DETAILED ACTION
Claims 1-11 are presented for examination.
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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“first optimization module to determine…” in claim 1
“second optimization module to determine…” in claim 1
“an output module to distribute…” in claim 1
“first optimization module determines…” in claim 2
“first optimization module takes into account…” in claim 3
“second optimization module takes into account…” in claim 4
“second optimization module determines…” in claim 5
“at least one of the first optimization module and the second optimization module is configured to re-execute…” in claim 6
“simulation module to perform a computer-aided material-flow simulation…” in claim 7
“simulation module accounts for…” in claim 8
“validation module to validate…” in claim 9
“prediction module to predict…” in claim 10
NOTE: Applicant’s Specification states, “The apparatus 100 comprises an interface 101, a first optimization module 102, a second optimization module 103 and an output module 104. The apparatus 100 can optionally comprise also a simulation module 105, a validation module 106 and/or a prediction module 107. In addition, the apparatus 100 can comprise at least one processor. The apparatus 100 can comprise in particular software components and hardware components; for example, modules of the apparatus can be embodied as software components. It may be an assistance system, for example.” (Spec: p. 9, emphasis added) “Can comprise” is not a special definition. While modules “can be embodied as software components,” the modules may be interpreted as the hardware comprising the software components. The reference to “at least one processor” (Spec: p. 9) is one example of a hardware component. The computer program product described on page 7 of Applicant’s Specification is another example.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claimed invention is directed to the “optimization of production planning” (Spec: p. 1) without significantly more.
Step
Analysis
1: Statutory Category?
Yes – The claims fall within at least one of the four categories of patent eligible subject matter. Process (claim 11), Apparatus (claims 1-10)
Independent claims:
Step
Analysis
2A – Prong 1: Judicial Exception Recited?
Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite:
[Claims 1, 11] optimizing production planning for production of a product, wherein workers are assigned to operate machines for producing the product, comprising:
import planning data for the production and competency information regarding machine operation and availability information of the workers;
determine an optimized percentage assignment of the workers to the respective machines for a defined time period based on the planning data, the competency information, and the availability information;
determine optimized production planning data, wherein an optimized time sequence of respective production steps is determined based on the planning data with respect to the workers and machines according to the percentage assignment the number of workers needed for a production step; and
distribute the optimized production planning data [for producing the product in accordance with the optimized production planning data (claim 11)].
Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106(a)(2)(C)(III), “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, ‘methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’’ 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. Aside from the general recitation of an interface and various modules (in claim 1), a human user could perform the recited operations (in claims 1 and 11). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to the “optimization of production planning” (Spec: p. 1), including the allocation of assignments and instructions to human workers, which (under its broadest reasonable interpretation) is an example of managing personal behavior and interactions between people as well as following instructions (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity.
2A – Prong 2: Integrated into a Practical Application?
No – The judicial exception(s) is/are not integrated into a practical application.
Claim 1 presents an apparatus comprising an interface to import data and various modules to perform the various claim operations.
Claim 11 does not present any additional elements and is, thus, directed to the abstract ideas per se.
The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: pp. 7, 9).
The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations.
The additional elements are recited at a high-level of generality (i.e., as generic processing elements performing generic computer functions) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception(s) using generic computer components. There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). Accordingly, the additional elements do not integrate the abstract ideas into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea(s).
The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process (see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)).
There is no transformation or reduction of a particular article to a different state or thing recited in the claims.
Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately.
2B: Claim(s) Provide(s) an Inventive Concept?
No – The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception(s). As discussed above with respect to integration of the abstract idea(s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exceptions using a generic computer component(s). Mere instructions to apply an exception using a generic computer component(s) cannot provide an inventive concept. The claims are not patent eligible.
Dependent claims:
Step
Analysis
2A – Prong 1: Judicial Exception Recited?
Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite:
[Claim 2] determines the optimized assignment of the workers to the respective machines using a mixed integer optimization problem.
[Claim 3] takes into account at least one of the following boundary conditions in determining the optimized assignment of the workers to the respective machines:
minimizing a change in workstation by a worker;
even utilization of a worker; and/or
compliance with machine-specific criteria.
