The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Notice to Applicant
In response to the communication received on 10/10/2024, the following is a Non-Final Office Action for Application No. 18911803.
Status of Claims
Claims 1-20 are pending.
Drawings
The applicant’s drawings submitted on 10/10/2024 are acceptable for examination purposes.
Information Disclosure Statement
The information disclosure statement(s) (IDS) filed 10/10/2024 and 12/23/2025 has been acknowledged. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
As required by M.P.E.P. 201.14(c), acknowledgement is made of applicant’s claim for priority based on: 18911803 filed 10/10/2024 is a Continuation in Part of 18911570 , filed 10/10/202; 18911570 is a Continuation in Part of 18501608, filed 11/03/2023, now U.S. Patent # 12217199 and having 1 RCE-type filing therein.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-16 of U.S. Patent No. US 12217199 B1. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims recite substantially similar limitations as follows: displaying, on the intelligent GUI, a representation of an optimized ramp operations schedule over a period of time for one or more inbound and outbound trains scheduled to be processed at a hub over the period of time, wherein the representation of the optimized ramp operations schedule includes a graphical representation of a status of one or more production tracks of the hub over the period of time overlayed with a representation of the one or more inbound and outbound trains scheduled to be processed at the hub placed correspondingly to a time within the period of time at which the respective train is to be processed; receiving, via the intelligent GUI, a user request to modify a processing time of at least one of the one or more inbound and outbound trains in the optimized ramp operations schedule; re-optimizing, by a ramp operations optimization system, the optimized ramp operations schedule based on the request to modify the processing time of the at least one of the one or more inbound and outbound trains to generate one or more optimized ramp operations schedule options; visually indicating, on the intelligent GUI, the one or more optimized ramp operations schedule options; committing one of the one or more optimized ramp operations schedule options for execution; and automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause execution of the committed re-optimized ramp operations.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 as directed to non-statutory subject matter.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. In adhering to the 2019 PEG, Step 1 is directed to determining whether or not the claims fall within a statutory class. Herein, the claims fall within statutory class of process or machine or manufacture. Hence, the claims qualify as potentially eligible subject matter under 35 U.S.C §101. With Step 1 being directed to a statutory category, the 2019 PEG flowchart is directed to Step 2. Step 2 is the two-part analysis from Alice Corp. (also called the Mayo test). The 2019 PEG makes two changes in Step 2A: It sets forth new procedure for Step 2A (called “revised Step 2A”) under which a claim is not “directed to” a judicial exception unless the claim satisfies a two-prong inquiry. The two-prong inquiry is as follows: Prong One: evaluate whether the claim recites a judicial exception (an abstract idea enumerated in the 2019 PEG, a law of nature, or a natural phenomenon). If claim recites an exception, then Prong Two: evaluate whether the claim recites additional elements that integrate the exception into a practical application of the exception. The claim(s) recite(s) the following abstract idea indicated by non-boldface font and additional limitations indicated by boldface font:
A method of advanced scheduling and optimization of ramp operations of a hub based on an intelligent graphical user interface (GUI), the method comprising: displaying, on the intelligent GUI, a representation of an optimized ramp operations schedule over a period of time for one or more inbound and outbound trains scheduled to be processed at a hub over the period of time, wherein the representation of the optimized ramp operations schedule includes a graphical representation of a status of one or more production tracks of the hub over the period of time overlayed with a representation of the one or more inbound and outbound trains scheduled to be processed at the hub placed correspondingly to a time within the period of time at which the respective train is to be processed; receiving, via the intelligent GUI, a user request to modify a processing time of at least one of the one or more inbound and outbound trains in the optimized ramp operations schedule; re-optimizing, by a ramp operations optimization system, the optimized ramp operations schedule based on the request to modify the processing time of the at least one of the one or more inbound and outbound trains to generate one or more optimized ramp operations schedule options; visually indicating, on the intelligent GUI, the one or more optimized ramp operations schedule options; committing one of the one or more optimized ramp operations schedule options for execution; and automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause execution of the committed re-optimized ramp operations.
