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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 5/15/2026 has been entered.
Response to Amendment
Claims 1, 6-7, 11-12, 15, and 17 are amended. Claims 1-20 are pending.
Response to Arguments
Applicant's arguments filed 4/16/2026 have been fully considered.
Regarding the objections to claims 1, 12, and 17, and as noted by Applicant on pages 12-13 of the response, the amendments to claims 1, 12, and 17 overcome the objections, which are withdrawn.
Regarding the rejections of claims 1-20 under 112(a), and as noted by Applicant on page 13 of the response, the amendments to claims 1, 12, and 17 overcomes the rejections, which are withdrawn.
Regarding the rejections of claims 1-20 under 101 as being directed to a judicial exception without significantly more, Examiner respectfully disagrees with Applicant’s arguments on pages 14-15 for the following reasons.
On page 14 of the response, Applicant contends that the claimed process integrates any exception into a practical application consistent with the USPTO’s August 4, 2025 memorandum, which cautions against oversimplifying or over-expanding the “mental process” grouping, and MPEP 2106. In support, Applicant notes that the claimed techniques can cause automated bots and machines controlled by the computer system to operate differently that by using conventional techniques, which can result in improved outcomes such as enabling the machines to perform activities without maintenance interruptions and preventing use of “unnecessary bandwidth for the automated agents (for example, automated robots/bots) performing maintenance on machines,” as described in the specification.
Regarding oversimplifying and/or over-expanding the mental processes exception, Examiner submits that the claim are evaluated as a whole, and in accordance with such evaluation, Examiner finds the application of the mental processes exception warranted because the individual steps and combinations thereof may be performed via mental processes.
Regarding additional elements, Examiner acknowledges that directing an automated bot to perform maintenance falls outside the abstract idea exception. However, as currently recited in the claims such direction and maintenance performance is recited at a high level of generality having no particularized functional relation to the step that fall within the mental processes exception, and therefore constitute insignificant extra solution activity (implementing maintenance via a known method) with respect to the thrust of the claimed invention which appears confined to the judicial exception. For example, the utility/improvement cited by Applicant (economy of information processing bandwidth) does not appear to be achieved in accordance with the particular configuration of an automated bot and would equivalently be derived for a system in which an automated bot is not used (human maintenance would similarly require less information for determining maintenance and/or finding a replacement machine to be used to avoid maintenance interruptions).
On page 14 of the response, Applicant further contends that the amended independent claims include steps providing improvements such as removing at least one non-essential functionality from the combinations of the functionalities to obtain set(s) of minimum functionalities required to perform an activity, identifying tasks scheduled to be performed by an identified machine requiring repair and a functionality corresponding to at least one of the scheduled tasks in the set of minimum functionalities; selecting a set of the machines that includes a second machine capable of performing the identified functionality and does not include the identified machine, scheduling a maintenance period during which the selected set of the machines performs the activity, and directing the automated bot to perform maintenance according to the maintenance plan.
Examiner submits that except for “directing the automated bot …”, all of these elements, individually and in any combination/subcombination may be performed via mental processes such that any alleged technical improvement is confined to the judicial exception with no combination/subcombination that may be considered in further combination with any additional element to result in the judicial exception being integrated into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception. As noted above, directing an automated bot to perform maintenance does not effectuate the claim as a whole amounting to significantly more because there is no combinatorial functional significance to using an automated bot to perform maintenance and the particular processing steps used to derive the maintenance schedule embodied by the steps falling within the judicial exception.
Regarding the rejections of independent claims 1, 12, and 17 under 103 as unpatenable over Shinge in view of Sobalvarro and in further view of Garrow, Examiner agrees with Applicant’s arguments on pages 15-16 that the amendments overcome the rejections, which are withdrawn. However, in view of further search and analysis new grounds for rejecting claims 1, 12, and 17 under 103 as unpatentable over Shinge in view of Sobalvarro and Garrow, and in further view of Reid (US 2022/0283578 A1) and Pal (US 2017/0011298 A1) are set forth below.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
In claim 1 line 28, “the scheduled tasks” renders claim 1 indefinite because “schedule tasks” lacks sufficiently clear antecedent basis. For the purpose of examination and based on apparently intended antecedent relation to “tasks that are scheduled to be performed by the identified machine” in lines 25-26, “the scheduled tasks” is interpreted as “the tasks that are scheduled to be performed by the identified machine.”
Independent claims 12 and 17 include substantially the same indefinite language and are likewise rejected for the same reasons.
Claims 2-11, 13-16, and 18-20 depend from claims 1, 12, and 17 respectively, and are likewise rejected for the same reasons.
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 because the claimed invention in each of these claims is directed to the abstract idea judicial exception without significantly more.
