DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This is in reply to communication filed on 01/15/2026.
Claims 1, 5, 9, 13 and 17 have been amended.
Claims 2, 10 and 18 have been cancelled.
Claims 1, 3-9, 11-17 and 19 are currently pending and have been examined.
Response to Arguments
In response to Applicant Arguments /Remarks made in an amendment filled on 01/15/2026:
Claim Rejections - 35 USC § 112:
Due to claim amendments the claim rejections - 35 USC § 112 have been withdrawn.
Regarding 35 USC § 101 rejection:
Applicant argument submitted under the title “Rejection of Claims under $101” in pages 20-28.
Applicant's arguments have been fully considered but they are not persuasive.
In response, the examiner respectfully disagrees and emphasizes none of the receiving, collecting, generating, receiving, training, predicting, receiving, updating, predicting, determining, receiving, repeating, tracking, ensuring, transmitting, displaying, categorizing steps, whether taken individually or collectively, have not been shown to affect any form of technical change or improvement whatsoever, and are abstract idea. Applicant's claims have not been shown to modify, reconfigure, manipulate, or transform the computer, computer software, or any technical elements in any discernible manner, much less yield an improvement thereto. There is simply no showing of implementing any of the claim steps, individually or in combination, amounts to a technological improvement, nor the alleged “improvement in functionality of the computer” suggested by Applicant. Although Applicant asserts that “training a reinforcement learning algorithm (QL model) with a series of historical part personas, historical intents, historical OTDs” the Examiner first notes that managing on-time delivery (OTD) of a product in the manufacturing industry is not reasonably understood as a technology, but instead involves organizing of human activity, and recited a mental processes steps/limitations that can be performed in the human mind or by human using a pen and paper under the “Mental Processes” abstract idea grouping, as discussed below in the §101 rejection.
Moreover, automating the claims steps with a generic computer is similar to simply adding the words “apply it,” which is not enough to transform an abstract idea into eligible subject matter. See, Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976. Applicant's Specification acknowledges that nothing more than general purpose computers is needed to implement the invention. Thus, any improvement achieved by automating the claim steps (i.e., using generic computing devices/software) is not a technical improvement, but instead would come from the capabilities of a general-purpose computer rather than the sequence of steps/activities recited in the method itself, which does not materially alter the patent eligibility of the claim.
Furthermore, the amended claims recite “training a Q-Learning (QL) model, with (i) the plurality of historical part personas associated with each of a plurality of historical parts, (ii) the plurality of historical intents associated with each of the plurality of historical parts, and (iii) the plurality of historical OTDs of each of the plurality of historical parts;” which is claimed at a high level of generality without any specific algorithmic steps, model architecture, calibration, sensor fusion, tracking pipeline, latency reduction, or accuracy improvements (contrast McRO, Inc. v. Bandai, 837 F.3d 1299, where specific rules improved animation; and Enfish, LLC v. Microsoft, 822 F.3d 1327, where a specific data structure improved database operation).
Even assuming, for the sake of argument, that the claims amount to an improvement over prior art techniques for on-time delivery (OTD) of a product in the manufacturing industry, such an improvement would be considered, at most, an improvement confined within the abstract idea itself, which is not enough to confer eligibility on the claim. For the reasons above, Applicant’s argument is not persuasive.
Applicant’s remaining arguments either logically depend from the above-rejected arguments, in which case they too are unpersuasive for the reasons set forth above arguments.
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, 3-9, 11-17 and 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1:
Claims 1, 3-8 and 19 recite a method, which is directed to a process.
Claims 9 and 11-16 recite a system, which is directed to a machine.
Claim 17 recite a non-transitory computer readable medium, which is directed to a manufacture.
Therefore, each claim falls within one of the four statutory categories.