[or]
A system configured for advanced scheduling and optimization of ramp operations of a hub based on an intelligent graphical user interface (GUI), comprising: at least one processor; and a memory operably coupled to the at least one processor and storing processor-readable code that, when executed by the at least one processor, is configured to perform operations including: displaying, on the intelligent GUI, a representation of an optimized ramp operations schedule over a period of time for one or more inbound and outbound trains scheduled to be processed at a hub over the period of time, wherein the representation of the optimized ramp operations schedule includes a graphical representation of a status of one or more production tracks of the hub over the period of time overlayed with a representation of the one or more inbound and outbound trains scheduled to be processed at the hub placed correspondingly to a time within the period of time at which the respective train is to be processed; receiving, via the intelligent GUI, a user request to modify a processing time of at least one of the one or more inbound and outbound trains in the optimized ramp operations schedule; re-optimizing, by a ramp operations optimization system, the optimized ramp operations schedule based on the request to modify the processing time of the at least one of the one or more inbound and outbound trains to generate one or more optimized ramp operations schedule options; visually indicating, on the intelligent GUI, the one or more optimized ramp operations schedule options; committing one of the one or more optimized ramp operations schedule options for execution; and automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause execution of the committed re-optimized ramp operations.
[or]
A computer-based tool for advanced scheduling and optimization of ramp operations of a hub based on an intelligent graphical user interface (GUI), the computer-based tool including non-transitory computer readable media having stored thereon computer code which, when executed by a processor, causes a computing device to perform operations comprising: displaying, on the intelligent GUI, a representation of an optimized ramp operations schedule over a period of time for one or more inbound and outbound trains scheduled to be processed at a hub over the period of time, wherein the representation of the optimized ramp operations schedule includes a graphical representation of a status of one or more production tracks of the hub over the period of time overlayed with a representation of the one or more inbound and outbound trains scheduled to be processed at the hub placed correspondingly to a time within the period of time at which the respective train is to be processed; receiving, via the intelligent GUI, a user request to modify a processing time of at least one of the one or more inbound and outbound trains in the optimized ramp operations schedule; re-optimizing, by a ramp operations optimization system, the optimized ramp operations schedule based on the request to modify the processing time of the at least one of the one or more inbound and outbound trains to generate one or more optimized ramp operations schedule options; visually indicating, on the intelligent GUI, the one or more optimized ramp operations schedule options; committing one of the one or more optimized ramp operations schedule options for execution; and automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause execution of the committed re-optimized ramp operations.
Per Prong One of Step 2A, the identified recitation of an abstract idea falls within at least one of the Abstract Idea Groupings consisting of: Mathematical Concepts, Mental Processes, or Certain Methods of Organizing Human Activity. Particularly, the identified recitation falls within the Mental Processes including concepts performed in the human mind (including an observation, evaluation judgment, opinion). Per Prong Two of Step 2A, this judicial exception is not integrated into a practical application because the claim as a whole does not integrate the identified abstract idea into a practical application. The train, computing device, processor and/or memory medium is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing/transmitting data. This generic train, computing device, processor and/or memory medium limitation is no more than mere instructions to apply the exception using a generic computer component. Further, sending a control signal by a train, computing device, processor and/or memory medium is mere instruction to apply an exception using a generic computer component which cannot integrate a judicial exception into a practical application. Accordingly, this/these additional element(s) does/do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, since the claims are directed to the determined judicial exception in view of the two prongs of Step 2A, the 2019 PEG flowchart is directed to Step 2B. Therein, the additional elements and combinations therewith are examined in the claims to determine whether the claims as a whole amounts to significantly more than the judicial exception. It is noted here that the additional elements are to be considered both individually and as an ordered combination. In this case, the claims each at most comprise additional elements of: train, computing device, processor and memory medium. Taken individually, the additional limitations each are generically recited and thus does not add significantly more to the respective limitations. Further, sending a control signal by a train, computing device, processor and/or memory medium is mere instruction to apply an exception using a generic computer component which cannot provide an inventive concept in Step 2B (or, looking back to Step 2A, cannot integrate a judicial exception into a practical application). For further support, the Applicant’s specification supports the claims being directed to use of a generic computer/memory type structure at ¶0109 wherein “performed with a general-purpose processor”. Taken as an ordered combination, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations are directed to limitations referenced in Alice Corp. that are not enough to qualify as significantly more when recited in a claim with an abstract idea include, as a non-limiting or non-exclusive examples: i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
