Patent Publication Number: US-2007100775-A1

Title: Method for estimating the cost of a future project

Description:
TECHNICAL FIELD  
      This disclosure relates generally to a method for determining the cost of a project and, more particularly, to a method for determining the cost of a future project based on automatically-collected historic data.  
     BACKGROUND  
      In the construction, maintenance, repair, and service industries, new projects require significant resources. These resources may include personnel, time, materials, facilities, equipment, and other resources known in the art. The availability of these resources may depend on a significant amount of financial investment and may have an associated amount of risk. The companies or other organizations that fund these projects or provide these services may desire to know the associated cost of investment, before committing the necessary resources.  
      The cost of investing in a new project is typically determined based on historic data manually gathered from past similar projects. This historic data could include information such as equipment cost, resale value of the equipment after completion of the project, total equipment operator cost, total fuel cost, total repair cost, insurance cost, etc. By assessing this information, an overall cost of the new project may be estimated. However, the conditions at one project location may vary over time, or may be very different from another project location, causing inaccuracies in the cost estimation.  
      One method that has been developed for improving the accuracy of an estimated cost associated with an intangible project is described in U.S. Patent Publication No. 2002/0138394 (the &#39;394 publication) of Elliot printed on Sep. 26, 2002. The &#39;394 publication describes a method of doing business that includes generating statistics data related to the new project location such as local labor rates, local cost for uniforms, local cost for equipment, local cost of supplies, local union regulations, etc. The method further includes calculating an estimated cost of providing the requested service based on the location-specific statistics data.  
      Although the method of the &#39;394 publication may improve the accuracy of cost estimation by factoring in location-specific cost parameters, it may be limited and labor intensive. In particular, because the statistics data used in the method of the &#39;394 publication does not include information related to the current operational condition of the equipment or operating parameters of the equipment affected by the location of the new project, the accuracy of the estimated cost may be inadequate. In addition, because the statistics data described in the &#39;394 publication must be manually collected, the method of the &#39;394 publication may be time consuming and inefficient.  
      The method of the present disclosure is directed towards overcoming one or more of the problems as set forth above.  
     SUMMARY OF THE INVENTION  
      In accordance with one aspect, the present disclosure is directed toward a method for determining the cost of a future project. The method includes receiving one or more parameters of a future project and determining an equipment solution that satisfies the parameters of the future project. The method also includes analyzing historic data automatically collected by equipment encompassed by the equipment solution and estimating a cost of implementing the equipment solution to complete the future project, based on the analysis. The method further includes calculating the cost of the future project based on the estimated cost of implementing the equipment solution.  
      According to another aspect, the present disclosure is directed toward a computer system including a console, at least one input device, and a central processing unit in communication with the console and the at least one input device. The central processing unit is configured to receive one or more parameters of a future project via the at least one input device and determine an equipment solution that satisfies the parameters of the future project. The central processing unit is also configured to analyze historic data automatically collected by equipment encompassed by the equipment solution and estimate a cost of implementing the equipment solution to complete the future project, based on the analysis. The central processing unit is further configured to calculate the cost of the future project based on the estimated cost of implementing the equipment solution.  
      In accordance with yet another aspect, the present disclosure is directed toward a computer readable medium for use on a computer system. The computer readable medium has computer executable instructions for performing a method, including receiving one or more parameters of a future project and determining an equipment solution that satisfies the parameters of the future project. The method also includes analyzing historic data automatically collected by equipment encompassed by the equipment solution and estimating a cost of implementing the equipment solution to complete the future project, based on the analysis. The method further includes calculating the cost of the future project based on the estimated cost of implementing the equipment solution. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       FIG. 1  is a schematic and diagrammatic illustration of an exemplary disclosed work machine;  
       FIG. 2  is a block illustration of an exemplary disclosed computer system for use with the work machine of  FIG. 1 ; and  
       FIG. 3  is a flowchart illustration of an exemplary disclosed method of operating the computer system of  FIG. 2 . 