Step 2A, Prong 1 (Is a judicial exception recited?):
The independent claims 1, 9 and 17 recite the abstract idea of ensuring on-time delivery (OTD) of a product in the manufacturing industry, see specification [002]. This idea is described by the steps of:
receiving product details of the product and part details of each of a plurality of parts, wherein the plurality of parts being associated with a manufacturing process of the product;
collecting part particulars for each of the plurality of parts from an enterprise resource planner that stores and maintains records of the plurality of parts from respective client devices, wherein the part particulars for each of the plurality of parts comprising at least one of: supplier data, fulfillment data, buyer data, and inducing data, wherein the inducing data for each part includes a score of an associated supplier, a location risk factor of the associated supplier, on-time delivery score of the associated supplier, weather condition score of the associated supplier, a mode of transport used by the associated supplier, a travel distance from the associated supplier to a manufacturing company, wherein a score for each supplier is assigned, based on supplier's history in delivery punctuality;
generating a part persona for each of the plurality of parts, based on the part particulars corresponding to each of the plurality of parts;
predicting (i) an initial intent for each of the plurality of parts and (ii) an initial OTD for each of the plurality of parts, based on the part persona corresponding to each of the plurality of parts, wherein predict the initial intent and the initial OTD for each part, in prior, based on one or more influencing factors in a part influencing matrix associated with the part persona,
receiving, (i) a plurality of historical part personas associated with each of a plurality of historical parts, wherein the plurality of historical parts are further associated with a historical product (ii) a plurality of historical intents associated with each of the plurality of historical parts, and (iii) a plurality of historical OTDs of each of the plurality of historical parts, wherein the historical OTD of each of the plurality of historical parts is determined based on the corresponding historical intent; and
training a Q-Learning (QL) model, with (i) the plurality of historical part personas associated with each of a plurality of historical parts, (ii) the plurality of historical intents associated with each of the plurality of historical parts, and (iii) the plurality of historical OTDs of each of the plurality of historical parts;
predicting (i) the successive intent for each of the plurality of parts and (ii) the successive OTD for each of the plurality of parts, by:
a) receiving at least one of: (i) one or more initial conversations and (ii) one or more initial events, associated with each of the plurality of parts;
b) updating the part persona for each of the plurality of parts, based on: (i) the initial intent associated with each of the plurality of parts, (ii) the one or more initial conversations associated with each of the plurality of parts, (iii) the one or more initial events associated with each of the plurality of parts, to obtain a successive part persona for each of the plurality of parts, wherein based on the one or more initial conversations and/or the one or more initial events, a plurality of correlations corresponding to the part are changed and a correlation score for each correlation is again calculated using an entropy and information gain function, the part influencing matrix is updated with the resulted plurality of correlations along with the corresponding correlation scores, and the part persona for each of the plurality of parts is updated based on one or more high-influence correlations and the initial intent associated with the part;
c) predicting (i) a successive intent for each of the plurality of parts and (ii) a successive OTD for each of the plurality of parts, based on the successive part persona corresponding to each of the plurality of parts;
d) determining a successive OTD of the product, based on the successive OTD for each of the plurality of parts;
e) receiving at least one of: (i) one or more successive conversations and (ii) one or more successive events, associated with each part of the plurality of parts; and
f) repeating the steps (b) through (e), by taking at least one of: (i) the one or more successive conversations as the one or more initial conversations, associated with each part, and (ii) the one or more successive events as the one or more initial events associated with each part, until either (i) the one or more initial conversations or one or more successive conversations associated with each part are not present, or (ii) the one or more initial events or one or more successive events associated with each part are not present; [[and]]
continuously tracking conversations between suppliers and a manufacturing company by employing conversation analysis to monitor off-line processes of the suppliers that supply the parts, to track status of the parts at a plurality of levels and process control using unstructured supply chain conversations and using them with a plurality of datapoints collected from a plurality of systems, wherein the status of sourcing of the parts for manufacturing is controlled, even if the suppliers are isolated, and minimize issues that cause missing valuable manufacturing time, wherein applying entropy principles for the process control to improve accuracy of predictions;
ensuring meeting the OTD of the product, based on the initial OTD for each of the plurality of parts, wherein the OTD of the product is predicted continuously and the part persona for each of the plurality of parts is updated, whenever there is a post, a conversation, or an update about each of the plurality of parts, and further sent to enable generation of automated early alerts to correct part deficiencies and take one or more actions that minimize disruptions in the manufacturing process and ensure meeting the OTD of the product;
transmitting records associated with the manufacturing process upon receiving a request or query associated with the manufacturing process wherein the online resources handle delivery of messages including notifications of unscheduled items and completion messages; and
displaying, the records including a tracking information about the parts, and the part influencing matrix in response to requesting or querying, wherein the part influencing matrix for each part includes the plurality of correlations along with respective correlation scores,
wherein including an entity for product entropy defining an entropy value of the product which indicates status of the product, an entity actor including one of the supplier, or a buyer, or a supplier executive, or a delivery leader, or a source executive, providing an advisory through an entity advisory and providing a feedback in terms of positive or negative through an entity feedback based on the entropy value of the product and the actor provides the one or more actions through an entity action based on the advisory and the feedback, wherein defines a relation between the part persona, the initial intent, and the initial OTD of the part, wherein the graph-based data model are customizable with a plurality of edges and a plurality of nodes,
wherein the initial intent for each of the plurality of parts and the successive intent for each of the plurality of parts are assigned with unique ID and stored and logically accessed, categorizing the post as one of a promotor or a detractor based on the events generated from the feedback being positive and negative, and the feedback provide status of associated part through entities promotor or detractor, wherein the events are associated with the product, and each event is classified as one of reactive, proactive or adhoc through respective entities reactive, proactive and adhoc in the graph-based data model, and an entity result, indicates a status of the associated part as one of 'pending', 'delivered', 'yet to be shipped, is feedback through an entity event;
wherein the initial intent and the successive intent for each of the plurality of parts is predicted through thereby enabling creation of a centralized monitoring function for ensuring meeting the OTD of the product
a) These claims recite a certain method of organizing human activity. The claims recite to a certain method of organizing human activity as the above abstract idea limitations are directed to managing personal behavior or relationships or interactions between people.