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ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 134 S. Ct. at 2359-60, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
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iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)); or
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v. Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook. The courts have recognized the following computer functions inter alia to be well-understood, routine, and conventional functions when they are claimed in a merely generic manner: performing repetitive calculations; receiving, processing, and storing data (e.g., the present claims); electronically scanning or extracting data; electronic recordkeeping; automating mental tasks (e.g., process/machine/manufacture for performing the present claims); and receiving or transmitting data (e.g., the present claims). The dependent claims do not cure the above stated deficiencies, and in particular, the dependent claims further narrow the abstract idea without reciting additional elements that integrate the exception into a practical application of the exception or providing significantly more than the abstract idea. Since there are no elements or ordered combination of elements that amount to significantly more than the judicial exception, the claims are not eligible subject matter under 35 USC §101. Thus, viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Rieppi (US 20140236957 A1) hereinafter referred to as Rieppi in view of Vujanic et al. (CA 3153593 A1) hereinafter referred to as Vujanic.
Rieppi teaches:
Claim 1. A method of advanced scheduling and optimization of ramp operations of a hub based on an intelligent graphical user interface (GUI), the method comprising:
displaying, on the intelligent GUI, a representation of an optimized ramp operations schedule over a period of time for one or more inbound and outbound trains scheduled to be processed at a hub over the period of time, wherein the representation of the optimized ramp operations schedule includes a graphical representation of a status of one or more production tracks of the hub over the period of time overlayed with a representation of the one or more inbound and outbound trains scheduled to be processed at the hub placed correspondingly to a time within the period of time at which the respective train is to be processed (¶0031 a traffic record may include a train's arrival date and time, single car volume, car cut volume, outbound classification, work classification (such as, but not limited to, regular connection, block swap, and the like), and departure date and time. In one embodiment of the invention, the car cut volume applies to groups of multiple cars. A dataset may further include inbound and outbound train plans and block classifications, such as jumbo, large or small, as discussed below, with respect to the block to track assignment process depicted in FIG. 11. FIGS. 5a and 5b depicts an example of a set of traffic records. ¶0034 Traffic record datasets may be maintained as a structured collection of data stored in a central data repository ¶0035 Traffic records may be accessed according to a specific date range. A date range is first determined or selected. After a date range is chosen, the traffic records that fall within the determined or selected date range are then selected. For example, a date range beginning on Jan. 1, 2012, and ending on Jan. 10, 2012 may be chosen. However, the dataset may only contain data for the 3rd, 6th, and 7th of January, 2012. Accordingly, only the traffic records for the 3rd, 6th, and 7th of January, 2012 may be selected and accessed from the traffic record dataset. That is, the resulting timeframe is identified on the basis of the dates selected. The traffic records are then sorted chronologically by date. FIGS. 5a and 5b depict an example of these traffic record);
receiving, via the intelligent GUI, a user request to modify a processing time of at least one of the one or more inbound and outbound trains in the optimized ramp operations schedule (¶0052 Referring to step 111 in FIG. 1, the traffic record dataset may be modified according to one or more business rules. Business rules allow rail terminals perform sensitivity analyses that model the differences in existing rail terminal traffic flow with projected or target traffic data. For example, business rules can be used to model the change in efficiency of rail terminal traffic flow caused by changing the average dwell time of that particular terminal and potentially in respect of a specific traffic type handled by that terminal. More specifically, if a particular group of traffic typically arrives at a rail terminal at 2:00 pm, and departs to a customer location at 8:00 pm, for a dwell period of 6 hours, the rail terminal may model the change in efficiency by decreasing the dwell time to 4 hours, or in other words, by departing at 6:00 pm, rather than 8:00 pm.);
re-optimizing, by a ramp operations optimization system, the optimized ramp operations schedule based on the request to modify the processing time of the at least one of the one or more inbound and outbound trains to generate one or more optimized ramp operations schedule options (¶0063 Referring to step 1103, switching parameters, i.e., railcar handling parameters, are defined for assigning blocks to tracks. Switching parameters, similarly to business rules, allow rail terminals to perform sensitivity analyses to determine an optimal number of classification tracks and track lengths required to meet the rail terminal's capacity needs. These parameters may include without limitation: volume threshold for large blocks; volume threshold for small blocks; a maximum number of cars to be held in a small block track; a maximum number of blocks to be held in a small block track; threshold for jumbo block overflow traffic; car footage; and a minimum classification track footage);
