Classifications

• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q10/00—Administration; Management
  • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q30/00—Commerce
  • G06Q30/02—Marketing; Price estimation or determination; Fundraising

Definitions

• Figure 15 is a diagram illustrating a single national stock number (NSN) part costs tab display screen in accordance with an advantageous embodiment of the present invention
• Figure 16 is a diagram illustrating a single NSN detailed part costs tab display screen in accordance with an advantageous embodiment of the present invention
• Figure 17 is a diagram illustrating a cost with related NSN tab display screen in accordance with an advantageous embodiment of the present invention
• Figure 18 is a diagram illustrating all flight hours and NSN failures tab display screen in accordance with an advantageous embodiment of the present invention.
• Figure 20 is a flowchart of a process for generating a set of cost analysis data tables for an identified commodity in accordance with an advantageous embodiment of the present invention
• FIG. 1 an exemplary diagram of a data processing environment is provided in which advantageous embodiments may be implemented. It should be appreciated that Figure 1 is only exemplary and is not intended to assert or imply any limitation with regard to the environment in which different embodiments may be implemented. Many modifications to the depicted environment may be made.
• FIG. 1 depicts an exemplary diagram of a data processing environment in which an advantageous embodiment of the present invention may be implemented.
• Network data processing system 100 is a network of computers in which embodiments may be implemented.
• Network data processing system 100 contains network 102, which is the medium used to provide communications links between various devices and computers connected together within network data processing system 100.
• Network 102 may include connections, such as wire, wireless communication links, or fiber optic cables.
• a commodity is a repairable equipment or component having one or more parts.
• Each part in a commodity can include one or more subparts .
• Each subpart in a part can also include one or more sub-subparts as well.
• the term commodity can be used to refer to an airplane, as well as a radio that is installed or to be installed inside the airplane.
• subpart refers to a part, piece, or constituent of a commodity or another part.
• a subpart may have one or more subparts of its own, which can be referred to as sub-subparts.
• a sub-subpart may also have subparts, and so forth.
• the different processes for the advantageous embodiments of the present invention may be implemented in a server, client, or combination of server and client computers.
• the processes and data may be located at a single client, such as client 110, alternatively, the processes for providing the simulations may be located on a server, such as server 104 with the client containing a process for providing user input and presenting output, such as through a browser program.
• the different processes for the advantageous embodiments of the present invention may also be implemented in any database system, such as relational database system 114 connected to a network, a server, a client, or combinations of server and client computers.
• network data processing system 100 may include additional servers, clients, databases, data storage devices, and other devices not shown in Figure 1.
• a computer implemented method for managing aircraft fleet maintenance and logistics is provided.
• the process identifies a set of cost driver subparts corresponding to an aircraft type commodity based on part data obtained by using data mining techniques to filter relevant part data from a plurality of data sources.
• the process populates a commodity database to display cost-related failure data and inherit configurations for the commodity based on maintenance and supply data from a set of data sources .
• the process computes an estimated future repair cost for the set of cost driver subparts in the commodity database.
• the commodity database is used to examine equipment health of the commodity.
• cost analysis tables 306 are stored in data storage device 308.
• Data storage device 308 is any type of known or available device for storing data, including but not limited to, random access memory (RAM) , nonvolatile random access memory (NVRAM) , read only memory (ROM) , main memory, cache, a hard disk, a secondary storage device, such as a flash memory or floppy disk, or any other type of data storage device.
• RAM random access memory
• NVRAM nonvolatile random access memory
• ROM read only memory
• main memory main memory
• cache main memory
• a hard disk such as a flash memory or floppy disk
• secondary storage device such as a flash memory or floppy disk, or any other type of data storage device.
• data storage device 308 is a local data storage device located on, or in association with, computer 300.
• data storage device 308 can also include one or more remote data storage devices located on one or more remote computers .
• Data sources 310 are accessed via server 312.
• Server 312 is any type of server, such as server 104 and 106 in Figure 1.
• Server 312 can be a server on a network, such as network 102 described in Figure 1.
• Computer 300 accesses server 312 via network device 314.
• Network device 314 is any type of known or available network access software for allowing computer 300 to access a network.
• Network device 314 connects to a network connection, such as network 102 in Figure 1.
• the network connection permits access to any type of network, such as a local area network (LAN), a wide area network (WAN), or the Internet.
• data sources 310 are located remotely to computer 300.
• one or more data sources in data sources 310 are located on or locally to computer 300.
• computer 300 can access data sources located on or locally to computer 300 in addition to data sources located remotely to computer 300.
• Commodities database manager 304 presents cost analysis tables 306 to a user by means of user interface 316.
• cost analysis tables 306 organize and rank cost analysis data in accordance with a keyed hierarchical coding sequence.
• cost analysis data in cost analysis tables 306 can be organized and ranked in accordance with any known or available organizing and ranking method.
• a cost driver subpart is not a part that is used only once in a single custom designed piece of equipment.
• a cost driver subpart can include a part that is not a part of significant repair and/or replacement cost, and/or a part that is used only once in a single custom designed piece of equipment.
