RU2259593C2 - System for determining cost of project - Google Patents

Abstract

FIELD: means for calculating cost of project during earlier stages of engineering.

SUBSTANCE: system for estimating cost of project, realized as computer software, has type module for receiving user input, determining type of project, and for forming requirements to project, project module receives requirements for project and compiles a project, including given data, operating characteristics data receives data from calculations and generates parameters of working characteristics, cost module receives data and determines cost, client cost module takes in working characteristics and determines cost of project for client.

EFFECT: higher efficiency.

10 cl, 8 dwg

Description

Technical field

This invention relates to a system for evaluating a project nodes, which provides the user with the ability to quickly determine the cost of the project in the early stages of the design process. The design process is constantly being improved due to the economic pressure of the market and also due to the need to identify risk aspects related to a particular design. The design must comply with the guarantees provided to the buyer, and must have the ability to be developed to meet these guarantees in terms of a definable and acceptable level of costs. In the past, the main decisions on the type of project and technical conditions were based on the parameters proceeding from the project. In this case, for example, when designing an aircraft engine, designers proceed from such parameters as weight. Performance criteria (i.e., to what extent this project meets the customer's requirements) are not evaluated until, during the design process, changes to the project become too costly. Accordingly, in the art there is an urgent need for a design system that will provide the ability to evaluate the effect of project variables at the preliminary design stage.

SUMMARY OF THE INVENTION

An example embodiment of the invention is directed to a project evaluation system implemented on a computer. The system includes a type module for receiving user input that determines the type of project, and for generating the corresponding requirements. The design module accepts the requirements and produces a project that includes the calculated data. The performance module accepts the calculated data and the type of project and generates performance parameters. The cost module accepts the calculated data and determines the cost price. The cost module for the customer accepts performance parameters and cost data, determines the cost of this project for the customer.

A brief description of the drawings.

Figure 1 is a block diagram of a system for evaluating an engine design in an exemplary embodiment of the invention.

Figure 2 illustrates a system for evaluating an engine design for performing deterministic exploration.

Figure 3 illustrates the space of design parameters formed on the basis of control parameters.

Figure 4 illustrates the restrictions on the placement in space of the design parameters of figure 3.

5 illustrates an example of deterministic exploration.

6 illustrates the use of an engine design assessment system for deterministic development.

7 illustrates the result of applying an engine project evaluation system to perform robustness analysis of a project.

Fig. 8 is a block diagram of a project evaluation system in an exemplary embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Figure 1 is a block diagram of a system for evaluating an engine design, depicted under the general designation 10 in an exemplary embodiment of the invention. Figure 1 depicts the application of the present invention to an engine design. In accordance with the description below with reference to Fig. 8, this system is applicable to any type of project. The engine design assessment system 10 consists of several modules. The user can assign input data to one or more modules, and the modules generate output data used by subsequent modules. The modules described in detail here have varying degrees of complexity or knowledge. Separate modules, and therefore the entire system, can be executed by a general-purpose computer in accordance with the following.

Turning to FIG. 1, an aircraft type (A / C) type module 12 is used to provide a user with a mechanism for inputting an A / C type on which the engine will be used. For example, a user may enter such data that the Boeing 767 used for commercial passenger / freight traffic should be a glider. Module 12 of the type of aircraft determines, depending on the user input, requirements for aircraft, engine requirements. Aircraft requirements can contain a variety of factors, including range and payload. Engine requirements may include factors such as traction and size restrictions. Module 12 type aircraft can be performed using a computer model. The user enters data such as an aircraft, and the model selects and displays data related to the requirements for aircraft and engine requirements.

The engine design module 14 receives the output from the aircraft type module 12 and provides the user with the opportunity to design an engine that meets the requirements established by the aircraft type module 12. The engine design module 14 provides the user with the opportunity to develop an engine design based on many factors, including, but not limited to, the factors of thermodynamics, aerodynamics, mechanics, and electrical engineering. Engine design module 14 provides a fast, consistent way to design an engine in accordance with specific requirements and design constraints. A detailed assessment of various aspects (for example, thermodynamic aspects) at the individual component level provides the engine design module 14 with the ability to quickly and consistently study changes in the requirements and limitations of the engine design.