[Claim 4] takes into account at least one of the following boundary conditions in determining the optimized production planning data:
compliance with a defined sequence of the production steps;
taking into account the bill of materials and/or bill of process;
compliance with a completion date;
a defined capacity of a machine; and/or
minimizing retooling times.
[Claim 5] determines, in the event that the production deviates in time from the optimized production planning data, re-optimized production planning data according to the optimized percentage assignment.
[Claim 6] re-execute the associated optimization on the basis of a current production status.
[Claim 7] perform a material-flow simulation of the production according to the optimized production planning data, and generate simulation data.
[Claim 8] wherein the simulation accounts for transport times between machines.
[Claim 9] validate the optimized production planning data on the basis of the simulation data.
[Claim 10] predict production-relevant data on the basis of the simulation data.
The dependent claims further present details of the abstract ideas identified in regard to the independent claims.
Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106(a)(2)(C)(III), “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, ‘methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’’ 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. Aside from the general recitation of an interface (claim 1) and various modules (in claims 1-10), a human user could perform the recited operations (in claims 1-11). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to the “optimization of production planning” (Spec: p. 1), including the allocation of assignments and instructions to human workers, which (under its broadest reasonable interpretation) is an example of managing personal behavior and interactions between people as well as following instructions (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity.
The use of a mixed integer optimization problem in claim 2 is an example of a mathematical concept.
2A – Prong 2: Integrated into a Practical Application?
No – The judicial exception(s) is/are not integrated into a practical application.
The dependent claims include the additional elements of their independent claims.
Claim 1 presents an apparatus comprising an interface to import data and various modules to perform the various claim operations.
Dependent claims 2-10 further present various modules to perform the various claim operations.
Claim 7 performs a computer-aided material-flow simulation of the production according to the optimized production planning data, and generate simulation data.
Claim 11 does not present any additional elements and is, thus, directed to the abstract ideas per se.
The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: pp. 7, 9).
The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations.
The additional elements are recited at a high-level of generality (i.e., as generic processing elements performing generic computer functions) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception(s) using generic computer components. There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). Accordingly, the additional elements do not integrate the abstract ideas into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea(s).
The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process (see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)).
There is no transformation or reduction of a particular article to a different state or thing recited in the claims.
Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately.
2B: Claim(s) Provide(s) an Inventive Concept?
No – The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception(s). As discussed above with respect to integration of the abstract idea(s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exceptions using a generic computer component(s). Mere instructions to apply an exception using a generic computer component(s) cannot provide an inventive concept. The claims are not patent eligible.
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, 3-7, and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Schneider et al. (US 2023/0128899) in view of Kneisel et al. (US 2009/0094545).
[Claim 1] Schneider discloses an apparatus for optimizing production planning for production of a product, wherein workers are assigned to operate machines for producing the product (¶ 82 – “…a shift operation of workers is simulated and the production lines in the simulation are assigned workers and a change in the assignment of workers to the production lines takes place at least depending on the material requirements and/or material stocks. The entire production system is thereby further optimized.”), the apparatus comprising:
an interface to import planning data for the production and competency information regarding machine operation and availability information of the workers (¶ 81 – “According to another aspect of the invention, production parameters, optimality criteria and/or constraints are simulated. Production parameters include worker situation, machine capabilities, material availabilities, material buffers and/or supplier capacities. Optimality criteria include maximum utilization of the machines and/or workers, minimization of delays, lowest stock levels and/or minimization of material flows. The constraints include material requirements priorities, maximum storage and/or material buffer sizes, transport conditions, planning horizon, and/or supplier capacities. The entire production system is thereby further optimized.”; ¶ 82 – “If the allocation is greater than the number of available employees, see Production Parameters, the allocation will be reduced accordingly. Various factors such as material stock, line capability, requirements, etc. can be taken into account when deciding which line to reduce.”; ¶ 94 – “Another embodiment of the production planning and/or control system according to the invention comprises a cloud infrastructure. The cloud infrastructure comprises cloud-based storage. A simulation of the production system, the production planning and/or control takes place in the cloud. By means of the invention, a digital twin of the entire production system is thus obtained in the cloud. The simulation and the real production system are controlled in the cloud, according to one aspect of the invention. Thus, according to one aspect of the invention, the method according to the invention is provided as software-as-a-service. The inputs and outputs are provided via appropriate interfaces, for example wireless interfaces, for example WLAN interfaces.”; ¶ 11 – “A compact description of the invention is presented by analysis of input values or inputs entered into the system, and output values or outputs provided by the system. Inputs to the system include direct and indirect inputs.”; ¶ 36 – “The initial production sequence is also input into the real production system or the real factory for implementation.