The examiner finds the claims to simply recites steps of fundamental economic principles or practices to determine on time delivery (OTD) for a purchased item and ensure executing the delivery based on determined data. The Examiner additionally finds the claims to be similar to an example the courts have identified as being a certain method of organizing human activity as being old or well-known may indicate that the practice is fundamental. See, e.g., Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 219-20, 110 USPQ2d 1981-82 (2014) (describing the concept of intermediated settlement, like the risk hedging in Bilski, to be a "‘fundamental economic practice long prevalent in our system of commerce’" and also as "a building block of the modern economy") (citation omitted); Bilski v. Kappos, 561 U.S. 593, 611, 95 USPQ2d 1001, 1010 (2010) (claims to the concept of hedging are a "fundamental economic practice long prevalent in our system of commerce and taught in any introductory finance class.") (citation omitted); Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1313, 120 USPQ2d 1353, 1356 (Fed. Cir. 2016) ("The category of abstract ideas embraces ‘fundamental economic practice[s] long prevalent in our system of commerce,’ … including ‘longstanding commercial practice[s]’").
In addition, managing personal behavior or relationships or interactions between people of following rules or instructions to receive item information, collect further item information, generate item related data, predict delivery data, ensure item delivery. The Examiner additionally finds the claims to be similar to an example the courts have identified as being a certain method of organizing human activity: i. filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016) (finding that filtering content was an abstract idea under step 2A, but reversing an invalidity judgment of ineligibility due to an inadequate step 2B analysis); ii. considering historical usage information while inputting data, BSG Tech. LLC v. Buyseasons, Inc., 899 F.3d 1281, 1286, 127 USPQ2d 1688, 1691 (Fed. Cir. 2018); and iii. a mental process that a neurologist should follow when testing a patient for nervous system malfunctions, In re Meyer, 688 F.2d 789, 791-93, 215 USPQ 193, 194-96 (CCPA 1982).
Offending clauses include:
“training a Q-Learning (QL) model, with (i) the plurality of historical part personas associated with each of a plurality of historical parts, (ii) the plurality of historical intents associated with each of the plurality of historical parts, and (iii) the plurality of historical OTDs of each of the plurality of historical parts;”
b) The claims recite a mental process. Before computers one could mentally or a human using paper and pen to determine on time delivery (OTD) for a purchased item and ensure executing the delivery based on determined data. The claims are merely directed to receive item information, collect further item information, generate item related data, predict delivery data, ensure item delivery based on the generated and predicted data. The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer"). Mental processes recited in claims that require computers are explained further below with respect to point C. The Examiner find the recited claims to be similar to a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016), which the courts have also found to recite a mental process.