Engine design module 14 bases the engine design on engine requirements received from aircraft type module 12, such as thrust, and also such as user-entered engine characteristics, such as fan compression ratio, overall compression ratio, unit temperature limits. Engine design module 14 also receives input from engine technology module 16. Engine technology module 16 contains data relating to various engine technologies (e.g., systems, materials, control processes, etc.). For example, engine technology module 16 may include data relating to multiple engine cooling systems. When the user determines a specific cooling system, the engine design module 14 accesses the engine technology module 16 to obtain the data necessary to incorporate this predetermined cooling system into an existing project.

Module 14 of the engine design performs thermodynamic analysis to ensure factors such as pressure, temperature, air flow in the engine, fuel consumption in the engine, for subsequent analysis of the project. Thermodynamic analysis includes aerodynamic design of engine components (fan, compressor, combustion chamber, high and low pressure turbines, etc.) in order to determine efficiency and performance in real conditions.

The design of aerodynamic nodes is based on the parametric levels of node technology. Node technologies are characterized outside specific dimensions in order to scale the nodes to an appropriate size to comply with traction requirements and the general thermodynamic characteristics of the engine. This nodal representation determines the design and actual efficiency and flow characteristics depending on the corresponding physical parameters.

Aerodynamic and thermodynamic analysis provides the basis for the mechanical design of the power plant. The mechanical design assessment includes positions such as rotating and static engine designs and selecting the appropriate material. Project evaluation includes a consistent geometric representation that is used to estimate engine weight. All control weights, external configurations and engine nacelles are included in the engine weight.

The engine design module 14 and the engine technology module 16 can be implemented using the engine design computer program. These engine design programs are publicly available and include Jack D. Mattingly's programs.

Based on the engine design created by the user in the engine design module 14, engine data such as thrust, fuel consumption and weight are determined. The engine data is sent to the aircraft performance module 18, which determines what the LA characteristics will be. The aircraft performance module 18 uses engine data obtained from the engine design module 14, such as thermodynamic data (traction and fuel consumption), power plant weight, engine nacelle geometry data to calculate the aircraft’s performance. This information is integrated with the aircraft characteristics previously determined (lift, drag, weight, etc.) obtained from the aircraft type module 12 in order to develop an aircraft model. The aircraft model is used to calculate aircraft performance in terms of thrust impulse, range, payload and flight time for various flights according to typical flight characteristics and safety standards. To calculate these performance characteristics with respect to typical aircraft operation, it is possible to evaluate several flights using the aircraft flight data package. Using data on the totality of flights will provide information on how a particular engine design will work throughout the entire life of the aircraft, and not just during one or two typical flights. The performance data of the aircraft is stored for analysis and is also used as input in the cost module 24 for the customer.

Module 18 aircraft performance can be performed using a computer program flight analysis. The flight analysis program determines the performance of an aircraft by modeling several flights and generating the operating characteristics of the aircraft, such as range, payload and thrust. These flight analysis programs are publicly available and include, for example, DAR programs.

Gas emission and noise data are also generated as part of aircraft performance. Gas emission and noise data can be generated using the noise module 22. Noise module 22 generates a noise estimate based on noise factors such as noise from the combustion chamber, exhaust fan jet, fan intake, jet stream (based on input from engine design module 14), glider noise (based on input from aircraft type module 12 ) Noise levels of the nodes are a function of elements such as aerodynamic, thermodynamic and mechanical parameters, as well as flight paths and some characteristics of the aircraft. Noise module 22 can be performed using a computer model containing a plurality of response surface equations derived from physical models.

The engine gas emission module 20 predicts the release of hydrocarbons such as (HC), nitrogen oxides (NO _x ), and carbon monoxide (CO), and this module operates based on the engine operating cycle parameters under engine operating conditions that correspond to the operating conditions provided for for certification. The gas emission module 20 can be performed using a computer model. The model accepts engine duty cycle parameters and provides data related to engine gas emissions.