“; ¶ 94 – “The inputs and outputs are provided via appropriate interfaces, for example wireless interfaces, for example WLAN interfaces.”); and
an output module to distribute the optimized production planning data (¶ 36 – “As soon as a better result with respect to the total cost function is available from one of the downstream thorough optimization procedures, it is output and implemented directly by the system in real production or output to a human controller for assistance.”; ¶ 120 – “Outputs of the production planning and/or control system APO according to the invention comprise open-loop and/or closed-loop control signals in order to produce in a real factory according to the optimized production sequence obtained in the second sub-method. Furthermore, the outputs of the production planning and/or control system APO according to the invention comprise informational outputs for a controller of the production system.”; ¶ 94 – “Another embodiment of the production planning and/or control system according to the invention comprises a cloud infrastructure. The cloud infrastructure comprises cloud-based storage. A simulation of the production system, the production planning and/or control takes place in the cloud. By means of the invention, a digital twin of the entire production system is thus obtained in the cloud. The simulation and the real production system are controlled in the cloud, according to one aspect of the invention. Thus, according to one aspect of the invention, the method according to the invention is provided as software-as-a-service. The inputs and outputs are provided via appropriate interfaces, for example wireless interfaces, for example WLAN interfaces.”).
Schneider discloses:
a first optimization module to determine an optimized assignment of the workers to the respective machines for a defined time period based on the planning data, the competency information, and the availability information (¶ 81 – “According to another aspect of the invention, production parameters, optimality criteria and/or constraints are simulated. Production parameters include worker situation, machine capabilities, material availabilities, material buffers and/or supplier capacities. Optimality criteria include maximum utilization of the machines and/or workers, minimization of delays, lowest stock levels and/or minimization of material flows. The constraints include material requirements priorities, maximum storage and/or material buffer sizes, transport conditions, planning horizon, and/or supplier capacities. The entire production system is thereby further optimized. According to one aspect of the invention, these data form inputs for the simulation.”; ¶ 82 – “According to another aspect of the invention, a shift operation of workers is simulated and the production lines in the simulation are assigned workers and a change in the assignment of workers to the production lines takes place at least depending on the material requirements and/or material stocks. The entire production system is thereby further optimized. According to one aspect of the invention, each production line is initially fully assigned, which means that the capacity utilization according to the production parameter is a maximum. If the allocation is greater than the number of available employees, see Production Parameters, the allocation will be reduced accordingly. Various factors such as material stock, line capability, requirements, etc. can be taken into account when deciding which line to reduce.”);
a second optimization module to determine optimized production planning data, wherein an optimized time sequence of respective production steps is determined based on the planning data with respect to the workers and machines according to the assignment the number of workers needed for a production step (¶ 81 – “According to another aspect of the invention, production parameters, optimality criteria and/or constraints are simulated. Production parameters include worker situation, machine capabilities, material availabilities, material buffers and/or supplier capacities. Optimality criteria include maximum utilization of the machines and/or workers, minimization of delays, lowest stock levels and/or minimization of material flows. The constraints include material requirements priorities, maximum storage and/or material buffer sizes, transport conditions, planning horizon, and/or supplier capacities. The entire production system is thereby further optimized. According to one aspect of the invention, these data form inputs for the simulation.”; ¶ 82 – “According to another aspect of the invention, a shift operation of workers is simulated and the production lines in the simulation are assigned workers and a change in the assignment of workers to the production lines takes place at least depending on the material requirements and/or material stocks. The entire production system is thereby further optimized. According to one aspect of the invention, each production line is initially fully assigned, which means that the capacity utilization according to the production parameter is a maximum. If the allocation is greater than the number of available employees, see Production Parameters, the allocation will be reduced accordingly. Various factors such as material stock, line capability, requirements, etc. can be taken into account when deciding which line to reduce.”).