visually indicating, on the intelligent GUI, the one or more optimized ramp operations schedule options (¶0046 Generating graphical overviews of railcar inventory allows rail terminals to visually analyze and detect traffic congestion patterns. For example, a staircase-like succession of colored time periods that proceeds vertically down the traffic records and horizontally through successive time periods, as depicted in FIG. 8, is indicative of a fairly smooth development and processing of railcar inventory. Conversely, a group of colored time periods that grows both vertically (i.e., across traffic records), and horizontally (i.e., across time periods), is indicative of increasing traffic dwells, which in turn, indicates potential traffic congestion issues to the rail terminal. In another aspect of the invention, the graphical display may be controlled to filter the data that is conditionally formatted. For example, the graphical display may only color code traffic records with rail cars above a certain volume.);
committing one of the one or more optimized ramp operations schedule options for execution (¶0067 Referring to step 1106, each block from the block list created in step 1104 is assigned to a track from the track list created in step 1102 in order of descending average departing volume. For example, jumbo blocks are first assigned to jumbo tracks. Overflow volume from jumbo blocks that cannot fit on a single dedicated track are assigned to overflow tracks, as described below. Next, large blocks are assigned to regular tracks; because the number of railcars in a large block will not exceed the maximum number of cars that can fit in a single track, there is no need to assign overflow volume from large blocks. After assigning large blocks, small blocks and overflow jumbo block volume too small for dedicated tracks are assigned to small tracks); and
automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause execution of the committed re-optimized ramp operations (¶0069 Referring to step 1107, the block list and associated track assignment data is consolidated into a final track list. The final track list may include a list of blocks and their classifications. For example, the first track in the track list may be a jumbo track containing a jumbo block. The last track in the track list may be a small track, containing two small blocks and two cars of overflow volume from the jumbo block. Using the car footage parameter specified in step 1103, the amount of square footage needed to accommodate all the blocks in each track may be determined.).
Although not explicitly taught by Rieppi, Vujanic teaches in the analogous art of systems for operation of railway systems:
re-optimizing, by a ramp operations optimization system, the optimized ramp operations schedule based on the request to modify the processing time of the at least one of the one or more inbound and outbound trains (Page 17 As will be discussed, the model 55 (Figure 6) is stored in an electronic data source in the form of database 42. The model 55 defines locations in the network 21 allowing passing of trains such as sidings, and double tracks. The model also contains information as to paths for journeys of each of the trains, for example journeys for them to carry out haulage assignments. Railway system 20 also includes a scheduling machine 33 that is in communication with the data communication system 29 for receiving the state data. As will be discussed in more detail shortly, the scheduling machine 33 includes one or more processors 35 and an electronic memory 47 in communication with the processors 35. The electronic memory contains instructions for the processors 35 to effect a number of tasks as follows: access the model 55 of the railway network 21 stored in the electronic data source 42; apply the state data xt1,..,xtn to the model 44 to determine, at each of the respective times of the state data, controls associated with each trains' path for each of the trains la,...,1n. Page 29 Line 15 Figure 5, which are generated by scheduling machine 33 in response to the state reports xt1,..,xtn are generated at constant intervals of time At in the presently described embodiment. It should be realized though that this is not necessary and the procedure presented herein can be applied .. in ad-hoc contexts where arbitrary events, such as trains arriving late at a station, are used to trigger plan re-computations. Note that t represents global (continuous) time, while k in the previous section was an index of time expressed as an integer number of stages relative to the position of the system at the time it was instantiated.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the systems for operation of railway systems of Vujanic with the system for terminal capacity management of Rieppi for the following reasons:
(1) a finding that there was some teaching, suggestion, or motivation, either in the references themselves or in the knowledge generally available to one of ordinary skill in the art, to modify the reference or to combine reference teachings, e.g. Rieppi ¶0003 teaches that there is a need for simulation tools that can model traffic and congestion patterns of rail terminals still in their planning or development stages, on the basis of high-level historical or forecast data;
(2) a finding that there was reasonable expectation of success since the only difference between the claimed invention and the prior art being the lack of actual combination of the elements in a single prior art reference, e.g. Rieppi Abstract teaches determining rail terminal capacity needs, and Vujanic Abstract teaches a scheduling machine that accesses a model of the railway network that is stored in an electronic data source; and
(3) whatever additional findings based on the Graham factual inquiries may be necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness, e.g. Rieppi at least the above cited paragraphs, and Vujanic at least the inclusively cited paragraphs.