The engine design module 14 and the engine technology module 16 provide input to the engine cost module 26. Module 26 of the cost of the engine determines such cost factors as the cost of development, manufacture and maintenance for a specific engine design, based on input from module 14 of the engine design and module 16 of the engine technology. The development cost can be based on statistical data and it determines which part of this engine is based on existing designs, and which on new designs. The higher the proportion of new designs, the higher the cost of development. Estimates of manufacturing costs can be based on an empirical model and can be determined by the physical size of the assembly and selected materials. Estimates of the cost of maintenance can be correlated with the cost of manufacturing and also the intensity of operation of the engine. An engine maintenance model is also provided, which calculates maintenance periods based on factors such as temperature levels for critical parts and the calculated degree of engine wear. Engine value module 26 may be implemented using a computer program such as PRICE-H, which can be purchased from Lockheed Martin.

The cost module 24 for the customer receives the output from the aircraft performance module 18, the gas emission module 20, and the noise module 22. The cost module 24 for the customer also receives maintenance cost data from the engine cost module 26, since the purchaser of the engine usually incurs maintenance costs. Customer cost module 24 may be based on conventional methods of direct operating costs, indirect operating costs, and interest. But instead of analyzing these parameters with respect to one flight, these expenses can be calculated with respect to the same combination of flights defined in the aircraft performance module 18.

The user can also assign a percentage to different flights to reflect the importance of the flight for the revenues of the airline. For example, a frequent flight will be given increased weight compared to less frequent flights. This provides a more accurate representation of the cost of the engine for the customer.

These costs also include the total investment that the airline makes to acquire the aircraft, and it is divided into depreciation, financing and insurance. Also, the payload data computed in the aircraft performance module is integrated with typical revenue data for a given airline to determine revenue for each flight. The payload provides data on the receipts of either passenger or freight traffic, depending on the factors of the flight and the load. These costs and revenues are integrated together with respect to the entire combination of flights in order to determine the annual cash flow for a given airline per one operated aircraft. These annual cash flows are summarized for the normal service life (15–25 years) to determine the total cash flow over the service life period. Taking into account the usual discounts applicable to this airline, the cash flow for the service life and investment are analyzed using the net present value method to determine the total cost of a particular estimated engine project. The airline’s internal payback ratio is also calculated. Since the engine project evaluation system is organized as a modular system, this process of calculating the cost for the customer is repeated for each engine project, as a result of which this metric can be used to determine the optimal space of the engine design parameters from the point of view of the airline or the customer.

The value of value to the customer is useful in determining a pricing strategy for engines that identifies differences in cost to the customer. If the end user derives a net gain in terms of profitability from one engine compared to another, then some of this gain can come from manufacturers either in the form of an increased price, an increased market share, or as a combination of both. This information provides guidance to the power plant manufacturer regarding the configuration that provides the highest cost to the customer, and this information also provides an opportunity to evaluate the cost-effectiveness of introducing any additional technology.

The cost module 24 for the customer can be performed using a computer program that determines the above-mentioned operating costs and revenue. Methods for determining cost are well known in the art and are feasible using computer programs. Revenue is based on factors such as range, payload (passengers or cargo) and thrust impulse generated by the aircraft performance module 18. Available data is used to calculate the cost of revenue based on these factors.

The competing engine module 28 includes one or more competing engines that are used to determine the cost to the customer in relation to the competing engine. The competing engine data is sent to customer value module 24, which determines the value of the competing engine to the customer. The cost of a competing engine for the customer is compared with the cost for the customer displayed in customer module 24 to get a cost difference. The competing engine module 28 can be executed using a computer program that stores operating characteristics and cost data (similar to the data generated by the aircraft performance module 18 and the engine cost module 26) for each competing engine. Factors such as performance and weight data for competing engines can be evaluated based on competitor data using available engine design software. Data on competitors can be generated in a separate process, stored in the system, and accessed through competitor module 28. The type of aircraft defined in the module 12 aircraft can be used to sample the corresponding data about the competing engine from the module 28 of the competing engine.

The engine environment module 30 takes the value of the cost difference from the cost module 24 for the customer and determines the sale price of the engine in order to capture a user-defined market share. Module 30 engine conditions contains forecasts of types and quantities of engines that will be in demand in the future. Predicted market conditions are based on the type of aircraft defined in module 12 of the aircraft type. Module 30 engine conditions can be performed using an empirical computer model that contains market data for many types of aircraft. After the type of the aircraft will be indicated in the module 12 of the type of aircraft, the module 30 of the conjuncture of engines refers to the relevant market data.

