DETAILED ACTION
Status of the Application
This communication is a Final Action for Application 18/766,652. In response to Examiner’s action mail dated September 10, 2025, Applicant submitted arguments and amendments mail dated November 27, 2025. Applicant amended claims 1 and 6. Applicant cancelled claim 2. Applicant added new claims 7-10. Claims 1, 3-10 are pending.
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 . 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.
Information Disclosure Statement
Applicant did not submit an information disclosure statement (IDS) to be considered by the examiner.
Response to Amendments
Applicant’s amendments have been considered. Applicant amended claims 1 and 6. Applicant cancelled claim 2. Applicant added new claims 7-10. Claims 1, 3-10 are pending.
Regarding the 35 U.S.C. 101, the Applicant’s amendments are not persuasive. The claims 1, 3-10 are not patent eligible under 35 U.S.C. 101, see below.
Regarding the 35 U.S.C 103 rejection. Applicant. Claims 1, 3-10 are rejected under 35 U.S.C 103, see below.
Response to Arguments
Applicant’s arguments filed November 27, 2025 have been fully considered but they are not persuasive and/or moot in view of the revise rejections. Applicant’s argument will be considered herein below.
Rejection of claims under 35 U.S.C. 101
On pages 5-7, of the Applicant’s 35 U.S.C. 101 arguments, Applicant traverses Examiner rejection. Applicant respectfully submits that the combination of the calculation being performed using two different set of variables depending on the amount of time data is collected provides an improvement in the functioning of the computer itself by facilitating early implementation followed by increased accuracy once data is collected for a certain amount of time.
Applicant explains it takes time to collect information necessary for determining personal trait(s) TA of the worker WKx. A certain time is required for the relationship Rxy to be constructed, and the reliability of the information on the relationship Rxy is considered low until the certain time elapses. Applicant explains it is expected that the accuracy of the calculation of the relationship level RLxy is increased by using the personal trait TA as the variable of the calculation of the relationship level RLxy citing instant specification [030]-[031]. Applicant explains once determined the personal trait data provides improved accuracy for the relationship level. The combination of early implementation along with improved accuracy clearly represents an improvement to the functioning of the computer itself.
For the reasons set forth, Applicant submits claim 1 is directed to patent eligible subject matter. Accordingly, reconsideration and withdrawal of the rejection of claim 1, as being directed to non-statutory subject matter, are respectfully requested.
Examiner respectfully disagrees with Applicant’s claim 1 arguments regarding patent eligibility. The claims are collecting personal trait data and relationship level data (i.e., Wky, WKx, TA, Rxy, RLxy, AT) for a duration to construct a reliability of information to improve the accuracy for the relationship level for scheduling purposes. Collecting data to complete calculations that formulates a relationship is a mathematical concept. The improvement of the accuracy of data, here relation level, is an improvement to the abstract idea. Similarly, observation of performance of a work is a mental concept – evaluation, observation, and judgement. The claim 1 is a mental concept at Step 2A prong one.
At Step 2A prong 2, the claims are evaluated to determine if the abstract idea is integrated into a practical application. To determine if the abstract idea is integrated into a practical application, the integration of the abstract idea and the additional elements are evaluated, and the claims are evaluated for an improvement to the functioning of the computer itself.
In the instant application, the simulation data is real space data are considered to determine work patterns. In the Application, the claims recite the additional elements: a simulation system, a database, and a processing circuitry. As recited, the claims are using the computers systems to collected the real space data. The real space data is used in the calculation of the abstract idea – determining /constructing relationship level between workers to improve the schedule. The claims are using a computer to gather the information and conduct a calculation. Therefore, the claims are adding the words “applying 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 – See MPEP 2106.05 (f). The claims are not improving the functioning of the database of simulation system. The limitations are not indicative of integration into a practical application.
At Step 2B, the claims are not indicative of integration into a practical application. The claims are not improving the functioning of a computer or any other technology or technical field. Here, the claims are using the computer to gather real-time data, calculating a relationship, and improving the data – compatibility data among workers to improve the schedule. The claims are not improving the functioning of the computer, database, or simulations system. The claims are improving the accuracy of the data output of the simulation system. So, the claims are not patent eligible.