• Commodities cost analysis database 400 is a relational database for organizing, sorting, and ranking cost analysis data, such as commodities cost analysis database 302 in Figure 3.
• This illustrative example includes processes performed by a user that are used as inputs and processes performed by commodities cost analysis database 400.
• a user identifies a commodity based on user data gathering processes and user input (user process 402).
• the commodity is any type of commodity, including but not limited to, an aircraft, a car, a boat, a radio, an engine, or a radar.
• Commodities cost analysis database 400 generates a keyed hierarchical breakdown coding sequence for each cost driver subpart of a commodity.
• the keyed hierarchical breakdown coding sequence provides a code to identify each part and subpart in a hierarchical fashion.
• the keyed hierarchical breakdown coding sequence also identifies the interrelationships of parts. For example, all subparts that are included in the passenger seat assembly include a common code to identify the passenger seat assembly subpart.
• the keyed hierarchical coding sequence for a head rest and seat cushions for a passenger seat assembly include a common code sequence identifying subparts of the passenger seat assembly. In this manner, the keyed hierarchical coding sequence identifies subparts and links them to the next higher assembly to which the subparts belong.
• Commodities cost analysis database 400 combines MIL- STD-1808 and ANSI Y32.16 schemas, or subsequent revisions to those schemas, using a series of alpha-numeric digits to form the unique keyed hierarchical coding sequence for each part or subpart .
• the keyed hierarchical breakdown coding sequence begins with a two-digit commodities code to identify a given commodity.
• a two-digit commodities code identifies the type of commodity, as shown in Figure 5. For example, in the sequence "61A1W3", the two-digit commodity code "61" refers to high frequency communications, as shown above.
• Commodities cost analysis database 400 also generates NSN table 424 based on historical demand for parts by national stock number (NSN) cost data.
• NSN table 424 provides information regarding historical NSN cost data for one or more parts.
• Commodities cost analysis database 400 will use the last nine (9) digits of the national stock number (NSN), referred to herein as the national item identification number (NIIN) , as a filter to query VAMOSC historical databases 410 to produce a record listing of four-digit federal supply class (FSC) and nine-digit NIIN.
• the NIIN is used as a filter to obtain part data, such as sales quantity, total credit quantity, standard price, total credit cost, and net cost from government data sources.
• aircraft quantity and flying hour table 426 is a table providing information regarding the operational hours during which each part is used.
• Aircraft quantity and flying hour table 426 provides information regarding aircraft types, quantities of each part used, and flying hours during which each part is used.
• Commodities cost analysis database 400 obtains this data by filtering for MDS_SRD, which identifies the aircraft.
• Commodities cost analysis database 400 also filters part data using the AFTOC data flight hours and aircraft quantities using the commodity.
• Commodities cost analysis database 400 uses this data to calculate minimum and maximum failure rates for parts when determining future costs.
• the commodity is a non-aircraft commodity.
• commodities cost analysis database 400 uses operating hours and equipment type on which the part is installed instead of flight hours and aircraft type.
• Table 500 is a sample list of two-digit codes based on the MIL-STD-1808 assigned to a commodity based on the type of commodity.
• the two-digit code identifies the type of commodity.
• the two-digit commodity code is generated based on MIL-STD-1808, subsequent revisions of the MIL-STD-1808, and/or any superseding data sources.
• MIL-STD-1808 is a U.S. military standard relating to military and commercial aircraft systems. For example, in the part identification sequence "61A1W3", the "61” is a two-digit commodity code that indicates the part is included in a commodity type identified as high frequency (HF) communications as shown at line 502.
• HF high frequency
• Selected main part numbers 614 is a display showing manufacturer part numbers for a selected part. In this example, selected main part numbers 614 is displayed to the right of main part 604. However, selected main part numbers 614 can be displayed in any location in a display screen.
• Selected breakdown part numbers 616 is a listing of manufacturer part numbers for a selected component part in selected main part numbers 614.
• Double clicking on a selected main part breakdown field, CAGE field, RJSICC field, or RJNJVC field triggers commodities cost analysis database to open a window or screen for a user to view or enter data.
• the selected main part on main part 604 has a breakdown listing of subparts 606. Each subpart has a corresponding selected breakdown number list 616. When users select a different main part, the corresponding subparts and associated parts appear in selected main parts breakdown 606. When users select a subpart, the corresponding part numbers field, CAGE field, RNCC field, and RNCC fields 616 appear.
• MDS mission design series
• Figure 8 is a diagram of a set of summary graphs for commodities sales and repair costs in accordance with an advantageous embodiment of the present invention.
• a summary graph such as net cost graph 802 is displayed in response to a user selecting an indicator on a commodity form summary, such as net control 610 in Figure 6.
• Net cost graph 802 is a graph showing a summary of net costs over a given time period. Net cost is an amount paid for all commodity repairs less credits from organizational (local) and depot-level (non-local) repairs. Negative values are not graphed.
• the process calculates metrics based on historical data, future costs, and projected return on investments (operation 2214) .
• the process displays the numbers and data calculated in operations 2202-2214 using tables, visual indicators, and/or graphical displays (operation 2216) .
• the process compares future estimated cost data for cost driver parts with estimated costs for improvements to show a break-even point and cost effectiveness for replacing a cost driver part and/or repairing the cost driver part (operation 2218) , with the process terminating thereafter.

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• 2007
  • 2007-12-20 WO PCT/US2007/088377 patent/WO2009082389A1/en not_active Ceased
  • 2007-12-20 EP EP07869648A patent/EP2223218A4/de not_active Ceased

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