Claim 1, substantially representative also of independent claims 12 and 17, recites:
“[a] computer-implemented method for carrying out maintenance in an internet of things (IoT) environment using an automated bot, the method comprising:
receiving, by a computer system, sensor data from at least one IoT sensor device that is monitoring machines controlled by the computer system, wherein the machines comprise a first set of the machines performing an activity that includes a set of sequential tasks;
generating, by the computer system, a knowledge corpus for the machines, wherein the knowledge corpus comprises a mapping of the machines to respective functionalities of the machines;
determining, by the computer system, combinations of the functionalities that are capable of performing the activity;
removing, by the computer system, at least one non-essential functionality from the combinations of the functionalities to obtain one or more sets of minimum functionalities required to perform the activity;
determining, by the computer system, a minimal level of maintenance for the first set of the machines, wherein the determining the minimal level of maintenance comprises evaluating the sensor data;
generating, by the computer system, a maintenance plan for the automated bot to perform the minimal level of maintenance for the first set of the machines without interrupting the activity, wherein the generating the maintenance plan comprises:
identifying a machine from the first set of machines that is required to undergo maintenance;
identifying, in the set of sequential tasks, tasks that are scheduled to be performed by the identified machine;
identifying, in the set of minimum functionalities, a functionality corresponding to at least one of the scheduled tasks;
selecting a set of the machines that includes a second machine capable of performing the identified functionality and does not include the identified machine; and
scheduling a maintenance period during which the second set of the machines performs the activity; and
directing, by the computer system and according to the maintenance plan, the automated bot to perform the required maintenance on the identified machine during the maintenance period.”
The claim limitations considered to fall within in the abstract idea are highlighted in bold font above and the remaining features are “additional elements.”
Step 1 of the subject matter eligibility analysis entails determining whether the claimed subject matter falls within one of the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. Claim 1 recites a method and claim 12 recites a system (machine), and each therefore falls within a statutory category.
Step 2A, Prong One of the analysis entails determining whether the claim recites a judicial exception such as an abstract idea. Under a broadest reasonable interpretation, the highlighted portions of claim 1 fall within the abstract idea judicial exception. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, the highlighted subject matter falls within the mental processes category (including an observation, evaluation, judgment, opinion). MPEP § 2106.04(a)(2).
The recited functions:
“generating” “a knowledge corpus for the machines, wherein the knowledge corpus comprises a mapping of the machines to respective functionalities of the machines;
determining” “combinations of the functionalities that are capable of performing the activity;
removing” “at least one non-essential functionality from the combinations of the functionalities to obtain one or more sets of minimum functionalities required to perform the activity;
determining” “a minimal level of maintenance for the first set of the machines, wherein the determining the minimal level of maintenance comprises evaluating the sensor data;
generating” “a maintenance plan for the automated bot to perform the minimal level of maintenance for the first set of the machines without interrupting the activity, wherein the generating the maintenance plan comprises:
identifying a machine from the first set of machines that is required to undergo maintenance;
identifying, in the set of sequential tasks, tasks that are scheduled to be performed by the identified machine;
identifying, in the set of minimum functionalities, a functionality corresponding to at least one of the scheduled tasks;
selecting a set of the machines that includes a second machine capable of performing the identified functionality and does not include the identified machine; and
scheduling a maintenance period during which the second set of the machines performs the activity”
may be performed as mental processes.
Generating a knowledge corpus that maps machines to respective functionalities of the machines may be performed via mental processes (e.g., observing and accumulating/learning the functions of machines). Determining combinations of the functionalities that are capable of performing the activity, removing at least one non-essential functionality from the combinations of the functionalities to obtain one or more sets of minimum functionalities required to perform the activity, and determining a minimal level of maintenance for the first set of the machines, wherein the determining the minimal level of maintenance comprises evaluating the sensor data may be performed via mental processes (evaluation and judgment). Generating a maintenance plan for the automated bot to perform the minimal level of maintenance for the first set of the machines without interrupting the activity, may also be performed via mental processes (e.g., conceiving of maintenance plan for an automated bot in accordance with evaluation of the determined minimal level of maintenance), including generating the maintenance plan by identifying a machine from the first set of machines that is required to undergo maintenance (e.g., evaluation and judgement), identifying, in the set of sequential tasks, tasks that are scheduled to be performed by the identified machine (evaluation and judgment), identifying, in the set of minimum functionalities, a functionality corresponding to at least one of the scheduled tasks (evaluation and judgment), and selecting a set of the machines that includes a second machine capable of performing the identified functionality and does not include the identified machine (e.g., evaluation of the set of machines and judgement in selecting a set that excludes the identified machine), and scheduling a maintenance period during which the second set of the machines performs the activity (ascertaining scheduling period based on evaluation and judgment).
Step 2A, Prong Two of the analysis entails determining whether the claim includes additional elements that integrate the recited judicial exception into a practical application. “A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception” (MPEP § 2106.04(d)).
MPEP § 2106.04(d) sets forth considerations to be applied in Step 2A, Prong Two for determining whether or not a claim integrates a judicial exception into a practical application. Based on the individual and collective limitations of claim 1 and applying a broadest reasonable interpretation, the most applicable of such considerations appear to include: improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)); applying the judicial exception with, or by use of, a particular machine (MPEP 2106.05(b)); and effecting a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)).