Applicant submits claims 3-5 depend from claim 1, recite additional features and are directed to patent eligible subject matter for a least the reasons set forth above with respect to claim 1 and/or for the additional features recited.
Because claims 3-5 depend on claim 1, see Examiner’s explanation for claim 1 above.
Applicant submits claim 6 is directed to patent eligible subject matter for reasons analogous to those set forth with respect to claim 1. Accordingly, reconsideration and withdrawal of the rejection of claim 6, as being directed to non-statutory subject matter, are respectfully requested.
Because claim 6 is analogous to claim 1, see Examiner’s explanation for claim 1 above.
Rejection of claims under 35 U.S.C. 102
On pages 7-8, of the Applicant’s 35 U.S.C 102 arguments, Applicant traverses Examiner’s prior rejection. Applicant submits Examiner has failed to identify where all of the elements of claim are described by the applied reference citing W. L. Gore.
Applicant submits that Wayne (US 2024/0,020,756) fails to explicitly or inherently disclose two different types of calculations as disclosed in claim 1. Accordingly, Applicant is requesting, reconsideration and withdrawal of the rejection of claim 1, as being anticipated by Wayne.
Examiner respectfully disagrees with Applicant’s prior art arguments. The Applicant’s amendments necessitate grounds for a new rejection. Particularly, the Applicant amended the claims limitations to include a second calculation. See prior art rejection below.
On page 8 of the Applicant’s prior art arguments, Applicant traverses Examiner’s prior art rejection for claims 3-5. Applicant submits, because claims 3-5 depend from claim 1, for the reasons set forth with claim 1, the claims should be reconsidered and Examiner should withdrawal the rejection.
Examiner respectfully disagrees with Applicant’s prior art arguments. The Applicant’s amendments necessitate grounds for a new rejection. Particularly, the Applicant amended the claims limitations to include a second calculation. See prior art rejection below.
On page 8 of the Applicant’s prior art arguments, Applicant traverses Examiner’s prior art rejection for claims 6. Applicant submits, because claim 6 is analogous to claim 1, for the reasons set forth with claim 1, the claim 6 rejection should be reconsidered. Applicant submits, Examiner should withdraw the claim 6 rejection.
Examiner respectfully disagrees with Applicant’s prior art arguments. The Applicant’s amendments necessitate grounds for a new rejection. Particularly, the Applicant amended the claims limitations to include a second calculation. See prior art rejection below.
New Claims
On page 8 of the Applicant’s arguments, the Applicant discusses the new claims 7, 8, 9, and 10.
Examiner respectfully acknowledges the Applicant’s discussion of the new claims. Because the claims are new, the claims are considered in the rejection. See below.
Claim Rejections - 35 USC § 112, First Paragraph
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 8 and 10 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 8 (and similarly claim 10) recites, “… captured by a wearable sensor worn by each of the multiple workers.” However, Applicant’s specification does not in expressly or inherently require, “… captured using a wearable sensor …,” as required by the claims.
In order to satisfy the written description requirement, each claim limitation must be expressly or inherently supported by the disclosure. MPEP 2163 (emphasis added). “The 'written description' requirement implements the principle that a patent must describe the technology that is sought to be patented; the requirement serves both to satisfy the inventor's obligation to disclose the technologic knowledge upon which the patent is based, and to demonstrate that the patentee was in possession of the invention that is claimed.” Capon v. Eshhar, 76 USPQ2d 1078, 1084 (Fed. Cir. 2005) (emphasis added). Further, the written description requirement promotes the progress of the useful arts by ensuring that patentees adequately describe their inventions in their patent specifications in exchange for the right to exclude others from practicing the invention for the duration of the patent's term. See MPEP 2163 (emphasis added).
For claims directed toward computer-implemented functions, like the presently claimed invention, “[i]f the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention including how to program the disclosed computer to perform the claimed function, a rejection under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, for lack of written description must be made.” MPEP 2161.01 (emphasis added). It is not enough that one skilled in the art could write a program to achieve the claimed function because the written description requirement requires that the specification explains how the inventor intends to achieve the claimed function. Examining Claims for Compliance with 35 USC 112(a) - PowerPoint of Computer Based Training, Slides 20 & 21, (emphasis added) available at http://www.uspto.gov/ sites/default/files/documents/uspto_112a_ part1_17aug2015.pptx. The ability of one skilled in the art to make and use the claimed invention does not satisfy the written description requirement if details of how the function is to be performed are not disclosed. Id. at Slide 20.
