction is not received, it is sent to the next corresponding client terminal in the list. If the candidate client terminal in the list is 0, the allocation failure instruction and the request for extension instruction are sent to the user terminal.

The beneficial effects of the risk factor evaluation system for equipment scientific research projects proposed by the present invention are:

1. The present invention identifies influencing factors based on WBS, introduces the concept of risk factors, and adopts a combination of qualitative and quantitative risk assessment methods for the characteristics of project risk data that are difficult to accurately measure;

2. The present invention converts the direct assessment of risk size into the assessment of risk factors, sends the risk factors to designated objects with corresponding technical matching degrees for evaluation and assignment, and uses information technology to improve the management of risk factor assessment of equipment scientific research projects. Efficiency and Results Effectiveness

3. The present invention conducts quantitative evaluation on the possibility of overruns and the impact of project completion; analyzes the probability of cost overruns from the perspectives of technology, economy, and progress, and conducts internal and external analysis on the possibility of overruns; The impact and consequences of the completion of the project, supplementary overruns, reduction of indicators, project suspension, etc.;

4. The present invention confirms the risk level step by step by means of the iso-risk curve, obtains the subsystem risk value in turn, and weights the subsystem risk value to obtain the overall risk value of the project, which provides a reference for the design of the incentive constraint coefficient;

5. The present invention utilizes the information technology to improve the management efficiency and result effectiveness of the risk factor evaluation of equipment scientific research projects through the information interaction between the client terminal, the user terminal and the server.

Description of drawings

FIG. 1 is a structural block diagram of a risk factor evaluation system for equipment scientific research projects according to the present invention.

FIG. 2 is a schematic exploded view of a certain type of anti-mine system in Example 2. FIG.

FIG. 3 shows the weight of a certain type of anti-mine system in Example 2.

Detailed ways

The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

The system structure of equipment scientific research projects is complex, including subsystems, subsystems, components and assemblies. WBS technology is a common practice of project management and a modern management method adapted to the construction of major engineering projects. Use WBS technology to carry out quantitative risk analysis of equipment scientific research project costs, and systematically decompose equipment scientific research projects step by step and item by item according to the characteristics of the task package, which can clearly display the investment direction and amount of equipment scientific research funds, and intuitively and effectively distinguish major risks. In order to establish the cost risk index system and complete the pre-process of the cost risk assessment of equipment scientific research projects.

The traditional risk assessment system for equipment scientific research projects uses software to directly simulate the original project assessment mode, aiming to improve the communication efficiency of personnel and the management efficiency of affairs by using information technology. With the continuous development of information technology and the continuous improvement of software and hardware performance, a new generation of engineering project management systems will be constructed on the basis of new technologies represented by cloud computing, mobile Internet, Internet of Things, artificial intelligence, etc. Affect existing project risk assessment management models and mechanisms.

Example 1

As shown in FIG. 1 , a risk factor evaluation system for equipment scientific research projects proposed by the present invention includes a server 3 , at least one user terminal 1 and at least one client terminal 2 . In this system, the user terminal 1 is used by project managers to create scientific research projects to be evaluated, decompose the magnitude units of the projects, determine secondary risk factors, divide risk levels according to risk magnitudes, and output evaluation results. The user terminal 2 is used by the project expert as the evaluation user, and is used for assigning the evaluation value to the secondary risk factor of the project, and the server 3 is used for data transmission and calculation.

The user terminal 1 includes a system decomposition module 11 , a risk indicator module 12 , and a risk level output module 13 . System decomposition module 11: Based on the WBS technology, the equipment scientific research projects are decomposed vertically to form units of magnitude; risk index module 12: The equipment scientific research projects to be evaluated are decomposed into several two dimensions from the two dimensions of project overrun probability risk and impact consequence risk. Each secondary risk factor has a designated professional type to match the corresponding type of client terminal 2; the risk level output module 13: matches the risk value of the magnitude unit output by the server 3 with the set risk curve , get the corresponding risk level and countermeasures, and output the evaluation results.