Regarding improvements to the functioning of a computer or other technology, none of the “additional elements” including that the method is “computer-implemented,” “receiving, by a computer system, sensor data from at least one IoT sensor device that is monitoring machines controlled by the computer system, wherein the machines comprise a first set of the machines performing an activity that includes a set of sequential tasks,” “directing, by the computer system and according to the maintenance plan, the automated bot to perform the required maintenance on the identified machine during the maintenance period,” and that the processing steps are performed by a “computer system,” appear to integrate the abstract idea in a manner that technologically improves any aspect of a device or system that may be used to implement the highlighted step or a device for implementing the highlighted step such as a signal processing device or a generic computer. Receiving, by a computer system, sensor data from at least one IoT sensor device that is monitoring machines controlled by the computer system, wherein the machines comprise a first set of the machines performing an activity that includes a set of sequential tasks represents high-level data collection having no particularized relation to the functions falling within the judicial exception and therefore constitutes insignificant extra solution activity that fails to integrate the judicial exception into a practical application. Directing, by the computer system and according to the maintenance plan, the automated bot to perform the required maintenance on the identified machine during the maintenance period does not embody an improvement in the functioning of a computer or other technical field improvement because it merely conveys computer-based (instruction based) high-level control of application functions (bot) that does not appear to entail any such improvement and therefore also constitutes insignificant extra solution activity that fails to integrate the judicial exception into a practical application.
Regarding application of the judicial exception with, or by use of, a particular machine, the additional elements are configured and implemented in a conventional (generalized computer implementation) rather than a particularized manner of determining production and maintenance requirements for machines.
Regarding a transformation or reduction of a particular article to a different state or thing, claim 1 does not include any such transformation or reduction. Instead, claim 1 as a whole entails a series of functions that may be performed individually and/or in combination by mental processes with “computer-implemented” representing conventional, routine data processing activity for implementing the judicial exception, such that the additional elements fail to provide a meaningful integration of the judicial exception (functions for determining information relevant to production and related maintenance) in an application that transforms an article to a different state. Instead, the additional element represents extra-solution activity that does not integrate the judicial exception into a practical application. In view of the various considerations encompassed by the Step 2A, Prong Two analysis, claim 1 does not include additional elements that integrate the recited abstract idea into a practical application.
Therefore, claim 1 is directed to a judicial exception and requires further analysis under Step 2B.
Regarding Step 2B, and as explained in the Step 2A Prong Two analysis, the additional elements in claim 1 constitute insignificant extra solution activity and therefore do not result in the claim as a whole amounting to significantly more than the judicial exception under Step 2B. Furthermore, the most of the additional elements appear to be generic and well understood as evidenced by the disclosures of Shinge (US 2022/0405717 A1), Sobalvarro (US 2022/0121181 A1) and Ueki (US 2021/0089928 A1), each of which teach a substantially similar data processing (computer-implemented) platform for processing information relating to machine activity configurations, operations, and maintenance and in which Sobalvarro and Ueki teach using sensors for monitoring machines.
As explained in the grounds for rejecting claim 1 under 103, Shinge teaches “a computer-implemented method,” as does Sobalvarro ([0039]-[0040]). Shinge and Sobalvarro further teach use of equipment monitoring information for equipment that may be collected via operation condition inputs (sensors) (Shinge: [0042], [0080]-[0081] use of “operation history” for condition based maintenance (as distinct from time based maintenance) [0045] describing dynamic operation information that may be used; Sobalvarro: Table I listing speeds and payloads as “Attributes”) as does Ueki ([0008] known in the prior art to use sensors for monitoring failures and remaining life). Planning and performing maintenance in an IoT environment such that the sensors constitute IoT sensors was also well-known as disclosed by Pal (US 2017/0011298 A1) as set forth in the grounds for rejecting claim 1 under 103 and Murali (US 2019/0220828 A1) ([0001]). Furthermore, using automated bots for performing maintenance was also well-known as disclosed by Reid (US 2022/0283578 A1) as set forth in the grounds for rejecting claim 1 under 103 and further disclosed by Joblin (US 2020/0167736 A1) ([0033]).
Therefore, the additional elements are insufficient to amount to significantly more than the judicial exception.
Claim 1 is therefore not patent eligible.
Independent claims 12 and 17 recite substantially the same elements falling within the judicial exception as claim 1 and include no additional elements that either integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception. For example, claim 12 further recites the additional element that the system includes “one or more computer processors,” which entails conventional, routine functionality of a generic computer system and therefore constitutes insignificant extra solution activity. Similarly, claim 17 further recites that the apparatus comprises “a compute readable storage medium having program instructions embodied thereon” to be “executable by a server,” which also entails convention, routine functionality of a generic computer system implemented as a server and therefore constitutes insignificant extra solution activity (there is no particularized significance to the server configuration relating to the elements constituting the judicial exception and instead a server configured as a processing node in the system was well-known in the art as disclosed by Shinge ([0037]) and Wallace (EP 4053656A2) (FIG. 1 server 18; [0040], [0042], [0044]).
Therefore, independent claims 12 and 17 are also not patent eligible under 101.