With respect to the recitation of “…captured by a wearable sensor worn by each of the multiple workers …,” the specification does not expressly or inherently require that captured using a wearable sensor.
In various portions of the specification, the specification discusses, “The vital data VT_H is acquired from, for example, a measurement tool worn by the worker WKx.” See specification [0041]. That is, the specification discloses a measurement tool worn by the worker. Accordingly, although the specification discloses a measurement tool worn by the worker, the specification does not expressly or inherently require “re captured by a wearable sensor worn by each of the multiple workers,” as claimed.
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, 3-5, 7-8 is/are process.
Claims 6, 9-10 is/are manufacture.
The claims (claim 1, similarly claims 6) recite “… in which data of multiple workers arranged in a work line of a real space; and … on a work line … corresponding to that of the real space based on data of a work plan in the work line of the real space and data stored … , wherein the data of the multiple workers stored in the database includes data of personal attributes of the multiple workers, data of personal traits of the multiple workers and data of a personal relationship level between two workers included in the multiple workers, the data of a personal relationship level is: calculated based solely on the data of the personal attributes prior to collecting the data of personal traits for a certain amount of time, and calculated based on the data of the personal attributes and the data of the personal traits once the data of the personal traits is collected for the certain amount of time, wherein the data of the work plan in the work line of the real space includes data of work contents of works scheduled to be performed in the work line of the real space, wherein, in the simulation, the processing circuitry is configured to search for an assignment pattern of workers satisfying a reference condition in which a work efficiency in a whole work line of the digital space is equal to or greater than a target value, based on the data of the work contents of works to be performed and data related to the personal relationship level between the two workers...”. Claims 1, 3-10 in view of the claim limitations, recite the abstract idea of collecting personal trait data and relationship level data (i.e., Wky, WKx, TA, Rxy, RLxy, AT) for a duration to construct a reliability of information to improve the accuracy for the relationship level for scheduling purpose. These limitations are collecting data to complete calculations that formulates a relationship is a mathematical concept, and thus, the claims are directed to an abstract concept at step 2A prong one.
Furthermore, the claims recite search for an assignment pattern of workers satisfying a reference condition in which a work efficiency in a whole work line, observation of performance of a work is a mental concept – evaluation, observation, and judgement. The claim 1 is a mental concept at Step 2A prong one.
This judicial exception is not integrated into a practical application under the second prong of Step 2A Prong 2. In particular, the claims recite the additional elements beyond the recited abstract idea of, “A simulation system, comprising: a database in which data of multiple workers arranged in a work line of a real space; and a processing circuitry configured to execute a simulation on a work line of a digital space”, in claim 1; “… A non-transitory computer-readable medium storing a simulation program, the simulation program causing a computer to execute a simulation in a work line of a digital space corresponding to a work line of a real space ..”, in claim 6; however, when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, each of the additional elements are computing elements recite 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 – see MPEP 2106.05 (f).
The additional elements in the dependent claims that are not recited in the independent claims are:
Claim 8: a wearable sensor
Claim 10: a wearable sensor
Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims also fail to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the additional elements when considered both individually and as an ordered combination do not amount to significantly more. (See MPEP 2106.05 (f) – mere instructions to Apply an Exception.
At step 2B, it is MPEP 2106.05 (d) – Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information).
Dependent claims 3-5, 7-8 further narrow the abstract idea of independent claim 1.
Dependent claims 9-10 further narrow claim 6.
Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 3-5, 7-8 & 9-10 do not transform the recited abstract idea into a patent eligible invention because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea.
Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1, 3-10 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
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, 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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 3-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wayne (US 20240020756 A1) in view of Sethre (US 2020/0394538 A1) and Ikuta (JP 2019003392a).
Regarding Claim 1, (Currently Amended)
A simulation system, comprising: a database in which data of multiple workers arranged in a work line of a real space; and a processing circuitry configured to execute a simulation on a work line of a digital space corresponding to that of the real space based on data of a work plan in the work line of the real space and data stored in the database, wherein the data of the multiple workers stored in the database includes data of personal attributes of the multiple workers, data of personal traits of the multiple workers and data of a personal relationship level between two workers included in the multiple workers, the data of a personal relationship level is: ….