The system decomposition module 11 uses the WBS technology to decompose into multiple units of magnitude layer by layer to form a task organization form of tree structure. In the information management system of risk factor assessment of equipment scientific research projects, the equipment scientific research projects are decomposed vertically according to the unit of magnitude, and the decomposition process is in-depth and progressive layer by layer until the granularity of the work unit level is no longer suitable for subdivision. The decomposition particle size is usually dominated by the first three levels, and the first three levels are solidified from the top layer, and then decomposed layer by layer to form sub-systems, subsystems, and work units, forming a unit system of magnitude subordinate to the entire system. Based on this, risk decomposition is carried out, the risk value of each magnitude unit is calculated, and a multi-level structure system in which the risk value corresponds to the content of scientific research work is formed. Each level of the division is regarded as a total system component with independent attributes, and is clearly defined in the evaluation index.

The risk index module 12 constructs a cost risk index system from two levels of overrun probability and impact degree on the basis of project system decomposition and according to the definition of project risk.

Overrun probability risk indicators include technical factors, economic factors and progress factors.

In terms of technical factors, first of all, it is necessary to predict the advancement of the technology required by the project, which is closely related to the tactical technical indicators. Relationship. If the target function cannot be achieved by relying on the existing technology, it is necessary to develop new technologies and invest a lot of R&D costs and labor costs to achieve breakthroughs in key technologies; if the existing technology can meet the needs of the target, the The degree of technical relevance and whether material or process adjustments need to be made to accommodate the new project system. At the same time, it is necessary to pay attention to the complexity of the technology, and whether multiple technologies of different types can be applied to the system at the same time can meet the needs. In addition, the qualifications of the personnel, working environment, organizational structure and reputation of the research unit will also affect the realization level of the technology in the project, and the cost of passing through the period and equipment loss are reflected in the cost. The secondary factors and evaluation basis of the technical factors proposed in this embodiment are shown in Table 1.

In terms of economic factors, changes in procurement costs are mainly caused by external environments such as macroeconomics, market industries, and microeconomics. Among them, the inflation rate, price increase rate and currency depreciation rate in the national economy will directly affect the changes in the cost of project development and procurement; the reconstruction of the international structure and the adjustment of state relations will drive the rise and fall of the international exchange rate, and the currency required for import and export will rise and fall. Exchange is an important factor affecting the cost of some components that cannot yet be localized; at the same time, the state can indirectly reflect the reduction or exemption of taxes related to the research and development of research units, increase the localization of supporting equipment, and encourage outsourcing units to improve the level of service guarantee. at the transaction price. In addition, the number of capable R&D units in the industry is related to the procurement method. For example, there is only one capable R&D unit. The military has to implement single-source procurement. The price deviates from the actual cost and tilts in its own favor. In the market environment, supply and demand determine the price. Once the military's demand exceeds the normal level that can be supplied by the research institute, the military is in a weak position in the dynamic game between supply and demand, and the military has to pay more to satisfy the research institute. requirements. The secondary factors and evaluation basis of the economic factors proposed in this embodiment are shown in Table 2.

In terms of progress factor, the system structure is decomposed before the project starts to develop, and the progress plan is formulated according to the construction period of the overall project and each sub-project to ensure that the project activities can be pushed forward according to the plan. The use of the network plan chart can clearly reflect the progress of the project at each stage, the amount of various resources required, expenses, and the key activities and key routes of the entire project. Achieving the desired goal of completing the project with the least amount of time and resources. If the preliminary schedule of a certain subsystem is unreasonable, it may affect the development of other related subsystems, and cause the overall project process to be interrupted in the actual development process; the matching of the subsystem schedule with the overall project schedule is also crucial, and only reasonable implementation can be achieved. Only the configuration can find the optimal solution through the critical path. Once the project is delayed or even interrupted, it will cause a chain effect of increased costs, resulting in additional delay costs such as employee compensation, production equipment operation, and liquidated damages. The secondary factors and evaluation basis of the progress factor proposed in this embodiment are shown in Table 3.

Impact Consequence Risk Indicator:

In practice, the consequences of cost overruns are not only two states of development success and failure, but also include overruns, reductions in targets, and project suspension.

Supplementary overrun refers to the need to organize technical research, technical coordination and related tests due to the high difficulty of technical research, changes in economic conditions or delays in the construction period. Existing actual expenditures are too costly and exceed the pre-determined budgetary limit. At this time, only by adding manpower, material and financial resources to make up for the overspending caused by the increase in cost, can the project achieve the expected development requirements.