Claims 2-11 depending from claim 1, claims 13-16 depending from claim 12, and claims 18-20 depending from claim 17 provide additional features/steps which are part of an expanded algorithm that includes the abstract idea of the respective independent claim (Step 2A, Prong One). None of dependent claims 2-11, 13-16, and 18-20 recite additional elements that integrate the abstract idea into practical application (Step 2A, Prong Two), and all fail the “significantly more” test under the step 2B for substantially similar reasons as discussed with regards to the independent claims.
For example, claims 2-6, 9-10, 13-15, 18-19 further recite functions that clearly may be performed via mental processes (e.g., evaluation and judgment) and include no further additional elements that computer-implementation in claim 10.
Claims 7 and 11 further characterizes the content of the maintenance plan (characterizes the data generated via the judicial exception) and therefore also falls within the judicial exception within no additional elements that either integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception.
Claim 8, representative also of claims 16 and 20, recites three functions (analyzing, identifying, and generating) that may be performed via mental processes and further recites “incorporating the adjustments into the maintenance plan,” which the Examiner finds to fall within the mental processes exception because it can be performed via mental processes (e.g., determining a different maintenance plan using judgement). Even if this element was found to fall outside the mental processes exception (e.g., considered to entail a tangible adjustment of maintenance data), it entails routine, conventional data processing activity (data outputs replacing other/previous outputs) that constitutes insignificant extra solution activity.
Dependent claims 2-11, 13-16, and 18-20 therefore also constitute ineligible subject matter under 101.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Shinge (US 2022/0405717 A1) in view of Sobalvarro (US 2022/0121181 A1) and in further view of Garrow (US 7,457,763 B1), Reid (US 2022/0283578 A1), and Pal (US 2017/0011298 A1).
As to independent claims 1, 12, and 17, as best understood in view of the grounds for rejecting claims 1, 12, and 17 under 112(b), Shinge teaches “a computer-implemented method for carrying out maintenance (method by computer implemented system for implementing maintenance plan depicted in FIG. 1; [0035])” “a system for carrying out maintenance (computer implemented system for implementing maintenance plan depicted in FIG. 1; [0035])” “wherein the system comprises one or more computer processors (FIG. 1 computer implemented system; FIG. 2 computation device 104; FIG. 4 computation device 304),” and “a computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions (FIG. 1 computer implemented system (inherently entails computer-readable storage medium such as memory required for processing); FIG. 2 computation device 104 connected to memory 103; FIG. 4 computation device 304 connected to memory 303) executable by a server to cause the server to perform a method for carrying out maintenance (FIG. 1 depicting networked system for implementing maintenance plan; [0037] system may be implemented in a networked configuration in which a server device receives and processes data from user)”, each configured to implement a method comprising:
“receiving, by a computer system,” “data from at least one” “device that is monitoring machines (FIGS. 4 and 9 and [0082] analysis system 300 contains/stores operation history data 325 (the operation data has been received (e.g., from user terminals 200 (performing monitoring function) per [0082]); [0042] analysis system 300 uses past operation history (must be received) to determine temporal changes in cumulative damage and failure probability)” “wherein the machines comprise a first set of machines performing an activity that includes a set of sequential tasks ([0038]-[0040] devices for which data is collected for maintenance may be manufacturing operation devices; [0068] and [0072]-[0073] devices may be part of a production line (sequential tasks for production activities); FIG. 6 depicting various production processes by machines/functionalities);”
“determining, by the computer system, combinations of the functionalities that are capable of performing the activity ([0077] describing indication of damage accumulation for a device of the target production process (indicates that known/determined devices (machines functions) are used to implement the production process). Examiner notes that an initial determination of the combined devices/machine functions (e.g., cutting/pressing, assembling depicted in FIG. 8) for implementing the activity functions (production processing) is inherently entailed in the described implementation of and damage accumulation monitoring for the devices/machines);
“obtain one or more sets of” “functionalities required to perform the activity ([0039] user terminal distribute production plan; FIG. 7 depicting production plan database 127 and FIG. 8 depicting remaining life records including records indicating processes (functionalities) required for respective production items that each contribute to the overall production process/activity; [0073]-[0074]);
determining, by the computer system, a minimal level of maintenance for” “the machines ([0008] condition-based modeling for determining maintenance requirements (e.g., timing) including determining over time (variable range) whether remaining life/failure probability requires a change in maintenance timing (i.e., may need to be performed earlier or may be postponed (minimized in a time interval) based on conditions that indicate failure probability/remaining life (indicative of maintenance at least minimally required for continued functioning); FIG. 12 blocks s2 and s3 depicting determination of remaining life information for devices and FIG. 13 blocks s12, s13 and s14 depicting determination of condition-based maintenance; [0102]), wherein the determining the minimal level of maintenance comprises evaluating the” “data ([0008] and [0042] failure probability used to determine condition-based (minimum level) maintenance);
generating, by the computer system, a maintenance plan” “to perform the minimal level of maintenance for” “the machines (FIG. 13 blocks s14 and s15; [0108]-[0110] condition-based maintenance timing adopted and implemented as recommendation)” “wherein the generating the maintenance plan comprises:
identifying a machine from the” “machines that is required to undergo maintenance ([0037], [0040], [0069], [0125], [0131] maintenance plan determined for target devices).”