Schneider calculates a utilization to optimize the assignment of workers and machines, yet Schneider does not explicitly disclose that the optimized assignment evaluation (such as Schneider’s utilization) is necessarily calculated as a percentage. Kneisel discloses that attributes of resources (including both human and machine resources) may be used to create a work sequence in a manufacturing environment (Kneisel: ¶¶ 36-40). A resource utilization percentage may be calculated for each resource in light of each resource’s capacity (Kneisel: ¶¶ 53-57) and total resource requirements may be summed over a time period (Kneisel: ¶¶ 52-57). In other words, Kneisel demonstrates that resource utilization may be expressed as a percentage. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Schneider wherein the optimized assignment evaluation (such as Schneider’s utilization) is expressed as a percentage in order to establish a meaningful quantitative standard to identify when resources are overutilized, underutilized, etc. and also alert to potential bottleneck situations (as suggested in ¶ 100 of Kneisel, which states, “At decision block 814, the resource overload alert system 602 determines, with respect to each resource in the system to be managed, and with respect to each future time period that the resource overload alert system 602 is configured to consider, whether the resource in question is expected to be loaded in the time period in question to such an extent that an alert should be generated. That is, the resource overload alert system 602 determines whether the resource in question is expected to be overloaded for the time period in question. This determination may be made, for example, by comparing the RU for the resource for the time period with a threshold, such as 100% or 95% or 90%, etc. (It need not be the case that the same threshold is employed for every resource.) If the RU for the resource for the time period equals or exceeds the threshold, then the resource overload alert system 602 may determine that an alert condition exists for the resource for the time period in question.”).
[Claim 3] Schneider discloses wherein the first optimization module takes into account at least one of the following boundary conditions in determining the optimized assignment of the workers to the respective machines:
minimizing a change in workstation by a worker;
even utilization of a worker; and/or
compliance with machine-specific criteria (¶¶ 14-17 – “[0014] Production parameters: worker situation, machine capabilities, materials availability, initial warehouse and buffer stocks, and/or supplier capacity; [0015] Material requirements: which material/semi-finished product must be produced at which time and/or weighting/prioritizing of the parts to be produced; [0016] Optimality criteria: maximum utilization of all machines and staff, minimization of delays, lowest warehouse stock levels, minimization of material flows from areas far apart within the factory and/or weighting them against each other and [0017] Constraints: In contrast to the optimality criteria, these must be strictly adhered to for an optimization run to be started. These are, for example, priorities of requirements with rank 1 which must always be produced at a specified time, storage/intermediate storage quantities that must not be exceeded, no transport of parts from one production line/store to another production line/store that is not currently practical for logistical or other reasons. The constraints can be changed by the controller. The planning horizon, for example, the number of hours or days over which the production schedule is to be planned in advance, also forms one of the constraints.”).
[Claim 4] Schneider discloses wherein the second optimization module takes into account at least one of the following boundary conditions in determining the optimized production planning data:
compliance with a defined sequence of the production steps (¶¶ 35-37 – Production sequences are optimized and re-optimized, as needed.);
taking into account the bill of materials and/or bill of process (¶ 116 – “The requirement thus selected is implemented when there are sufficient input materials available to fully satisfy the requirement. In this case, the input materials are reserved for this requirement. If there are not enough supplied input materials available, a check is made to determine whether it is possible to deliver them at the current time. Constraints may include supplier capacities. In the positive case, a corresponding delivery is ordered and the delivered material is reserved. In the negative case, the next requirement is selected according to the data structure. If an input material can be both produced and delivered, then the initial delivery and buffer stocks are reduced as described above, with the difference that, in contrast to initial buffer stocks, the delivery time must be taken into account.”);
compliance with a completion date (¶¶ 43-44 – material requirement deadlines);
a defined capacity of a machine (¶ 88 – “The line capacity is a constraint and relates to technical limitations of the respective production line. The material requirement that can run on a production line is not necessarily the material requirement with the highest priority, depending on the line capacity. By taking into account the line capacity, the entire production system is thus further optimized. According to one aspect of the invention, the line capacity is input into the simulation.”); and/or
minimizing retooling times.