Decreased indicators refer to the fact that within a predictable time limit, the expected requirements cannot be met by delaying the progress and additional funds, and the performance can only be reduced. It is difficult to overcome the technical bottleneck by virtue of the existing R&D conditions such as production technology, equipment and facilities, or the imported components are difficult to obtain due to the influence of the international political situation. The original technical requirements cannot be achieved, and the project development can only be completed by reducing the performance indicators.

Project suspension refers to the fact that the technical difficulty of tackling key problems is too high, the expected capital chain supply is insufficient, the development project cannot be completed within the specified time, the delay of progress, and excessive additional funds make it meaningless to continue the development of the project; or the finished product developed under the existing conditions The cost-effectiveness ratio of function realization is too low, and new and lower-cost alternatives have emerged, so the project can only be suspended to evaluate whether it has the value of continuing development.

Risk level output module 13: Match the risk magnitude of the magnitude unit output by the server 3 with the set risk curve by means of the iso-risk curve, obtain the risk level of the entire project and form a risk assessment result. The project risk is divided into low risk, medium risk and high risk, and the project risk level of the equipment scientific research project is determined. It is generally believed that F _f <0.3 is a low risk, which has little impact on the equipment development plan objectives, and there are few phenomena of performance degradation, increased procurement cost, and progress interruption; between 0.3 < F _f < 0.7 is medium Risk, affecting the equipment development plan objectives, resulting in a certain performance decline and an increase in the procurement cost; F _f >0.7 is a high risk, the probability of risk occurrence is very high, and it has a significant impact on the equipment development plan objectives, resulting in obvious performance decline, Increased procurement costs and schedule disruptions.

The evaluation value given to the project risk by the secondary risk factor of the project by the client terminal 2 is the weight value of the effect degree of the secondary factor on the influencing factors of each project. Client terminal 2 is used by experts in technical fields, economic cost experts and progress analysis experts. As experts in different technical fields, they will score the secondary risk factors corresponding to the technical fields in the project in the range of [0, 1]. The higher the score, the higher the score. The greater the risk, the scores are V _{1 j} , V _{2 j} , V _{3 i} , (j=1,2,3,4,5;i=1,2,3).

The server 3 includes an evaluation value sending and collecting module 31 , a project overrun probability value calculation module 32 , a project impact consequence value calculation module 33 , and a project risk value calculation module 34 . The evaluation value sending and collecting module 31 : sending the magnitude unit and the secondary risk factor output by the user terminal 1 to the corresponding type of the client terminal 2 .

The evaluation magnitude sending and collecting module 31 sends 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 value sending and collecting module 31 distributes the magnitude unit and the secondary risk factor to the corresponding client terminal 2 according to the pre-stored list sequence, and sets the task period, and the evaluation user sends the confirmation reception instruction to the server 3 through the client terminal 2; if If the server 3 does not receive the confirmation reception instruction within the specified time, it will send it to the next corresponding client terminal 2 in the list.

Item overrun probability value calculation module 32: According to the magnitude unit output by the user terminal 1 and the evaluation value output by the client terminal 2, respectively calculate the item overrun probability value P _f of the magnitude unit at different levels in the magnitude unit.

The probability of expense risk is mainly affected by technology dependency, change range of procurement cost and schedule cycle arrangement. Therefore, set the factor set A = {technology, economy, progress}={ A ₁ , A ₂ , A ₃ } for the probability of overruns, and assign different weights according to the degree of effect of each influencing factor in the type of equipment scientific research project. The value is set by experts according to the actual situation of the project. It is assumed that the weight set corresponding to each factor W = { W ₁ , W ₂ , W ₃ }, W ₁ +W ₂ +W ₃ =1.

The influencing factor set can be further subdivided according to the secondary factor indicators: A ₁ = {technological advancement, technological innovation, technological inheritance, technological complexity, and the situation of the research unit}={ a ₁₁ , a ₁₂ , a ₁₃ , a ₁₄ , a ₁₅ }, A ₂ = {national economic situation, international situation, domestic policy orientation, industry environment changes, product supply and demand}={ a ₂₁ , a ₂₂ , a ₂₃ , a ₂₄ , a ₂₅ }, A ₃ ={subsystem progress, overall project progress}={ a ₃₁ , a ₃₂ }. Each secondary factor weight W _ij is set according to the degree of importance, satisfying ∑ W _{1 j} =1, ∑ W _{2 j} =1, ∑ W _{3 i} =1, (j=1,2,3,4,5; i=1,2,3).