    
    
     DETAILED DESCRIPTION  
       FIG. 1  illustrates a work machine  10  having an exemplary disclose data acquisition system  12 . Work machine  10  may embody a stationary or mobile machine configured to perform some type of operation associated with an industry such as mining, construction, farming, transportation, power generation, or any other industry known in the art. For example, work machine  10  may be an earth moving machine such as a haul truck,.a dozer, a loader, a backhoe, an excavator, a motor grader, or any other earth moving machine. Work machine  10  may alternatively embody a stationary generator set, pumping mechanism, or any other suitable operation-performing work machine.  
      Data acquisition system  12  may include components that cooperate to automatically gather information from work machine  10  during operation of work machine  10 . For example, data acquisition system  12  may include an interface module  16 , a communication module  18 , and a controller  22  configured to communicate with an off-board system  20  via communication module  18 . It is contemplated that one or more of interface module  16 , communication module  18 , and controller  22  may be integrated as a single unit. It is further contemplated that data acquisition system  12  may include additional or different components than those illustrated in  FIG. 1 .  
      Interface module  16  may include a plurality of sensing devices  16   a - e  distributed throughout work machine  10  and configured to gather data from various components and subsystems of work machine  10 . Sensing devices  16   a - e  may be associated with a work implement  23 , a power source  24 , a transmission  26 , a torque converter  28 , a fluid supply  30 , and/or other components and subsystems of work machine  10 . These sensing devices  16   a - e  may be configured to automatically gather data from the components and subsystems of work machine  10  such as, for example, implement, engine, and/or work machine speed or location; fluid pressure, flow rate, temperature, contamination level, and/or viscosity; electric current and/or voltage levels; fluid (i.e., fuel, oil, etc.) consumption rates; loading levels (i.e., payload value, percent of maximum allowable payload limit, payload history, payload distribution, etc.); transmission output ratio; cycle time; grade; performed maintenance and/or repair operations; and other such pieces of information. Additional information may be generated or maintained by interface module  16  such as, for example, time of day, date, and operator information. Each of the gathered pieces of information may be indexed relative to the time, day, date, operator information, or other pieces of information to trend the various operational aspects of work machine  10 .  
      Communication module  18  may include any device that is configured to facilitate communications between controller  22  and off-board system  20 . Communication module  18  may include hardware and/or software that enables communication module  18  to send and/or receive data messages through a direct data link  32  or a wireless communication link  34 . The wireless communications may include satellite, cellular, infrared, and any other type of wireless communications that enable controller  22  to wirelessly exchange information with off-board system  20 .  
      Controller  22  may include any means for monitoring, recording, storing, indexing, processing, and/or communicating the operational aspects of work machine  10  described above. These means may include components such as, for example, a memory, one or more data storage devices, a central processing unit, or any other components that may be used to run an application. Furthermore, although aspects of the present disclosure may be described generally as being stored in memory, one skilled in the art will appreciate that these aspects can be stored on or read from types of computer program products or computer-readable media, such as computer chips and secondary storage devices, including hard disks, floppy disks, optical media, CD-ROM, or other forms of RAM or ROM.  
      Controller  22  may be in communication with the other components of data acquisition system  12 . For example, controller  22  may be in communication with interface module  16  and with communication module  18  via communication lines  36  and  38 , respectively. Various other known circuits may be associated with controller  22  such as, for example, power supply circuitry, signal-conditioning circuitry, solenoid driver circuitry, communication circuitry, and other appropriate circuitry.  