Shinge does not expressly teach “generating, by the computer system, a knowledge corpus for the machines, wherein the knowledge corpus comprises a mapping of the machines to respective functionalities of the machines,” and further does not expressly teach that the steps of “determining … a minimal level of maintenance,” “generating … a maintenance plan … to perform the minimal level of maintenance,” and “identifying a machine … that is required to undergo maintenance” are performed with respect to “the first set of machines.”
Sobalvarro discloses a method for optimizing a factory schedule and factory layout (Abstract) that includes a computer system controlling/directing a first set of machines to perform activities (FIG. 1 depicting a computer system comprising processor 110 and memory 115 configured to control physical factor 160, which per [0043] and Table 1 includes multiple machines, via optimized layouts 125 and schedules 130; [0040]-[0041]) generating a knowledge corpus for the machines, wherein the knowledge corpus comprises a mapping of the machines to respective functionalities of the machines (Table 1 associating objects (machines) with respective functions; [0040] describing processing of the objects in Table 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Sobalvarro’s teaching of directing activity for a set of machines (e.g., production/manufacturing) via computer control (automated) to the method taught by Shinge such that the machines are automated in some manner to implement activities and that consequently, the steps of “determining … a minimal level of maintenance,” “generating … a maintenance plan … to perform the minimal level of maintenance,” and “identifying a machine … that is required to undergo maintenance” are performed with respect to “the first set of machines.”
The motivation would have been to enhance efficiency of the system (e.g., production/manufacturing) via automation as suggested by Sobalvarro.
It would further have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Sobalvarro’s teaching of generating a knowledge corpus that maps the machines to respective functionalities to the method taught by Shinge as modified by Sobalvarro such that in combination the method includes generating such mapping.
The motivation would have been to enable implementation of automated (controlled by the information) machine operations and adjustments to such operations in a manner that effectuates the functions required for operation as suggested by Sobalvarro.
Shinge appears to further at least suggest “removing” “at least one non-essential functionality from the combinations of the functionalities to obtain one or more sets of minimum functionalities required to perform the activity,” because as explained above Shinge teaches a set of processes required for performing an activity, which inherently includes excluding functionalities not required to obtain a minimum set of such functionalities required to perform the activity.
Furthermore, Sobalvarro discloses a method for optimizing a factory schedule and factory layout (Abstract) that includes determining a set of minimum functionalities entailing effective exclusion of unnecessary functions required to perform an activity (FIG. 1 constraints and requirements (for factory production) 140; [0046] layout optimization includes receiving a work order that specifies operations to be performed (functionalities) and the objective function to be maximized in accordance with the work order (activity). The selective determination of particular operations among all available for implementing the work order activities constitutes excluding unnecessary functions as part of determining a set of minimum functionalities).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Sobalvarro’s teaching of determining a set of minimum functionalities required to perform an activity such as by selectively determining which operations to implement to the exclusion of others for layout corresponding to a particular work order to the method taught by Shinge such that the combined method includes determining one or more sets of minimum functionalities required to perform an activity.
The motivation would have been to optimize efficient allocation of system resources for implementing specific activities such as may be specified in work orders as suggested by Sobalvarro.
Regarding the generating of the maintenance plan to perform the maintenance “without interrupting the activity” and including “identifying, in the set of sequential tasks, tasks that are scheduled to be performed by the identified machine; identifying, in the set of minimum functionalities, a functionality corresponding to at least one of the scheduled tasks; and selecting, a set of the machines that includes a second machine capable of performing the identified functionality and does not include the identified machine; and scheduling a maintenance period during which the second set of the machines performs the activity,” Sobalvarro discloses that maintenance scheduling may be accounted for in determining optimized production scheduling ([0044] and Table 1 objects corresponding to machines (and per [0017] and [0046] used for layout and production scheduling) includes maintenance schedule data), and further discloses in the same object-based association, the potential need for machine replacement by an equivalent machine to be accounted for in the machine objects used for determining optimized layouts/scheduling ([0044] and Table 1 indicating “equivalent objects for replacement” as an object attribute).