Wayne [058] discloses … non-transitory computer readable medium storing instructions for bootstrap scheduling.; Wayne [050] discloses the bootstrap circuit is structured to: match the first employee to a second employee via querying one or more databases based at least in part on the employee data; retrieve historical schedule data associated with the second employee via querying the one or more databases; extract a schedule trend from the historical schedule data; identify a portion of the historical schedule data corresponding to the extracted schedule trend; and generate, based at least in part on the identified portion, schedule data corresponding to the first employee. The schedule data provisioning circuit is structured to transmit the schedule data.
Wayne [076] discloses different incentives for the same shift may be offered to different workers. In embodiments, differences in offered incentives may be based on worker properties. For example, a high-level or more senior worker may be offered a better incentive than a lower ranked, newer worker. In embodiments, an AI or a manager may provide feedback regarding a worker's performance of a task, e.g., timeliness, accuracy, etc., which may, in turn, affect the worker's rating.
Thus, Wayne teaches matching a schedule (a relationship) between two workers. Wayne teaches a hierarchy between workers and performance traits (e.g., timeliness, accuracy), Wayne [050], [076].
Wayne discloses employee interactions may include properties that are linked with specific employees or groups of employees such as interaction ratings between employees, including managers, who would be working together. Interaction ratings may indicate how well employee combinations get along, whether they work well together, duplication of skill sets, roles, and the like. Interaction ratings may be based at least on a score, range, scale, or the like., Wayne [0427].
Although highly suggested, in Wayne, Examiner relies on Sethre to teach:
… calculated based solely on the data of the personal attributes prior to collecting the data of personal traits for a certain amount of time, and calculated based on the data of the personal attributes and the data of the personal traits once the data of the personal traits is collected for the certain amount of time, …
Sethre teaches training, based on personal attributes of employees of multiple employers and work culture attributes associated with each employer of the multiple employers, an employee-employer compatibility model that defines associations between the personal attributes and the work culture attributes Sethre [005].
Sethre teaches machine learning algorithm 218 is provided personal attributes of employees of multiple employers and work culture attributes associated with each employer of the multiple employers as input, and is executed by model generator 216 to generate the employee-employer compatibility model. Personal attributes of employees may include characteristics or personality traits of an individual. Some examples of personal attributes include: loyalty, commitment, honesty, enthusiasm, reliability, positive self-esteem, sense of humor, motivation, adaptability, etc. Work culture attributes are directed to the character and personality of the enterprise. Some examples of work culture attributes include: fairness, environment of collaboration, encouragement of employee engagement, learning opportunities, good communication, opportunities for growth, etc., Sethre [030].
Sethre teaches ML model generator 216 may also include a machine learning (ML) application that implements the ML algorithm to the employee-employer compatibility model. When the ML algorithm is implemented, it may find patterns personal attributes of employees and work culture attributes of enterprises to map the personal attributes to the work culture attributes, and output a model that matches qualified candidates with enterprises, where the candidates are compatible with the company culture of the enterprise., Sethre [031]
Examiner submits, the applicant’s limitations recite a certain amount of time. The Applicant is encouraged to clarify the certain amount of time as supported by the specification. Examiner interprets a certain amount of time as any duration, including one second which is long enough to collected a data point. Since Sethre collected data, the limitation of certain amount of time is taught.
Wayne teaches methods for enabling workers to compete for currently upcoming shifts. Sethre teaches a platform that considers personal attributes of employees. It would have been obvious to combine before the effective filing date, linking specific employees or groups who would work together, as taught by Wayne, with using a machine learning model to match qualified candidates, where the candidates are compatible with the company culture, provide better matches for candidates and employers., Sethre [040].
wherein the data of the work plan in the work line of the real space includes data of work contents of works scheduled to be performed in the work line of the real space, wherein, in the simulation, the processing circuitry is configured to search for an assignment pattern of workers satisfying a reference condition in which a work efficiency in a whole work line of the digital space is equal to or greater than a target value, based on the data of the work contents of works to be performed and data related to the personal relationship level between the two workers.