Then, the price data output by the engine module 30, the data on development and production costs from the engine prime cost module 26 are sent to the commercial profit module 32. Commercial profit module 32 determines the profit, taking into account factors such as development costs, production costs, the final price and maintenance revenues (if the manufacturer serves any percentage of the engines sold). Profit is determined over the entire life of the engine. According to Figure 1, profit can be used to influence a business strategy. For example, you may find that the profit on the engines of the first type of aircraft is always less than the profit on the engines of the second type of aircraft. This will force the manufacturer to produce engines for the second type of aircraft. Commercial profit module 32 can be implemented using a computer model that determines commercial profit by subtracting costs (such as development costs, manufacturing costs, etc.) from the revenue (price, maintenance revenue, etc.).

The engine design assessment system 10 may also be implemented without the use of a competing engine module 28. In this embodiment, the user determines the price to be assigned to the engine. Module 30 engine conditions determines the value of the market share that this engine design will capture at a certain price. Price and market share information is used using the commercial profit module 32 to determine the commercial profit for a given engine over the entire life of the engine.

The engine design assessment system 10 of FIG. 1 can be used at a preliminary design level. This will enable users to better understand exactly which engine parameters and limitations affect design decisions to the greatest extent. The engine design assessment system helps users focus on the right space for design parameters and identify some constraints and parameters that may not be quantified. The engine design evaluation system provides valuable information in the early stages of the design process in order to make optimal design decisions that will provide economic benefits to the customer.

The engine design assessment system 10 can be used in a number of design processes, including deterministic design studies, probabilistic design studies and project robustness analyzes. A description of each of these applications is provided here. Deterministic studies primarily include the main control / design parameters, i.e. variables that the user can change, such as the compression ratio of the fan, the pressure of the internal circuit of the engine, the temperature at the inlet of the fan, cooling technology and materials, etc. When performing a deterministic study, the user is able to determine the optimal possible design of the engine relative to several output parameters i.e. traction impulse, range, customer value, etc.).

FIG. 2 illustrates the input and output data of an engine design assessment system 10 in an exemplary deterministic design. According to the image in FIG. 2, the project evaluation system 10 receives signal parameters defining engine requirements, including thrust at maximum climb, thrust at sea level and thrust at high altitude. The engine design evaluation system also accepts control parameters, which are parameters that the user can change, and which the user wants to select to optimize one or several output parameters. In a deterministic study, the uncertainty parameters are not used. The goal is to evaluate how the control parameters affect the output parameters so that the user can optimize the control parameters. The engine project evaluation system generates output depending on the control parameters to provide the user with a project space indicating how the control parameters affect one or more output parameters.

Figure 3 depicts an example space of design parameters generated by the engine design evaluation system and correlating two control parameters XI (fan compression ratio) and X2 (temperature in the compressor outlet pipe) with a thrust pulse. When studying this space of design parameters, it is easy for the user to understand how changes in the control parameters X1 and X2 affect the thrust impulse. Figure 3 depicts the benefits of deterministic design over conventional spot design. In point design, designers make design decisions using statistical trends and also based on design experience to determine the very limited number of point design engines under consideration. But at the same time, the engine designer is not able to visualize what exactly is happening in the whole space of design parameters; however, only a few point projects represent the optimal possible engines within a given space of design parameters.

Deterministic design provides the user with the ability to quickly evaluate a large space of design parameters determined by control parameters. The user can also impose restrictions on the control parameters according to Figure 4, so that the user can concentrate on that part of the space of design parameters that can actually be implemented. This allows the user to understand the impact of restrictions, as a result of which this restriction can either be reviewed, or a possible change can be introduced into the project. Therefore, a deterministic study improves understanding of future point design configurations.

A deterministic study is not limited to two control parameters. You can apply any number of control parameters. In order to optimize one or more output parameters, a decisive program can be used (eg, Axel decisive program). For example, it is possible to form a space of design parameters that correlates all five control parameters depicted in Figure 2 with a thrust impulse. Then the decisive program can find the values of five control parameters that optimize the thrust momentum, cost for the customer, commercial profit, etc.