The project overrun probability value calculation module 32 receives the evaluation value assigned to the project risk by the secondary risk factor of the project sent by the client terminal 2, and builds an expert group through the weighting method on the basis of the expert's evaluation result of the overrun probability occurrence probability. The results of the joint evaluation, weighted calculation to obtain the technical indicators, economic indicators, progress indicators.

The evaluation set V corresponding to the factor set A is assigned the magnitude vector V =( V ₁ , V ₂ , V ₃ , V ₄ , V ₅ ) =(0,0.25,0.5,0.75,1), and the evaluation set V is set according to the index system A description of the magnitudes is shown in Table 4.

Each evaluation value v _i corresponds to the corresponding evaluation value V _j , and the proportion of experts with different evaluation values is counted. In order to simplify the calculation process, only 5 values are set, and the scoring results are classified as relatively similar value ratios , then the proportion of experts in the jth order of the ith factor is m _ij , (j=1,2,3,4,5;i=1,2,3), the evaluation matrix can be obtained as:

The project overrun probability magnitude calculation module 32 calculates the project overrun probability magnitude P _f of the magnitude units at different levels in the magnitude unit:

Item impact consequence value calculation module 33: According to the magnitude unit output by the user terminal 1 and the evaluation value output by the client terminal 2, respectively calculate the project impact consequence value C _f of the magnitude units at different levels in the magnitude unit.

The present invention adopts the fuzzy analysis method, so that multiple expert scoring results output by different client terminals 2 are brought into the evaluation matrix and integrated together. The fuzziness of C is quantified, and this fuzzy information is transformed into definite decision-making information to obtain the risk value C _f .

Assuming that the set of factors affecting the completion of the project B = {supplement overruns, reduce indicators, project suspension}={ B ₁ , B ₂ , B ₃ }, the weight set corresponding to each factor X= ( X ₁ , X ₂ , X ₃ ), X ₁ + X ₂ + X ₃ =1, the specific weight can also be set by experts according to the actual situation of equipment scientific research projects. The magnitude vector Y= ( Y ₁ , Y ₂ , Y ₃ , Y ₄ , Y ₅ )=(0,0.25,0.5,0.75,1) of the evaluation set Y corresponding to the factor set B , and the magnitudes are described in Table 5. List.

Referring to the evaluation criteria in Table 5, and according to the characteristics of equipment scientific research projects, experts scored through the client terminal 2 based on the actual situation from three aspects: supplementing overruns, reducing indicators, and project suspension. The higher the score, the greater the impact on the completion of the project. Then, the proportion of experts with different score levels is counted. In order to simplify the calculation process, only 5 score levels are set, and the scoring results are classified as a relatively similar magnitude ratio, then the jth level of the i -th factor appears. The expert ratio of is d _ij (j=1,2,3,4,5; i=1,2,3), the evaluation matrix can be obtained as

The fuzzy evaluation method is used to estimate the impact of the project completion situation with strong ambiguity, and the fuzzy comprehensive evaluation matrix E of the impact degree of the project completion situation is obtained, which is a fuzzy subset on Y.

Normalize E to get E' = ( e ₁ ' , e ₂ ' , e ₃ ' , e ₄ ' , e ₅ ' ). Then the project impact consequence value C _f is expressed as

C _f = E' · Y ^T = 0 d ₁ '+ 0 .25d ₂ '+ 0 .5d ₃ '+ 0.75 d ₄ '+ 1 d ₅ '

The project risk value calculation module 34 : calculates the project risk value F _f of each unit in the magnitude unit according to the output magnitude unit and the evaluation value output by the client terminal 2 . Project risks generally exist in equipment development projects. The complexity of equipment and the uncertainty of internal and external conditions make the development of equipment scientific research projects with great risks, causing changes in costs and affecting final transaction costs.

From the perspective of project risk definition, the cost risk value F _f is

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 represents the probability of budget overruns; C _S represents the impact of budget overruns on the project.