[Claim 5] Schneider discloses wherein the second optimization module determines, in the event that the production deviates in time from the optimized production planning data, re-optimized production planning data according to the optimized assignment (¶¶ 35-37 – Production sequences are optimized and re-optimized, as needed.; ¶ 37 – “When an event occurs that affects production, such as machine failure or a changed worker situation, a new initial production sequence is devised and the method starts again from the beginning.”).
Schneider calculates a utilization to optimize the assignment of workers and machines, yet Schneider does not explicitly disclose that the optimized assignment evaluation (such as Schneider’s utilization) is necessarily calculated as a percentage. Kneisel discloses that attributes of resources (including both human and machine resources) may be used to create a work sequence in a manufacturing environment (Kneisel: ¶¶ 36-40). A resource utilization percentage may be calculated for each resource in light of each resource’s capacity and total resource requirements may be summed over a time period (Kneisel: ¶¶ 52-57). In other words, Kneisel demonstrates that resource utilization may be expressed as a percentage. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Schneider wherein the optimized assignment evaluation (such as Schneider’s utilization) is expressed as a percentage in order to establish a meaningful quantitative standard to identify when resources are overutilized, underutilized, etc. and also alert to potential bottleneck situations (as suggested in ¶ 100 of Kneisel, which states, “At decision block 814, the resource overload alert system 602 determines, with respect to each resource in the system to be managed, and with respect to each future time period that the resource overload alert system 602 is configured to consider, whether the resource in question is expected to be loaded in the time period in question to such an extent that an alert should be generated. That is, the resource overload alert system 602 determines whether the resource in question is expected to be overloaded for the time period in question. This determination may be made, for example, by comparing the RU for the resource for the time period with a threshold, such as 100% or 95% or 90%, etc. (It need not be the case that the same threshold is employed for every resource.) If the RU for the resource for the time period equals or exceeds the threshold, then the resource overload alert system 602 may determine that an alert condition exists for the resource for the time period in question.”).
[Claim 6] Schneider discloses wherein at least one of the first optimization module and the second optimization module is configured to re-execute the associated optimization on the basis of a current production status (¶¶ 35-37 – Production sequences are optimized and re-optimized, as needed.; ¶ 37 – “When an event occurs that affects production, such as machine failure or a changed worker situation, a new initial production sequence is devised and the method starts again from the beginning.”).
[Claim 7] Schneider discloses a simulation module to perform a computer-aided material-flow simulation of the production according to the optimized production planning data, and generate simulation data (¶ 83 – “The entire production system is thereby further optimized. If an input material can be both produced and delivered, according to a further aspect of the invention the initial delivery and buffer stocks are reduced as described above, with the difference that, in contrast to initial buffer stocks, the delivery time must be taken into account. According to one aspect of the invention, the second check, the supplier orders, supplier capacities, delivery times and/or supplier control are input into the simulation.”; ¶ 94 – “A simulation of the production system, the production planning and/or control takes place in the cloud. By means of the invention, a digital twin of the entire production system is thus obtained in the cloud. The simulation and the real production system are controlled in the cloud, according to one aspect of the invention. Thus, according to one aspect of the invention, the method according to the invention is provided as software-as-a-service.”).
[Claim 9] Schneider discloses a validation module to validate the optimized production planning data on the basis of the simulation data (¶¶ 66-74 – Fitness functions are used to identify a best solution of multiple candidate solutions.; ¶¶ 81-82 – Various scenarios are simulated.; ¶ 92 – “According to a further aspect of the invention, in the simulation a digital twin of a real factory is generated, a planning horizon is determined for the digital twin and the real factory is controlled by means of the planning horizon.”; ¶ 94 – “A simulation of the production system, the production planning and/or control takes place in the cloud. By means of the invention, a digital twin of the entire production system is thus obtained in the cloud. The simulation and the real production system are controlled in the cloud, according to one aspect of the invention. Thus, according to one aspect of the invention, the method according to the invention is provided as software-as-a-service. The inputs and outputs are provided via appropriate interfaces, for example wireless interfaces, for example WLAN interfaces.”).