Wayne [0103] discloses embodiments may use historic data, e.g., the inputs for a given scheduling scenario, the configuration of the agglomerate scheduling network used, the precited results, and/or actual results to generate an agglomerate network model. In embodiments, experiments may be run on the model to see if proposed changes to the network might result in improved performance metrics prior to deployment of any changes to the network., Wayne [0103], [076]-[077], [106] Examiner submits, experiments are scenarios/ simulations.
Wayne [0385] discloses the database may be associated with the first entity 270120 and/or the second entity 270128. For example, embodiments of the current disclosure may retrieve information from the database such as, but not limited to: a number of hours worked by an employee; a skill set possessed by an employee; a performance evaluation (which may be in the form of a score, e.g., “high performer”, “satisfactory performer”, and/or “needs improvement”); physical limitations, e.g., a lifting weight limit; and/or the like. Further non-limiting examples of constraint data 270234 include data corresponding to a minimum wage per hour, a minimum amount of pay, an amount of overtime, and the like, Wayne [0385]. Examiner submits a performance evaluation (which may be in the form of a score, e.g., “high performer”, “satisfactory performer”, and/or “needs improvement”) are measured values, thresholds/ target values.
Further, Wayne [0498] discloses the method includes generating a plurality of schedules for a plurality of targets using different configurations of an agglomerate network, determining a performance score of the plurality of schedules, and identifying configurations of the agglomerate network and targets with schedules above a performance score/threshold., Wayne [0498]. Examiner submits a performance score are measured values, thresholds/ target values.
Wayne [0383] discloses the apparatus 270100 may further include a constraint identification circuit 270210 structured to determine 270220 constraint data 270234 corresponding to the employee. Non-limiting examples of constraint data 270234 include: maximum number of hours available to work in a day, week, month, year, etc.; physical limitations, excluded time periods, e.g., no morning shifts, no evening shifts, etc.; a maximum amount of pay per day, year, month, year, etc.; crew rest requirements; employee(s) that must be co-workers; employee(s) that must be avoided, etc., Wayne [0383] teaches crew tests, and thus, Wayne discloses relationship level between the two workers.
Ikuta further teaches:
… wherein the data of the work plan in the work line of the real space includes data of work contents of works scheduled to be performed in the work line of the real space, wherein, in the simulation, the processing circuitry is configured to search for an assignment pattern of workers satisfying a reference condition in which a work efficiency in a whole work line of the digital space is equal to or greater than a target value, …
Ikuta teaches comparing the required work capacity and the actual work capacity for each of the plurality of time periods, and when there is a time period when the actual work capacity is insufficient with respect to the required work capacity, the work schedule of at least one worker A work schedule creation method. Ikuta [p.1]; When there are a plurality of time zones in which the actual work capacity is sufficient with respect to the requested work capacity of the shift destination, the time zone with the smallest time difference from the break time defined in the work schedule of the worker is selected. [p.1]; Based on a production schedule in a manufacturing facility, a required work capability calculation unit that calculates a required work capability required for work for the manufacturing facility for each of a plurality of time zones, and Based on the work schedule of each worker and the production schedule, a work schedule creation unit that creates a work schedule for performing work on the manufacturing facility; Based on the work schedule and the work ability of each individual worker, an actual work ability calculation unit that calculates the work ability combined with the work ability of a plurality of workers for each of the plurality of time zones; Comparing the required work capacity and the actual work capacity for each of the plurality of time periods, and when there is a time period when the actual work capacity is insufficient . Ikuta [p.2].
Wayne teaches methods for enabling workers to compete for currently upcoming shifts. Ikuta teaches creating a schedule for a manufacturing facility. It would have been obvious to combine before the effective filing date, linking specific employees or groups who would work together, as taught by Wayne, with actual work capacity and with respect to the required work capacity, as taught by Ikuta, where the candidates are compatible with the company culture, to create a work schedule which can suppress the manufacture stop of a manufacturing facility., Sethre [p.2]
Regarding Claim 2 - Cancelled
Regarding Claim 3, (Original)
The simulation system according to claim 1, wherein the data of the work contents of the works to be performed includes data of a level of a relevance of the work contents performed by each of the two workers, and wherein, in the simulation, the processing circuitry is further configured to set a personal relationship level required in the work to be performed for each of the works to be performed based on the data of the level of relevance, and wherein, in the simulation, the search for the assignment pattern of the workers is executed based on the personal relationship level between the two workers and a personal relationship level required in the work to be performed.