Step 2A, Prong 2 (Is the exception integrated into a practical application?):
This judicial exception is not integrated into a practical application because the claims satisfy the following criteria, which indicate that the claims do not integrate the abstract idea into practical application:
The claimed additional limitations are:
Claim 1: processor, one or more hardware processors of a prediction device, data model, trained intent and OTD prediction model, the trained intent and OTD prediction model is present in a prediction unit of the prediction device, an one or more client devices, an Input/Output interface of the prediction device, the prediction device is connected to the one or more client devices and online resources through a network, a conversation fluid algorithm which is obtained using a long short-term memory (LSTM) based network, artificial intelligence, data model is a graph-based data model, a historical repository,
Claim 9: a prediction device connected to one or more client devices and online resources, through a network, wherein the prediction device comprising: a memory storing instructions; one or more Input/Output (1/0) interfaces; and one or more hardware processors coupled to the memory via the one or more 1/0 interfaces, wherein the one or more hardware processors of the prediction device, data model, trained intent and OTD prediction model, the prediction device is connected to the one or more client devices and online resources through a network, a conversation fluid algorithm which is obtained using a long short-term memory (LSTM) based network, an artificial intelligence method, data model is a graph-based data model, a historical repository,
Claim 17: a computer program product comprising a non-transitory computer readable medium having a computer readable program embodied therein, wherein the computer readable program, when executed on a computing device, prediction device, a data model, a trained intent and OTD prediction model, an one or more client devices, the one or more hardware processors of a prediction device, an Input/Output interface, the prediction device is connected to the one or more client devices and online resources through a network, data model is a graph-based data model, a conversation fluid algorithm which is obtained using a long short-term memory (LSTM) based network, an artificial intelligence method, a historical repository,
The additional limitations are directed to using a generic computer to process information and perform the abstract idea. Therefore, the limitations merely amount to adding the words “apply it” (or an equivalent) to the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f).
Claims 1, 9 and 17: recitation of “training a Q-Learning (QL) model, with (i) the plurality of historical part personas associated with each of a plurality of historical parts, (ii) the plurality of historical intents associated with each of the plurality of historical parts, and (iii) the plurality of historical OTDs of each of the plurality of historical parts;” is claimed at a high level of generality without any specific algorithmic steps, model architecture, calibration, sensor fusion, tracking pipeline, latency reduction, or accuracy improvements (contrast McRO, Inc. v. Bandai, 837 F.3d 1299, where specific rules improved animation; and Enfish, LLC v. Microsoft, 822 F.3d 1327, where a specific data structure improved database operation).
Step 2B (Does the claim recite additional elements that amount to significantly more that the judicial exception?):
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As for Step 2B analysis, knowing the consideration is overlapping with Step 2A, Prong 2. The Step 2B considerations have already been substantially addressed under Step 2A Prong 2, see Step 2A Prong 2 analysis above. As discussed above, the additional imitations amount to adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f).
In addition, the dependent claims recite:
Step 2A, Prong 1 (Is a judicial exception recited?):
Dependent claims 3-8, 11-16 and 19 recitations further narrowing the abstract idea recited in the independent claims 1, 9 and 17 and therefore directed towards the same abstract idea.
Step 2A, Prong 2 and Step 2B:
The dependent claims 3-8, 11-16 and 19 further narrow the abstract idea recited in the independent claims 1, 9 and 17 and are therefore directed towards the same abstract idea.
The dependent claims recite the following additional limitations:
Claim 4: the one or more client devices,
Claim 5: the trained intent and OTD prediction model, repository,
Claims 11, 15, 16: the one or more hardware processors of the prediction device,
Claim 12: the one or more hardware processors of the prediction device, the one or more client devices,
Claim 13: the one or more hardware processors of the prediction device, the trained intent and OTD prediction model, repository,
Claim 19: prediction device, , software or hardware capabilities of the one or more client devices,
However, the examiner finds each of these additional elements to be directed to merely “apply it” or applying a generic technology to perform the recited abstract idea of determine on time delivery (OTD) for a purchased item and ensure executing the delivery based on determined data, the recitation to the generic computer technology that is being used as a tool to execute the steps that define the abstract idea do not provide for integration at the 2nd prong and do not provide for significantly more at step 2B.
Therefore, the limitations on the invention of claims 1, 3-9, 11-17 and 19, when viewed individually and in ordered combination are directed to in-eligible subject matter.
Distinguished Over Prior Art
The claims 1, 3-9, 11-17 and 19, in present form, have overcome the prior art rejections and the examiner has been unable to find the claimed limitations in the prior art. Accordingly, the examiner recommends addressing the outstanding rejections above. The reason to withdraw the 35 USC 103 rejection of claims 1, 3-9, 11-17 and 19 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention.
Conclusion
1. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
2. Any inquiry concerning this communication or earlier communications from the examiner should be directed to AVIA SALMAN whose telephone number is (313)446-4901. The examiner can normally be reached on Monday thru Friday; 9:00 AM to 5:00 PM EST.
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/AVIA SALMAN/Primary Patent Examiner, Art Unit 3627