      Off-board system  20  may represent one or more computing systems of a business entity associated with work machine  10 , such as a manufacturer, dealer, retailer, owner, or any other entity that generates, maintains, sends, and/or receives information associated with work machine  10 . The one or more computing systems may include, for example, a laptop, a work station, a personal digital assistant, a mainframe, and other computing systems known in the art. As illustrated in  FIG. 2 , off-board system  20  may include a central processing unit (CPU)  40 , a random access memory (RAM)  42 , a read-only memory (ROM)  44 , a console  46 , an input device  48 , a network interface  50 , a database  52 , and a storage  54 . It is contemplated that off-board system  20  may include additional; fewer, and/or different components than what is listed above. It is understood that the type and number of listed devices are exemplary only and not intended to be limiting.  
      CPU  40  may execute sequences of computer program instructions to perform various processes that will be explained below. The computer program instructions may be loaded into RAM  42  for execution by CPU  40  from ROM  44 .  
      Storage  54  may embody any appropriate type of mass storage provided to store any type of information CPU  40  may need to perform the processes. For example, storage  54  may include one or more hard disk devices, optical disk devices, or other storage devices that provide storage space.  
      Off-board system  20  may interface with a user via console  46 , input device  48 , and network interface  50 . In particular, console  46  may provide a graphics user interface (GUI) to display information to users of off-board system  20 . Console  46  may be any appropriate type of computer display device or computer monitor. Input device  48  may be provided for users to input information into off-board system  20 . Input device  48  may include, for example, a keyboard, a mouse, or other optical or wireless computer input devices. Further, network interface  50  may provide communication connections such that off-board system  20  may be accessed remotely through computer networks.  
      Database  52  may contain model data and any information related to data records under analysis. Database  52  may also include analysis tools for analyzing the information within database  52 . CPU  40  may use database  52  to determine historic relations or trends relating to fluid consumption rates; work machine repair and/or maintenance history; loading, stresses, and/or wear on components of work machine  10 ; hours of use, and other such pieces of real time machine usage information.  
       FIG. 3  illustrates a flowchart  56  depicting an exemplary method that utilizes off-board system  20  to determine a cost of a future project based on the historical relations or trends determined by CPU  40  . It is contemplated that the method may alternatively be implemented manually without the use of off-board system  20 . The method depicted in flowchart  56  will be described in more detail below.  
     INDUSTRIAL APPLICABILITY  
      The disclosed method and system may provide a way to accurately determine the cost of a future project. In particular, the disclosed method and system maybe used to determine an equipment solution to the future project and the associated required resources based on real time or historic data automatically collected by a work machine. In this manner, a potential investor in the future project may determine the magnitude of investment required to successfully complete the future project, before committing to the project.  
      As illustrated in  FIG. 3 , the first step in determining the cost of a future project may include determining or receiving parameters of the future project (Step  100 ). These parameters may be input to CPU  40  via input device  48  or communicated to CPU  40  via network interface  50  and may include, for example, specific project information. The specific project information may include, among other things, a job type (e.g., a digging operation, a clearing operation, a leveling operation, a hauling operation, a drilling operation, a dozing operation, etc.,) a geographical profile of the project area (e.g., acreage, required profile or dimension, grade, soil composition, typical weather condition, elevation, noise or emission regulations, etc.), a timeline for project scheduling (e.g., allowable operation times, required start of project, required completion date, etc.), and/or any other such project parameters. It is contemplated that CPU  40  may alternatively determine one or more of these parameters as a function of one or more other input parameters.  
      Upon determination or receipt of the project parameter information, an equipment solution may be determined that satisfies the parameters (Step  110 ). An equipment solution may include the use of one or more work machines  10  of various types, sizes, quantities, capabilities, etc. to complete the future project according to the parameters described above. For example, an equipment solution to an excavation project could include one or more hydraulic excavators working in tandem with a dozer or wheel loader to fill a series of haul trucks within a predetermined period of time. Work machines  10  encompassed by the equipment solution may be provided in varying quantities and sizes, and operated at predetermined times of the day for predetermined periods of time by particular operators based on the specific project parameters. For any particular project, multiple equipment solutions may be provided depending upon the predefined project parameters. Similarly, it is contemplated that for certain projects, only one equipment solution may be available based on the predefined project parameters.  