See claim 1. Wayne [0383] teaches crew tests, and thus, Wayne discloses relationship level between the two workers., See Wayne [0383], [0498].
Regarding Claim 4, (Original)
The simulation system according to claim 1, wherein the processing circuitry further configured to execute staff assignment processing to arrange workers in the work line of the real space, wherein, in the staff assignment processing, the processing circuitry is configured to select multiple workers to be arranged in the work line of the real space by referring to data of a schedule of the workers scheduled to be arranged in the work line of the real space by using a search result by the simulation.
Wayne [0499] discloses an embodiment of the Autonomous Agglomerated Resource Utilization Modeler, as described herein, may utilize correlated agglomerated models to produce improved shift work schedules that balance both implicit and explicit quality parameters. Such embodiments may optimize quality parameters across one or more hierarchical agglomerated scheduling models.
Wayne [0500] discloses Other use cases include optimizing a schedule for one or more of: 1) benefits to education, e.g., experienced employee with several new employees, or maximize cross-training across skills/departments; 2) benefits to environment, e.g., maximize at least one of ridesharing, bike/walk to work, public transportation, etc., and/or maximize the percent of resources (used by those scheduled tasks/people) that are renewable; 3) benefits to utilities bills, e.g., certain jobs/skills may use more resources (electric/gas) and can be scheduled for when those rates are predicated to be lower, and/or to maximize the percent of resources that are renewable; 4) schedule to maximize throughput, e.g., right before an estimated peak demand it may be optimal to have the most efficient employees there; and/or 5) amount of system resources to be used generating schedules, e.g., if need extra resources, e.g., virtual machines, are needed to generate a particular schedule, it may be optimal to generate the schedule at off-peak times and/or during better rates.
Regarding Claim 5, (Original)
The simulation system according to claim 4, wherein, when the search result obtained by the simulation includes two or more patterns of assignment patterns of workers satisfying the reference condition, the staff assignment processing executes the reference using data of the schedule of the workers to be arranged in order from an assignment pattern of a worker having a high work efficiency in the whole work line.
See claim 4. Wayne [0499]-[0500]. For example, Wayne [0500] discloses schedule to maximize throughput, e.g., right before an estimated peak demand it may be optimal to have the most efficient employees there.
Regarding Claim 6, (Currently Amended)
A non-transitory computer-readable medium storing a simulation program, the simulation program causing a computer to execute a simulation in a work line of a digital space corresponding to a work line of a real space, wherein, in the simulation, an assignment pattern of workers satisfying a reference condition that a work efficiency in a whole work line of the digital space is equal to or more than a target value is searched for based on data of work contents of works scheduled to be performed in the work line of the real space and data of a personal relationship level between two workers included in multiple workers arranged in the work line of the real space, the data of the work contents being calculated based on data related to personal attributes of the multiple workers.
Wayne [058] discloses … non-transitory computer readable medium storing instructions for bootstrap scheduling.; Wayne [050] discloses the bootstrap circuit is structured to: match the first employee to a second employee via querying one or more databases based at least in part on the employee data; retrieve historical schedule data associated with the second employee via querying the one or more databases; extract a schedule trend from the historical schedule data; identify a portion of the historical schedule data corresponding to the extracted schedule trend; and generate, based at least in part on the identified portion, schedule data corresponding to the first employee. The schedule data provisioning circuit is structured to transmit the schedule data.
Wayne [076] discloses … a high-level or more senior worker may be offered a better incentive than a lower ranked, newer worker. … an AI or a manager may provide feedback regarding a worker's performance of a task, e.g., timeliness, accuracy, etc., which may, in turn, affect the worker's rating.
Wayne [0103] discloses embodiments may use historic data, e.g., the inputs for a given scheduling scenario, the configuration of the agglomerate scheduling network., Wayne [0103], [076]-[077], [0105]-[0106] Examiner submits, experiments are scenarios/ simulations.