Therefore, it would be obvious to one skilled in the art at the time of the invention to combine the systems for operation of railway systems of Vujanic with the system for terminal capacity management of Rieppi. The rationale to support a conclusion that the claim would have been obvious is that "a person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and whether there would have been a reasonable expectation of success in doing so." DyStar Textilfarben GmbH & Co. Deutschland KG v. C.H. Patrick Co., 464 F.3d 1356, 1360, 80 USPQ2d 1641, 1645 (Fed. Cir. 2006). See MPEP 2143(G).
Rieppi teaches:
Claim 2. The method of claim 1, wherein the user request to modify the processing time of at least one of the one or more inbound and outbound trains includes utilizing sliding and dragging functionality within the intelligent GUI to change the processing schedule of the train (¶0035 Traffic records may be accessed according to a specific date range. A date range is first determined or selected. After a date range is chosen, the traffic records that fall within the determined or selected date range are then selected. For example, a date range beginning on Jan. 1, 2012, and ending on Jan. 10, 2012 may be chosen. However, the dataset may only contain data for the 3rd, 6th, and 7th of January, 2012. Accordingly, only the traffic records for the 3rd, 6th, and 7th of January, 2012 may be selected and accessed from the traffic record dataset. That is, the resulting timeframe is identified on the basis of the dates selected. The traffic records are then sorted chronologically by date. FIGS. 5a and 5b depict an example of these traffic records).
Rieppi teaches:
Claim 3. The method of claim 1, wherein visually indicating the one or more optimized ramp operations schedule options on the intelligent GUI includes enabling the user to cycle through the one or more optimized ramp operations schedule options to review potential impacts on the ramp operations schedule (¶0035 Traffic records may be accessed according to a specific date range. A date range is first determined or selected. After a date range is chosen, the traffic records that fall within the determined or selected date range are then selected. For example, a date range beginning on Jan. 1, 2012, and ending on Jan. 10, 2012 may be chosen. However, the dataset may only contain data for the 3rd, 6th, and 7th of January, 2012. Accordingly, only the traffic records for the 3rd, 6th, and 7th of January, 2012 may be selected and accessed from the traffic record dataset. That is, the resulting timeframe is identified on the basis of the dates selected. The traffic records are then sorted chronologically by date. FIGS. 5a and 5b depict an example of these traffic records ¶0036 Referring to step 101 in FIG. 1, once the traffic records have been accessed, traffic records are then discretized into smaller periodic time intervals. The process of discretizing each time interval is shown in more detail in steps 202-204 of FIG. 2. As FIG. 2 illustrates, after selecting traffic records within a specific date range, as step 202 shows, a traffic record is sorted chronologically, and then divided into periods of discrete time units, as shown in step 203.).