FIG. 5 illustrates an exemplary deterministic study conducted using the engine design assessment system 10. To evaluate the large space of design parameters, nine different control parameters were selected. The control parameters were constrained between predetermined limits. To minimize the number of runs needed to formulate the response surface equation for different output parameters, modified experiment design (PE) using central composite design (DSP) with nine variables was used. The application of the engine design assessment system 10 at the preliminary design level significantly accelerates the assessment of a large space of design parameters with many control parameters.

Modified PE DSP for nine control parameters is 147 different runs. It would take a huge amount of time to generate 147 spot design engines, evaluate the engine using an aircraft flight analysis program, and determine all relevant output parameters (traction impulse, acoustics, cost for the customer, etc.). Using the project evaluation system, these tasks were completed in the evening and the next morning the results were ready. Thanks to the quick response of the engine design assessment system, the user can evaluate the impact of many different design constraints and assumptions. An analysis of the design of the nodes provides an understanding of the constraints that reduced additional benefits in terms of performance.

One of the output parameters presented in FIG. 5 is an improved thrust impulse. Using the engine design assessment system 10, a user was able to determine how various design constraints affect engine performance. The first limitation to be evaluated was the maximum increase in engine thrust (i.e., the amount of additional thrust that this engine design could master due to modifications). The engine design assessment system 10 has shown that designing an engine with less potential for increasing traction results in improved impulse traction. With a decrease in the maximum potential for increasing thrust from 40% to 15%, the thrust momentum improves by about 1%. In addition, the torque of the fan shaft and the bearing speed were limiting factors. The engine design evaluation system 10 has shown that applying new material to the fan shaft will improve traction momentum by another 1%.

The engine design assessment system can also be used in probabilistic studies to model the uncertainty of FIG. 6. In accordance with the image in FIG. 6, uncertainty parameters are applied to the engine design evaluation system 10. The control parameters are fixed for a specific engine design. This allows the user to see the effects of uncertainty for a single engine design. Uncertainty is present in the preliminary stages of the design process due to project requirements arising in the course of its design; and also there are uncertainties associated with the detailed implementation of the aerodynamic and mechanical design of engine components. This uncertainty is due to the assignment of a statistical distribution to each uncertainty parameter and also to the use of the Monte Carlo method or equivalent methods, such as fast probabilistic integration (BIE), to form probability distribution functions (PDF) or integral distribution functions (IGF) that characterize the probability that This output parameter will be consistent with the goals of the system.

By using statistical analysis tools, the engine design assessment system 10 has the ability to evaluate uncertainties and quantify the likelihood that the output parameters will meet design requirements. Uncertainty parameters are variable values that the user cannot reliably predict in the early stages of the design process (e.g., efficiency of nodes, cooling flows, etc.). This type of analysis gives the user the opportunity to determine which particular uncertainty variables most affect certain output parameters and identify technology improvement programs. An IGF illustrates the likelihood of matching a specific goal for a specific set of engine control parameters.

6 represents a specific engine configuration constructed according to a given set of engine requirements, with the addition of engine uncertainty parameters. The output is presented as IGF. The graphs characterize the level of confidence that a given output parameter will correspond to a given target with a given engine configuration subjected to the levels of the uncertainty parameter. For example, according to the example in FIG. 6, the probability of achieving a goal with respect to the thrust impulse for a particular engine configuration subject to some uncertainty is 85%.

Engine design assessment system 10 may also be used to perform robustness analysis of the design. Robust engine design is a cumulative effect of deterministic design and probabilistic assessment. In other words, the robustness analysis of the project is performed to identify the optimal possible engine configuration and to evaluate the uncertainties associated with each engine configuration. Uncertainty analysis can also be used to determine the risk of breaking a limit or restricting a project. A robust project provides the opportunity to maximize the likelihood that a given engine design meets project constraints. This type of analysis provides the user with the opportunity not only to quantify the change associated with the output of the system, but also to determine the change in the constraints of the project. The values of the mean and standard deviation of the output parameters of all combinations of the project are selected in the form of surface reaction equations. These surface reaction equations are then subject to the constraints imposed on the engine design. Therefore, the user is able to quantify the risk associated with optimal deterministic design.