Furthermore, Garrow discloses a predictive maintenance method for eliminating or reducing equipment downtime (Abstract) and that includes a scheduler that may determine to preserve a maintenance schedule by using an alternate component to be used as a substitute for/during maintenance (col. 5 lines 12-24 and col. 12 lines 14-22 describing use/revision of a maintenance schedule in which an alternate component is used as a substitute for a component under maintenance which would result in uninterrupted production).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Garrow’s teaching of using substitute components during maintenance to the method taught by Shinge as modified by Sobalvarro and including Sobalvarro’s teaching of computer-controlled machine activity based on a maintenance schedule and that maintenance scheduling is accounted for in production scheduling including potential machine replacement during maintenance, such that in combination the maintenance scheduling includes generating a maintenance plan to perform maintenance without interrupting activity including selecting, a set of the machines that includes a second machine capable of performing the identified functionality and does not include the identified machine, and the method further includes directing, by the computer system and according to the maintenance plan, the system to perform the required maintenance on the identified machine during the maintenance period. Examiner notes that replacing a machine with a substitute machine necessarily entails identifying tasks that are scheduled to be performed by the identified machine (substitution requires matching tasks) and identifying a functionality corresponding to at least one of the scheduled tasks (substitution entails substituting and therefore identifying respective functionalities), such that in the combination in which the set of minimum functionalities are set as set forth above, the method would include identifying, in the set of sequential tasks, tasks that are scheduled to be performed by the identified machine and identifying, in the set of minimum functionalities, a functionality corresponding to at least one of the scheduled tasks as part of the “selecting” step. Examiner further notes that such combination would consequently entail an effective scheduling (e.g., via Garrow scheduler 124) of a maintenance period during which the replacement/substitute component is used such that the method would also include scheduling a maintenance period during which the second set of the machines performs the activity.
The motivation for such combination would have been to eliminate or reduce downtime of the machine-implemented system as disclosed by Garrow.
Regarding the method further including “using an automated bot” to perform maintenance and “directing, by the computer system and according to the maintenance plan, the automated bot to perform the required maintenance on the identified machine during the maintenance period,” Shinge teaches that maintenance is implemented on the identified machine during the maintenance period according the to the maintenance plan (FIG. 13, [0106] maintenance implementation according to a determine implementation timing) but does not teach the specifics of performing maintenance and therefore does not teach the system using an “automated bot” to perform the maintenance.
Reid discloses a method/system for maintenance resource allocation (Abstract) in which a robot (automated bot) may be directed by the system for performing maintenance ([0017], [0032], and [0057] service robot may be utilized interchangeably with service technician as a service (maintenance) resource; [0044] and [0046] service resource directed by system).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Reid’s teaching of the availability of automated bots for performing maintenance to the method/system taught by Shinge as modified by Sobalvarro and Garrow, such that in combination the method includes using an automated bot to perform maintenance including steps of generating a maintenance plan for the automated bot and directing, by the computer system and according to the maintenance plan, the automated bot to perform the required maintenance on the identified machine during the maintenance period.
Such a combination would amount to selecting a known system-controllable option for performing maintenance to achieve predictable results.
Regarding receiving, by a computer system, “sensor” data from at least one device that is monitoring machines “controlled by the computer system” and wherein the determining the minimum level of maintenance comprises evaluating the “sensor” data, Garrow further teaches receiving sensor data from a monitoring machine (col. 7 lines 26-36 data processing system 100 collects (receives) performance data from an operational data source 14 that may be a sensor associated with the equipment; col. 2 lines 58-66 sensor is incorporated into/with the equipment (equivalent of computer-controlled “device monitoring machine” depicted in Applicant’s FIG. 5)) in which the sensor data is used for determining required maintenance (col. 2 lines 58-66 sensor data and col. 7 lines 26-36 performance data analyzer may receive sensor data indicating performance condition; FIG. 4 performance data used for predicting required maintenance activity). Regarding the device monitoring machines being “controlled by the computer system,” as noted above Sobalvarro discloses the monitored equipment being controlled by a computer system (FIG. 1 depicting a computer system comprising processor 110 and memory 115 configured control physical factory 160, which per [0043] and Table 1 includes multiple machines, via optimized layouts 125 and schedules 130; [0040]-[0041]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Garrow’s teaching of receiving sensor data from a monitoring machine for determining required (minimum needed) maintenance to the method taught by Shinge, as modified by Sobalvarro to include target equipment that is computer-controlled such that in combination the method includes “receiving, by a computer system, sensor data from at least one” “sensor device monitoring machines controlled by the computer system” and “wherein the determining the minimal level of maintenance comprises evaluating the sensor data.”
Such a combination would amount to selecting a known design option for collecting and applying information that relates to equipment condition and is therefore useful for making maintenance decisions to achieve predictable results. Furthermore, a particular motivation would have been to collect and apply information that is particularly relevant to dynamic equipment operating condition to optimize maintenance decision-making as suggested by Garrow.
None of Shinge, Sobalvarro, Garrow, and Reid expressly teach the system/method being implemented in an internet of things (IoT) and using IoT sensors for monitoring machines.
Pal discloses a method/system for monitoring and determining maintenance for machines in an internet of things (IoT) environment (Abstract machine data collected and processor for machines located in IoT; [0011] in which the sensors are correspondingly IoT sensors (IoT environment entails a machine wearable sensor network; [0013]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Pal’s teaching of implementing sensor-based machine monitoring related to maintenance in an IoT environment to the method/system taught by Shinge as modified by Sobalvarro, Garrow, and Reid, which teaches sensor based collection of data from machines, such that in the combination the method/system is implemented in an internet of things (IoT) and using IoT sensors for monitoring machines.
The motivation would have been to leverage the interconnected sensor configuration of an IoT environment to be leveraged for obtain machine related information useful for determining maintenance related information.