      Once the equipment solution has been determined, historic data automatically collected during a previous project by the same equipment encompassed by the solution to the future project may be analyzed to predict operation of the equipment during completion of the future project (Step  120 ). In the example of the excavation project described above, historic data automatically captured and/or generated by data acquisition system  12  for the hydraulic excavators, dozer or wheel loader, and the series of haul trucks may be analyzed. The analysis may include, for example, a comparison of the previous project&#39;s parameters to the future project&#39;s parameters, and the inherent relationship to the associated operational aspects or trends of the same work machines  10  collected during completion of the previous project. These same aspects can then be predicted for the work machines  10  encompassed by the equipment solution of the future project according to the inherent relationship . Ideally, the historic data collected from one work machine  10  may be used to predict the operational aspects of the same work machine  10  at the same work location.  
      For example, if the project area of the future excavation project is larger than the project area of a previous excavation project and the soil composition is more abrasive, it can be expected that the amount of fuel required by the work machines  10  to complete the future project may increase; tire, track, or implement wear may increase; additional repairs may be required; and the operational and/or maintenance time of each work machine  10  may increase. The amount of increase may be proportional to the increase in the project&#39;s parameters (e.g., project area and soil abrasiveness in the excavation example above). In addition, trends associated with each of the captured operational aspects of each work machine  10  may indicate an increasing or decreasing need for repair or maintenance that may be manifested during completion of the future project, or may be used to predict an impending component failure or other potential problem associated with the future project. The history of these operational aspects and the corresponding trends automatically captured or generated by data acquisition system  12  may be used to predict the operational resources (i.e., fuel, oil, water, etc.), repair resources, maintenance resources, replacement resources or other related resources required during the implementation of the equipment solution (Step  130 ). These predictions may then be converted by CPU  40  to an equipment solution cost or cost of completing the future project with the associated equipment solution (Step  140 ).  
      Once the equipment solution cost has been determined, this cost may be compared with an industry standard and selected for the project or modified based on the comparison (Step  145 ). Specifically, the cost of implementing the equipment solution determined from step  110  described above may be greater than other available solutions. Other available solutions might include rental equipment, the purchase of new equipment or technology, manual labor, and other such solutions known in the art. The cost of these other available solutions may be determined according to conventional methods. Then, if the equipment solution determined from step  110  above is more expensive to implement than the other available solutions, the equipment solution may be modified or replaced with other available solutions to generate a lower overall equipment solution cost.  
      The cost of the future project may be calculated as a function of the estimated cost of implementing the selected or modified equipment solution (Step  150 ). That is, in addition to the conventionally estimated cost of materials and labor associated with the future project, the cost of the equipment solution may be included in the final tally. Because the cost of the final project takes into account data automatically collected during previous projects performed by the same work machine(s)  10  that are intended for the future project, the estimated cost of implementing the equipment solution may be very accurate. In addition, when the automatically collected data is collected at the same job site location as that of the future project, thereby taking into account location-specific relationships, the accuracy can be increased even more. Further, because the data is automatically collected, the process may be inexpensive and efficient.  
      It is contemplated that once the cost of the final project has been determined and approved for implementation, CPU  40  may automatically schedule the resources necessary to implement the equipment solution. In particular, upon acceptance of a bid proposal, for example, CPU  40  may automatically arrange for the transportation, repair, maintenance, service, operation, and other such tasks associated with the use of equipment encompassed by the equipment solution. CPU  40  may also automatically gather data from the equipment during operation and compare the actual operational aspects, historical trends, and associated costs to the previously predicted values to track the accuracy of the process.  
      It will be apparent to those skilled in the art that various modifications and variations can be made to the method and system of the present disclosure. Other embodiments of the method and system will be apparent to those skilled in the art from consideration of the specification and practice of the method and system disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope of the disclosure being indicated by the following claims and their equivalents.