At Wayne [0385], Examiner submits a performance evaluation (which may be in the form of a score, e.g., “high performer”, “satisfactory performer”, and/or “needs improvement”) are measured values, thresholds/ target values.
At Wayne [0498], Examiner submits a performance score are measured values, thresholds/ target values.
At Wayne [0383], teaches crew tests, and thus, Wayne discloses relationship level between the two workers.
Although highly suggested in Wayne, Examiner relies on Sethre to teach:
calculated based solely on data related to personal attributes of the multiple workers prior to collecting the data of personal traits for a certain amount of time, and calculated based on the data of the personal attributes and the data of the personal traits once the data of the personal traits is collected for the certain amount of time.
Sethre [030]- [031].
Examiner submits, the applicant’s limitations recite a certain amount of time. The Applicant is encouraged to clarify the certain amount of time as supported by the specification. Examiner interprets a certain amount of time as any duration, including one second which is long enough to collected a data point. Since Sethre collected data, the limitation of certain amount of time is taught.
Wayne teaches methods for enabling workers to compete for currently upcoming shifts. Sethre teaches a platform that considers personal attributes of employees. It would have been obvious to combine before the effective filing date, linking specific employees or groups who would work together, as taught by Wayne, with using a machine learning model to match qualified candidates, where the candidates are compatible with the company culture, provide better matches for candidates and employers., Sethre [040].
Claim(s) 7, 8, 9, 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wayne (US 2024/0,020,756 A1) in view of Sethre (US 2020/0394538 A1) and Ikuta (JP 2019003392a) and in further of Amsallem (US 12, 390, 171).
Regarding Claim 7, (New) [and similarly claim 9]
The simulation system according to claim 1, wherein the data of personal traits relates to personality or sociability of the multiple workers, and the data of personal attributes relates to position, work tenure, or type of employment.
See claim 1 rejection for system and personal traits.
Amsallem teaches a wrist wearable device monitoring health information using new qualitative descriptor of the user's physiological state without displaying a numeric score representing the user's physiological state. (A5) In some embodiments of any of (A3)-(A4), the user interface object is a first user interface object, and the displaying the user interface object also includes displaying a second user interface object that, when selected, causes the wrist-wearable device to schedule a future performance of the activity. (A6).
Wayne teaches methods for enabling workers to compete for currently upcoming shifts. Amsallem teaches monitoring physiological parameter for a user wearing the wrist-wearable device. It would have been obvious to combine before the effective filing date, linking specific employees or groups who would work together, as taught by Wayne, with using a machine learning model to match qualified candidates , comparing the values for the plurality of physiological parameters to baseline values for the physiological parameters, as taught by Amsallem, to easily and quickly understand to inform their day-to-day activity choices and goals., Amsallem [column 1 lines 38-40].
Regarding Claim 8, (New) [and similarly claim 10]
The simulation system according to claim 1, wherein the data of each of the multiple workers is captured using a wearable sensor worn by each of the multiple workers, and the data of each of the multiple workers includes at least one of pulse, blood pressure, or body temperature.
See claim 1 rejection for system and personal traits.
Amsallem teaches a wrist wearable device monitoring health information (heart rate, blood pressure) throughout the day without hampering daily life (e.g., working).
Wayne teaches methods for enabling workers to compete for currently upcoming shifts. Amsallem teaches monitoring physiological parameter for a user wearing the wrist-wearable device. It would have been obvious to combine before the effective filing date, linking specific employees or groups who would work together, as taught by Wayne, with using a machine learning model to match qualified candidates, comparing the values for the plurality of physiological parameters to baseline values for the physiological parameters, as taught by Amsallem, to easily and quickly understand to inform their day-to-day activity choices and goals., Amsallem [column 1 lines 38-40].
Conclusion
The prior art made of record and not relied upon is considered pertinent to Fera (2019, Towards Digital Twin Implementation for Assessing Production Line Performance and Balancing) teaches wearable devices offer the possibility to analyze data related both to real production phases and pre-production phases, as well as to the design phase, when the physical production line does not exist yet, providing in this way preventive information about the production line performance factors.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/THEA LABOGIN/Examiner, Art Unit 3624
/HAMZEH OBAID/Primary Examiner, Art Unit 3624