7 illustrates the feasibility of a robust design. 7 depicts the space of design parameters relative to the temperature of the compressor outlet pipe (X2) depending on the temperature at the inlet of the turbine rotor (X3). Explore three different points in the space of design parameters. At point A, the standard deviation of the thrust impulse is minimal, which indicates the minimum dispersion value in the project space. The range of thrust impulse values at this location is depicted as a distribution of 100. Only half of the distribution 100 corresponds to a given thrust impulse (half of the distribution is located to the left of the desired thrust impulse). Accordingly, using the minimum dispersion to select a thrust impulse gives an approximate 50 percent chance of matching a given thrust impulse. At point B, the average thrust momentum is minimized. The range of values of the thrust impulse at this location is shown as distribution 110. Distribution 110 has the largest variation in the project space, and the probability of matching the given thrust impulse is about 60% - only slightly better than at point A. Point C represents the optimal robust solution. The range of values of the thrust impulse at point C is represented by the distribution 120. In accordance with the image in FIG. 7, about 85% of the distribution 120 corresponds to a given thrust impulse.

A 50% confidence level (implemented at point A of the project space) characterizes the 50% risk of non-compliance with the project requirements. This discrepancy with design requirements entails redesign, re-checks, or financial penalties associated with guarantees and discounts due to a possible delay in putting the engine into operation. An 85 percent confidence level (implemented at point C of the project space) represents a 15 percent risk of non-compliance with project requirements. Accordingly, using the engine design assessment system 10 to perform robustness analysis of the project, the risk of non-compliance with the design constraint is more than tripled.

Using the engine project evaluation system to perform robustness analyzes of the project, the control parameters of the engine can be selected so as to maximize the likelihood of meeting the project objectives. In the example of FIG. 7, maximizing the likelihood of matching a given thrust impulse resulted in only a negligible negative impact (a fraction of a percent) on the design thrust impulse, engine weight, and engine cost. Additional risk reduction can be achieved by finding a level of confidence at which all restrictions converge to a single point. This is the least risk engine, i.e. an engine that has a lower probability of non-compliance with both design constraints and tasks that provide value to the customer.

The engine design evaluation system provides the user with a means of evaluating the quantitative effect of design decisions in the early stages of the process. The system quickly provides complete robustness analyzes and therefore the user can quickly make design decisions. In accordance with the foregoing, this system quantifies uncertainties using the FRV or IGF and provides the user with the opportunity to develop projects with a probability of success as a stimulating factor. This system is also parametric, which allows the user to explore the whole space of design parameters immediately instead of examining one point in the space of design parameters.

FIG. 8 depicts a project evaluation system 100 as an example embodiment. The project evaluation system 100 can be applied to various technologies, and it is not limited to the aircraft engine project evaluation described in relation to FIG. 1. The project evaluation system 100 is similar to the system set forth in relation to FIG. 1 in that it is used to evaluate the design of a unit (eg, an engine) that is part of a system (eg, an airplane). An exemplary system / assembly combination that can be evaluated using the project evaluation system 100 is a locomotive / engine combination (diesel or gas). Additional system / node configurations include “household appliance / subsystem” configurations (in this case, the household appliance includes a wide class of consumer goods, including washing machines, hair dryers, refrigerators, video recorders, CD players, etc.); configurations “power station / generator” (including steam turbines, turbogenerators, etc.), “computer / processor”, “transport device / propulsion system” and “incandescent lamp / filament”. It is implied that the above examples of the application of the project evaluation system do not limit the range of application of this invention.

System 100 includes modules similar to those described with respect to FIG. 1. Type module 112 provides the user with the opportunity to select a particular application. For example, if a user designs an engine for a locomotive, then he can specify the type of locomotive. Then the type module determines such requirements for the engine as horsepower, fuel efficiency, etc.

Project module 114 receives requirements from type 112 module and enables the user to develop a project that meets the requirements defined by type module 112. For module 114 of the project, you can use the available design programs. Project module 114 also receives input from technology module 116. Technology module 116 contains data related to various technologies. For example, if a system is used to design a cooling subsystem for a refrigerator, then technology module 116 may contain data related to different damper configurations (eg, a single damper or a double damper). After the user determines a specific technology, the design module 114 refers to the technology module 116 to obtain the data necessary to incorporate a specific technology into an existing project.