Rieppi teaches:
Claim 4. The method of claim 1, wherein committing one of the one or more optimized ramp operations schedule options for execution includes the ramp operations optimization system automatically selecting an optimized ramp operations schedule option based on predefined criteria (¶0064 a reduction in the volume threshold for large blocks would likely cause more blocks to be defined as "jumbo" blocks, which in turn, would cause more blocks to be distributed across multiple tracks, and therefore, raise the minimum number of tracks required to stage the railcar blocks. Accordingly, the specification parameters allow rail terminals to perform sensitivity analyses and optimize the minimum number of tracks and track sizes required to stage railcars at a rail terminal. Significantly, these sensitivity analyses do not require micro-simulation tools that typically involve resource-intensive virtual representations of terminals and tracks to perform a simulation. In this way, rail terminals may analyze the impact of various different switching parameters on rail terminal capacity needs in a timely and efficient manner).
Rieppi teaches:
Claim 5. The method of claim 1, wherein committing one of the one or more optimized ramp operations schedule options for execution includes allowing the user to select one of the optimized ramp operations schedule options via the intelligent GUI and then committing the selected option (¶0035 Traffic records may be accessed according to a specific date range. A date range is first determined or selected. After a date range is chosen, the traffic records that fall within the determined or selected date range are then selected. For example, a date range beginning on Jan. 1, 2012, and ending on Jan. 10, 2012 may be chosen. However, the dataset may only contain data for the 3rd, 6th, and 7th of January, 2012. Accordingly, only the traffic records for the 3rd, 6th, and 7th of January, 2012 may be selected and accessed from the traffic record dataset. That is, the resulting timeframe is identified on the basis of the dates selected. The traffic records are then sorted chronologically by date. FIGS. 5a and 5b depict an example of these traffic records).
Rieppi teaches:
Claim 6. The method of claim 1, further comprising: allowing the user to reject all of the one or more optimized ramp operations schedule options and maintain the original ramp operations schedule including the modification of the processing time of the at least one of the one or more inbound and outbound trains (¶0063 Referring to step 1103, switching parameters, i.e., railcar handling parameters, are defined for assigning blocks to tracks. Switching parameters, similarly to business rules, allow rail terminals to perform sensitivity analyses to determine an optimal number of classification tracks and track lengths required to meet the rail terminal's capacity needs. These parameters may include without limitation: volume threshold for large blocks; volume threshold for small blocks; a maximum number of cars to be held in a small block track; a maximum number of blocks to be held in a small block track; threshold for jumbo block overflow traffic; car footage; and a minimum classification track footage. The volume threshold for large blocks parameter specifies the maximum number of cars that may be held in a single classification track. Blocks with an average departing size exceeding such thresholds will be defined as "jumbo" blocks.).
Rieppi teaches:
Claim 7. The method of claim 1, wherein committing one of the one or more optimized ramp operations schedule options for execution includes sending a notification to execute the committed re-optimized ramp operations schedule during the timeframe represented by the schedule during operations (¶0052 Referring to step 111 in FIG. 1, the traffic record dataset may be modified according to one or more business rules. Business rules allow rail terminals perform sensitivity analyses that model the differences in existing rail terminal traffic flow with projected or target traffic data. For example, business rules can be used to model the change in efficiency of rail terminal traffic flow caused by changing the average dwell time of that particular terminal and potentially in respect of a specific traffic type handled by that terminal. More specifically, if a particular group of traffic typically arrives at a rail terminal at 2:00 pm, and departs to a customer location at 8:00 pm, for a dwell period of 6 hours, the rail terminal may model the change in efficiency by decreasing the dwell time to 4 hours, or in other words, by departing at 6:00 pm, rather than 8:00 pm).
As per claims 8-14 and 15-20, the system and computer-based tool tracks the method of claims 1-7 and 1-6, respectively, resulting in substantially similar limitations. The same cited prior art and rationale of claims 1-7 and 1-6 are applied to claims 8-14 and 15-20, respectively. Rieppi discloses that the embodiment may be found as a system and computer-based tool (Fig. 1 and ¶0045 The use of a computer processor to create hourly interval indexes, retrieve dwell occupancy values and calculate inventory capacity demand allows rail terminals to analyze terminal capacity needs quickly and efficiently).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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/KURTIS GILLS/Primary Examiner, Art Unit 3624