As to claims 2, 13, and 18, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches the method of claim 1, system of claim 12, and program product of claim 17, and further teaches “wherein generating the maintenance plan comprises:
analyzing execution plans for the sets of the machines capable of supporting the one or more sets of minimum functionalities (Shinge: FIG. 7 production plan database 127 including records showing scheduled production amounts for respective processes (functionalities), that per [0077] are associated with respective devices/machines); [0059] production plan applied for implementing functions (i.e., is analyzed)); and
determining, from the analyzing, a downtime of at least one of the machines (Shinge: FIG. 7 production plan database 127 including records corresponding to processes (functionalities), that per the grounds for rejecting claim 1 are associated with respective devices/machines, in which the records (e.g., for Quenching K) includes indicated no production (no activity) dates).”
As to claim 3, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches “[t]he method of claim 1, wherein selecting the set of machines comprises:
determining whether there are any sets from the one or more sets of minimum functionalities that involve only machines that do not need to undergo maintenance (Shinge: [0008]-[0009] remaining life information for particular devices used in determining maintenance timing adjustments within a variable range; FIG. 13 block s14. Examiner notes that the individualized determinations of when (sooner or later) to perform maintenance for particular devices that implement the processing functions inherently entails a determination that a given device for a corresponding production process does not need to undergo maintenance for at least some period of time).”
As to claims 4, 14, and 19 the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches the method of claim 1, the system of claim 12, and the program product of claim 17, and Shinge further teaches, pursuant to determining functionalities for performing the activity,
“determining current functionalities of the first set of the machines performing the activity (Shinge: FIG. 8 depicting Remaining Life Information records for particular processes (functionalities) that indicate operational data including cumulative damage (monitoring operational data for a particular process inherently entails a determination that the process is operating/performing activity; FIG. 9 Operation History including records indicating particular product processes (functionalities e.g., Cutting X) for which production operation was recorded (i.e., the functionality that performed the activities were determined)); and
determining one or more combinations of functionalities from the current functionalities and the mapped functionalities in the knowledge corpus that are capable of performing the activity (Shinge: FIG. 7 Production Plan including records identifying production processes (functionalities) that per [0077] are associated with respective machines. Examiner notes that the “one or more combinations of functionalities from the current functionalities and the mapped functionalities” may comprise one or more functionalities from the “mapped functionalities” and any number including none of the functionalities from the “current functionalities”).”
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Shinge’s teaching of determining current functionalities performing an activity, determining capable functionalities of one or more machines, and determining one or more combinations of functionalities from the current functionalities and the mapped functionalities for performing the activity pursuant to determining functionalities for performing the activity to the method taught by Shinge as modified by Sobalvarro in which such determinations regarding machine operation and capabilities are made to determine one or more sets of minimum functionalities for performing an activity, such that in combination these steps are performed for determining one or more sets of minimum functionalities for performing an activity.
The motivation would have been to utilize available activity performance data and machine capability data for optimizing efficient allocation of system resources for implementing specific activities.
As to claim 5, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches “[t]he method of claim 4, wherein determining the current functionalities comprises:
identifying which functionalities are programmed to perform the activity (Shinge: FIG. 3 depicting user terminal 200 in which production plan 225 (functionalities for performing production activities) is stored in memory for processing by computation device 204; [0059]).”
As to claims 6 and 15, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches the method of claim 4 and the system of claim 14, and further teaches “wherein determining one or more combinations of functionalities that are capable of performing the activity comprises:
identifying a set of different functionalities from the current functionalities” “that are capable of performing a same task from the set of sequential tasks (as set forth in the grounds for rejecting claim 1, Garrow combined with Shinge and Sobalvarro teaches selecting a substitute machine for replacing a machine during maintenance, which inherently entails identifying different functionalities (functionality of the substitute) capable of performing a same task); and
selecting a functionality from the set of different functionalities for each of the combinations of functionalities (the selection of the substitute machine constitutes an effective selection of a functionality from the different functionality).”
It would further have been obvious to one of ordinary skill in the art before the effective filing date, to have applied the foregoing combined teachings with the mapped functionalities taught by Sobalvarro as set forth in the grounds for rejecting claim 1, such that in combination the method includes identifying a set of different functionalities from the mapped as well as current functionalities.
The motivation would have been to leverage the automated/stored functionality data to optimize efficiency of selecting a replacement machine.
As to claim 7, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches “[t]he method of claim 1, wherein the generating the maintenance plan further comprises selecting, based on the knowledge corpus, a time to perform maintenance on the one or more of the machines (Shinge: FIG. 6 maintenance plan DB including records indicating starting dates and completion dates for implementing corresponding maintenance events; Abstract disclosing condition-based maintenance implementation timing (i.e., maintenance timing is adjusted based on the condition-based maintenance determinations); FIG. 13 blocks s11 and s12 adjusting maintenance timing in accordance with remaining life and maintenance list; [0101]-[0102]. Regarding the selection of a time to perform the maintenance “based on the knowledge corpus,” (i.e., a knowledge corpus that includes a mapping of machines to respective machine functionalities), the Examiner notes the overall method implemented by the teachings of Shinge, Sobalvarro, and Garrow as combined for claim 1 includes an expanded knowledge corpus that includes the portion of the knowledge corpus contributed by Sobalvarro (maps machines to respective functions) and other knowledge such as Shinge’s tracking of remaining life and maintenance list such that the timing is implemented by this overall knowledge corpus maintained and used in the overall method.).