Example 2

Based on the above-mentioned risk factor evaluation system for equipment scientific research projects, the present invention proposes a risk factor evaluation method for equipment scientific research projects, including the following steps:

1) User terminal 1 decomposes the equipment scientific research project to be evaluated into several magnitude units, subdivides the project risk into several secondary risk factors, and sends the magnitude unit and secondary risk factors of the equipment scientific research project to be evaluated to server 3;

2) The server 3 sends the magnitude unit and the secondary risk factor to the client terminal 2 with the corresponding type according to the type of the secondary risk factor;

3) The client terminal 2 downloads the magnitude unit and the secondary risk factor from the server 3, assigns an evaluation value to the secondary risk factor of the project, and transmits the output evaluation value to the server 3;

4) The server 3 receives the evaluation value from the client terminal 2, respectively calculates the magnitude unit risk value of different levels, and transmits it to the user terminal 1;

5) The user terminal 1 receives the risk value from the server 3, divides the risk level, and outputs the evaluation result.

Taking a certain type of anti-mine system as an example, 30 experts were invited to participate in the demonstration of system risks through the client terminal 2. The project personnel decomposed the sub-system into six parts through the user terminal 1, and each sub-system can be decomposed into 3- 6 subsystems, as shown in Figure 2. Due to confidentiality reasons, the data has been blurred to a certain extent, but it does not affect the credibility and authenticity.

Because the system structure involved is relatively complex, and the length of each evaluation is long, only the detailed evaluation of the anti-mine display console A ₁ in the shipboard integrated control system A is carried out.

1) Evaluation of overrun probability value of shipboard integrated control system A project

Taking the technical factor as an example, the expert assigns the weight of the secondary factor through the client terminal 2, the technological advancement (0.2), the technological innovation (0.2), the technological inheritance (0.3), the technological complexity (0.1), the research unit situation (0.2). The user terminal 1 calculates the technical factor score according to the scoring results of each secondary factor output by a certain client terminal 2 = 0.36*0.2+0.28*0.2 +0.41*0.3+0.55*0.1+0.19*0.2=0.344, the result is closer to v ₂ =0.25, so this result is included in the proportion of v ₂ . Similarly, the user terminal 1 calculates and obtains the evaluation value given by the three indicators.

The overrun probability value obtained by the evaluation value sending and collecting module 31 is:

The project overrun probability value calculation module 32 calculates the technical, economic and progress scores _of the A1 module according to the risk index output by the risk index module 12.

The project overrun probability magnitude calculation module 32 calculates the overrun probability magnitude value _of the A1 plate.

2) Impact and consequence assessment of shipboard integrated control system A

Through the client terminal 2, the expert assigns a value to the weights of overspending, reduction indicators, and the impact degree of project suspension, and the evaluation value sending and collecting module 31 obtains the weight set:

The project impact consequence value calculation module 33 calculates the score of the A module according to the evaluation criteria in Table 5.

The fuzzy comprehensive evaluation matrix for calculating the risk impact degree by the project impact consequence value calculation module 33 is:

normalized to get

E' =(0.121, 0.219, 0.366, 0.219, 0.075)

The project impact consequence value calculation module 33 calculates that the impact _of the A1 module on the project completion is:

3) Risk classification of a certain type of anti-mine system

_The project risk value calculation module 34 calculates the A1 module cost risk value:

F _f ^{A 1} = P _f ^{A 1} + C _f ^{A 1} - P _f ^{A 1} C _f ^{A 1} =0.263+0.477-0.263*0.477=0.615

Similarly, F _f ^{A 2} =0.258, F _f ^{A 3} =0.314, and F _f ^{A 4} =0.764 are calculated. Use the analytic hierarchy process to determine the degree of influence of subsystems A1, A2, A3, and A4 on subsystem A, and then obtain the weight vector

Q ^A =( q ^{A 1} , q ^{A 2} , q ^{A 3} , q ^{A 4} )=(0.40,0.20,0.15,0.25)

Therefore, the risk value of subsystem A is

F _f ¹ = F _f ^{A 1} q ^{A 1} + F _f ^{A 2} q ^{A 2} + F _f ^{A 3} q ^{A 3} + F _f ^{A 4} q ^{A 4} =