The module 114 of the project generates a project that includes the estimated data. The performance module 118 uses the calculated data from the project module 114 to calculate the design performance. For example, if the design is a cooling subsystem for a refrigerator, then the performance module 118 may determine a nominal efficiency value for the refrigerator.

Cost module 126, customer cost module 124, competition module 128, market module 130 and commercial profit module 132 operate similarly to engine cost module 26, customer cost module 24, competing engine module 28, engine market module 30 and commercial profit module, respectively described above with reference to FIG. 1. Cost module 124 for a customer can derive a cost value for a customer based on known market expectations. For example, the cost to the customer of a refrigeration subsystem for a refrigerator may be based on factors such as efficiency and average time to failure. If the project relates to an incandescent filament for an incandescent lamp, then the cost to the customer may be based on the brightness and life of the lamp. The cost module 126, the competition module 128, the market module 130, and the commercial profit module 132 operate similarly to the modules in FIG. 1. In accordance with the foregoing, competition module 128 and customer cost module 124 are used to determine a cost difference for market module 130. The market module can then determine the selling price for a given node in order to capture a user-defined market share. The commercial profit module 132 then determines the profit based on the selling price and cost. The project evaluation system 100 may also operate without competition module 128 as described with respect to the project evaluation system 10.

As indicated above, this invention can be implemented in the form of computer-executable processes and devices that perform these processes. This invention can also be implemented in the form of a computer program containing instructions in physical media such as floppy disks, CD-ROMs, hard disk drives, or any other computer-readable media, and if the computer program is downloaded and executed by a computer, then the computer becomes a device that implements this invention. This invention can also be implemented in the form of a computer program, which, for example, is stored in a medium, downloaded to a computer and / or executed by a computer, or transmitted using a transmission medium, such as electrical wiring or cable, via optical fibers or by electromagnetic radiation moreover, when the computer program is downloaded to the computer and executed by the computer, the computer becomes a device for implementing the present invention. When executed by means of a general-purpose microprocessor, segments of a computer program configure the microprocessor to create certain logic circuits.

Although the invention is set forth herein with reference to exemplary embodiments, it will be apparent to those skilled in the art that various changes can be made therein and its elements may be replaced by equivalents within the scope of this invention. You can also make many modifications in accordance with a specific situation or some material according to the technical solutions of the present invention, without leaving its scope. Therefore, it is understood that the invention is not limited to the specific embodiments disclosed herein, and that the invention includes all implementations falling within the scope of the appended claims.

Claims (10)

1. A computer-implemented project evaluation system for determining the project cost of a node, comprising a type module (112) for receiving user input that determines the type of project to formulate project requirements; a project module (114) for receiving the specified project requirements, the project module generating a project including estimated data; a performance module (118) for receiving said calculation data and generating performance parameters; cost module for the customer, designed to receive the specified performance parameters and determine the cost of the project for the customer. 2. The system according to claim 1, characterized in that it further comprises a competitor module (128) for generating cost data and performance data related to a competing project, the cost module for a customer determining the cost for a customer from a competitor based on cost data and workers characteristics obtained from the competitor module, while the cost module for the customer additionally determines the difference in cost between the cost for the customer from the competitor and the given value for the customer. 3. The system according to claim 2, characterized in that it further comprises a conjuncture module (130) for receiving the indicated difference in cost and a desired market share, the conjuncture module determining the selling price for the specified project in order to obtain the indicated desired market share. 4. The system according to claim 3, characterized in that it further comprises a cost module (126) for receiving said calculation data and for determining a cost price and a commercial profit module (132) for receiving said sales price and said cost price and for determining a commercial profit of said project . 5. The system according to claim 1, characterized in that said node is a propulsion system for a vehicle. 6. The system according to claim 1, characterized in that said unit is an engine used in a locomotive. 7. The system according to claim 1, characterized in that said node is a subsystem for use in a household electrical appliance. 8. The system according to claim 1, characterized in that said node is a power generator of a power plant. 9. The system according to claim 1, characterized in that said node is a processor used in a computer. 10. The system according to claim 1, characterized in that said assembly is an incandescent filament in an incandescent lamp.

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