As to claims 8, 16, and 20 the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches the method of claim 1, the system of claim 12, and the program product of claim 17, and further teaches “the generating the maintenance plan further comprising:
analyzing an existing maintenance plan (Shinge: Abstract and [0008] method implements adjustments in variable range for pre-determined maintenance timing; [0005] time-based maintenance (TBM) as basis; [0039] obtain basis maintenance plan; [0040] analysis system generates information on temporal changes in failure probabilities of devices subject to basis maintenance plan; FIG. 6 depicting “regular” maintenance plan);
identifying a problem likely to be caused by the existing maintenance plan (Shinge: [0040] and [0042] analysis system determines temporal changes in failure probability of devices subject to the (basis) maintenance plan; [0078]-[0079] analysis for determining failure probabilities; FIG. 13 block s11);
generating an adjustment to the existing maintenance plan that addresses the problem (Shinge: Abstract the timings in existing maintenance plan are modified in a variable range based on condition-based maintenance processing (i.e., maintenance timings are determined/adjusted) to address condition issues that per [0040], [0042], and [0078]-[0079] may be remaining life corresponding to failure probabilities; FIG. 13 blocks s12, s13, and s14, [0102], [0108]); and
incorporating the adjustment into the maintenance plan (Shinge: FIG. 13 blocks s14 and s15, [0108] and [0110]).”
As to claim 9, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches “[t]he method of claim 1, wherein determining the minimal level of maintenance comprises:
analyzing interdependencies between activities and the machines (Shinge: FIG. 7 production plan records associate overall production activity with specific production processes (cleaning, quenching, etc.) such that the generation of the records constitutes an analysis of the interdependencies between overall production activity and the specific production processes. Examiner notes that the systemic awareness (per [0077]) of devices that performs the specific production processes results in the analyzed interdependencies between the activities and the specific production processes being functionally equivalent to analyzed interdependencies between the activities and the machines; [0039] and [0059] production plan provided to maintenance plan assistant device (production plan processed for determining maintenance of equipment performing the production processes including in the production plan); [0074] production plan applicable to “target” period that per [0101] is period in which maintenance plan assistance device 100 is determining factors (e.g., damage suppression) for determining the conditional maintenance; FIG. 13 block s10 production process used as input for determining adjustments to maintenance timing); and
determining whether one or more of the machines are used to accomplish multiple activities (Shinge: FIG. 7 production plan, that as indicated above is used for determining the minimum level of maintenance, records indicate production processes, which per [0077] are known by the system as being implemented by respective devices/machines, and are for accomplishing multiple activities).
As to claim 10, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches “[t]he method of claim 1,” and Shinge teaches “determining, by the computer system and based on new” “data from monitoring the selected set of machines while performing the activity, that one or more machines of the selected set of machines need maintenance ([0008] and [0042] device condition relevant to maintenance (e.g., remaining life) reflect temporal changes in failure probabilities used for condition-based maintenance planning (i.e., temporally evolving (new) RUL data used to monitor and determine maintenance requirements).”
Garrow further teaches that sensor data may be used for monitoring equipment condition and used for determining required maintenance (i.e., maintenance determined on an as-needed basis) (col. 2 lines 58-66 and col. 7 lines 26-36 performance data analyzer may receive sensor data indicating performance condition; FIG. 4 performance data used for predicting required maintenance activity).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Garrow’s use of sensor data as the source for monitoring equipment condition to the method taught by Shinge, which teaches using “new” (temporally evolving) data for monitoring equipment condition, as modified by Sobalvarro and Garrow (to include sensor data input for claim 1), such that in combination the method includes using new/evolving sensor data for monitoring the selected set of machines and determining need for maintenance for one or more of the machines based thereon.
Such a combination would amount to selecting a known design option for collecting and applying information that relates to equipment condition and is therefore useful for making maintenance decisions to achieve predictable results. Furthermore, a particular motivation would have been to collect and apply information that is particularly relevant to dynamic equipment operating condition to optimize maintenance decision-making as suggested by Garrow.
As to claim 11, the combination of Shinge, Sobalvarro, Garrow, Reid, and Pal teaches “[t]he method of claim 1, wherein generating the maintenance plan further comprises generating an activity execution plan for the selected set of machines while the identified machine undergoes maintenance (as combined for claim 1, the combination of Shinge, Sobalvarro, and Garrow teaching using a substitute machine to replace a machine undergoing maintenance, which inherently entails an activity plan (execution of the process) for the selected set (including substitute machine) while the machine undergoes maintenance).”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW W BACA whose telephone number is (571)272-2507. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
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/MATTHEW W. BACA/Examiner, Art Unit 2857
/LINA CORDERO/Primary Examiner, Art Unit 2857
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