0.615*0.40+0.258*0.20+0.314*0.15+0.764*0.25=0.5357

Similarly, the project risk value calculation module 34 calculates the risk values of other sub-systems F _f ^B =0.8563, F _f ^C =0.7837, F _f ^D =0.3984, F _f ^E =0.4197, F _f ^F =0.2958 . Use the analytic hierarchy process to determine the degree of influence of the sub-systems B, C, D, E, and F on the overall system, and then obtain the 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,)

Figure 3 can be obtained by sorting out the weights of a certain type of anti-mine system. 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 project risk value calculation module 34, and divides the risk level. Because 0.3< F _f ^A1 <0.7, according to the iso-risk curve, it can be known that the anti-mine display and control system belongs to the medium risk level, and outputs the evaluation result. The cost risk of the entire anti-mine system is at a medium to high level. It is necessary to attach great importance to the cost risk issue from the research and development stage, or reduce the research and development ratio in the project, or postpone the project establishment until further pre-research results are released. to develop. At the same time, a higher incentive coefficient and compensation plan are set up in the link of contract terms to encourage research units to develop.

In order to promote the scientific formation of the price of equipment scientific research projects, it is necessary to design incentive-constrained pricing contracts according to the size of the project risk. The invention starts from the definition of project risk, combines the characteristics of equipment scientific research projects, and builds a project risk factor evaluation system on the basis of the decomposition of the project system structure, so as to carry out quantitative evaluation on the possibility of overspending and the impact of project completion. . Establish cost overrun probability risk indicators in the three dimensions of technology, economy, and schedule, conduct internal and external analysis of the possibility of overruns, supplement different impact consequences such as overruns, reduction indicators, project suspension, etc., through the cost overrun probability of each subsystem It evaluates the impact of the overall completion of the project, converts the direct risk score into the risk factor score, and then calculates the overall project score by weighting, and finally determines the overall cost risk level.

Finally, it should be noted that the above specific embodiments are only used to illustrate the technical solution of the patent and not to limit it. Although the patent has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solution of the patent can be Modifications or equivalent substitutions are made without departing from the spirit and scope of the technical solutions of this patent, and they should all be covered by the scope of the claims of this patent.

Claims (10)

1. An equipment scientific research project risk factor assessment system, 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): used to decompose the equipment scientific research project to be evaluated into several units of magnitude, subdivide the project risk into several secondary risk factors, and divide the magnitude unit of the equipment scientific research project to be evaluated and the two The risk factor is sent to the server (3), the risk value from the server (3) is received, the risk level is divided, and the evaluation result is output; The client terminal (2): used to download the magnitude unit and the secondary risk factor from the server (3), assign an evaluation value to the secondary risk factor of the project, and output the evaluation value and transmit it to the server (3); The server (3): used to send the magnitude unit and the secondary risk factor to the client terminal (2), the secondary risk factor has different types, and the server (3) sends according to the type of the secondary risk factor to the client terminal (2) of the corresponding type; the server (3) receives the evaluation value from the client terminal (2), calculates the magnitude unit risk value of different levels respectively, and transmits it to the user terminal (1) . 2. A system for evaluating risk factors of equipment scientific research projects according to claim 1, characterized in that: the user terminal (1) comprises a system decomposition module (11), a risk indicator module (12), a risk level output module ( 13); The system decomposition module: based on the WBS technology, the equipment scientific research projects are longitudinally decomposed to form units of magnitude; The risk index module (12): decompose the equipment scientific research project to be evaluated into several secondary risk factors from the two dimensions of project overrun probability risk and impact consequence risk, and each secondary risk factor has a designated professional type to match the corresponding type of client terminal (2); The risk level output module (13): matches the risk magnitude of the magnitude unit output by the server (3) with the set risk curve, obtains the corresponding risk level and countermeasures, and outputs the evaluation result. 3. A system for evaluating risk factors of equipment scientific research projects according to claim 1, characterized in that: the evaluation value given by the client terminal (2) to the secondary risk factors of the project to the project risk is the secondary factor pair. The weight value of the effect degree of each project's influencing factors, the higher the score, the greater the risk. 4. A system for evaluating risk factors of equipment scientific research projects according to claim 1, characterized in that: the server (3) comprises an evaluation value sending and collecting module (31), a project overrun probability value calculation module (32) , a project impact and consequence magnitude calculation module (33), a project risk magnitude calculation module (34); The evaluation value sending and collecting module (31): send the magnitude unit and the secondary risk factor output by the user terminal (1) to the corresponding type of client terminal (2); The project overrun probability magnitude calculation module (32): according to the magnitude unit output by the user terminal (1) and the evaluation magnitude output by the client terminal (2), respectively calculate the items of the magnitude unit at different levels in the magnitude unit overspending probability magnitude P _f ; The project impact consequence magnitude calculation module (33): according to the magnitude unit output by the user terminal (1) and the evaluation magnitude output by the client terminal (2), respectively calculate the magnitude unit items of different levels in the magnitude unit influence the consequence magnitude C _f ; The project risk value calculation module (34): according to the output magnitude unit and the evaluation value output by the client terminal (2), respectively calculate the project risk value F _f of different levels of the magnitude unit in the magnitude unit. 5. a kind of equipment scientific research project risk factor assessment system according to claim 4, is characterized in that: the calculation method of described project overrun probability value P _f is:

In the formula, Wi represents the probability of project overrun of the ith factor, m _ij represents the proportion of the jth _{unit of magnitude of the ith factor, V j} represents the _evaluation value, W represents the weight set of the probability of overrun, M Represents the project overrun probability evaluation matrix, V represents the project overrun probability evaluation value vector, and T is the transpose symbol. 6. a kind of equipment scientific research project risk factor assessment system according to claim 4, is characterized in that: the calculation method of described project influence consequence value C _f is:

In the formula, E' represents the fuzzy comprehensive evaluation matrix after normalization, Y represents the magnitude vector of project impact consequences, and T represents the transpose symbol. 7. a kind of equipment scientific research project risk factor assessment system according to claim 4, is characterized in that: the calculation method of described project risk value F _f is: 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 represents the probability of budget overrun; C _s represents the impact of budget overrun on the project. 8 . The risk factor evaluation system for equipment scientific research projects according to claim 3 , wherein the types of the secondary risk factors include technical factors, economic factors, progress factors and impact and consequence factors, wherein the technical factors include technical factors. 9 . Advancement, technological innovation, technological succession, technological complexity, research unit situation, economic factors include national economic situation and inflation rate, international situation and exchange rate changes, domestic policy orientation, industry environment, product supply and demand , the progress factor includes the subsystem progress and the overall project progress; the influencing consequence factors include overspending, reduction of target, and project suspension. 9. A method for evaluating risk factors of equipment scientific research projects, characterized in that the method is implemented based on a system for evaluating risk factors of equipment scientific research projects, the system comprising a server (3), at least one user terminal (1) and at least one A client terminal (2), the method includes the following steps: 1) User terminal (1) Decompose the equipment scientific research project to be evaluated into several units of magnitude, subdivide the project risk into several secondary risk factors, and divide the units of magnitude and secondary risk factors of the equipment scientific research project to be evaluated send to server(3); 2) The server (3) sends the magnitude unit and the secondary risk factor to the client terminal (2) with the corresponding type according to the type of the secondary risk factor; 3) The client terminal (2) downloads the magnitude unit and the secondary risk factor from the server (3), assigns an evaluation value to the secondary risk factor of the project, and transmits the output evaluation value to the server (3); 4) The server (3) receives the evaluation value from the client terminal (2), calculates the magnitude unit risk value of different levels respectively, and transmits it to the user terminal (1); 5) The user terminal (1) receives the risk value from the server (3), divides the risk level, and outputs the evaluation result. 10 . The method for evaluating risk factors of equipment scientific research projects according to claim 9 , wherein the server ( 3 ) distributes magnitude units and secondary risk factors to corresponding client terminals according to a pre-stored list sequence. 11 . (2), and set the task period, the evaluation user sends the confirmation reception instruction to the server (3) through the client terminal (2); if the server (3) does not receive the confirmation reception instruction within the specified time, it will be sent to the next corresponding command in the list. If the candidate client terminal (2) in the list is 0, it sends an allocation failure instruction and an extension request instruction to the user terminal (1).

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