[Claim 10] Schneider discloses a prediction module to predict production-relevant data on the basis of the simulation data (¶ 53 – “The simulation provides a virtual representation of the production system, production planning and/or production control, in which the entire production system is implemented as a digital twin. For example, the simulation includes the simulation of bottlenecks or critical paths. The simulation simulates a future state of the production system, according to one aspect of the invention. This enables planning horizons stretching as far into the future as desired, for example in the range of several weeks. Through the simulation, the optimization achieved by the method according to the invention, and thus the entire production system, is adapted to production changes in an advantageous way.”; ¶ 92 – “According to a further aspect of the invention, in the simulation a digital twin of a real factory is generated, a planning horizon is determined for the digital twin and the real factory is controlled by means of the planning horizon.”; ¶ 94 – “A simulation of the production system, the production planning and/or control takes place in the cloud. By means of the invention, a digital twin of the entire production system is thus obtained in the cloud. The simulation and the real production system are controlled in the cloud, according to one aspect of the invention. Thus, according to one aspect of the invention, the method according to the invention is provided as software-as-a-service. The inputs and outputs are provided via appropriate interfaces, for example wireless interfaces, for example WLAN interfaces.”).
[Claim 11] Claim 11 recites limitations already addressed by the rejection of claim 1 above; therefore, the same rejection applies.
Furthermore, Schneider discloses that the step of distributing the optimized production planning data is for producing the product in accordance with the optimized production planning data (Schneider: ¶ 36 – “As soon as a better result with respect to the total cost function is available from one of the downstream thorough optimization procedures, it is output and implemented directly by the system in real production or output to a human controller for assistance.”; ¶ 120 – “Outputs of the production planning and/or control system APO according to the invention comprise open-loop and/or closed-loop control signals in order to produce in a real factory according to the optimized production sequence obtained in the second sub-method. Furthermore, the outputs of the production planning and/or control system APO according to the invention comprise informational outputs for a controller of the production system.”).
Claims 2 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Schneider et al. (US 2023/0128899) in view of Kneisel et al. (US 2009/0094545), as applied to claim 1 (for claim 2) and to claims 1 and 7 (for claim 8) above, in view of Brown et al. (US 2022/0253954).
[Claim 2] Schneider does not explicitly disclose wherein the first optimization module determines the optimized assignment of the workers to the respective machines using a mixed integer optimization problem. Brown uses mixed integer programs to schedule resources in a production environment (Brown: abstract, ¶¶ 80, 83, 86-87). Brown suggests that the use of mixed integer optimization can be adjusted to be a linear or non-linear problem based on the number of constraints that are to be taken into account, thereby providing some flexibility in balancing granularity with tractability (Brown: ¶ 83 – “Based on this, it is possible to introduce additional variables and constraints to convert the MINP above to an MILP. However, for long horizons or when each node 302 can produce many materials, this approach results in many additional variables and constraints. In fact, the number of constraints and variables can grow quadratically as a function of horizon and the number of materials at each node 302. Thus, the following alternative approach can be used for such cases in some embodiments.”; ¶ 87 – “For example, the transition cost term in Equation (19), along with associated variables and constraints, can be removed from the problem formulation. It is also possible to remove consideration of changeover times from the problem formulation. The resulting problem is a much more tractable mixed integer linear program. The second module or step can be responsible for post-processing the relaxed solution into a feasible and near-optimal production schedule.”). Schneider’s resources may be both human and machine resources. Brown’s use of mixed integer programming would be adaptable to any type of resource, including in a manufacturing environment. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Schneider wherein the first optimization module determines the optimized assignment of the workers to the respective machines using a mixed integer optimization problem in order to facilitate optimization of resource allocation in a production environment with the ability to balance the granularity of the number of constraints to be considered with tractability (as suggested in ¶¶ 83 and 87 of Brown).
[Claim 8] Schneider addresses the use of a simulation module (Schneider: ¶¶ 83, 94); however, Schneider does not explicitly disclose wherein the simulation module accounts for transport times between machines. As explained in Brown, in evaluating an optimal production schedule, costs and objectives are taken into account (Brown: ¶ 49) and costs and objectives may be associated with transportation times of materials between nodes (Brown: ¶ 46) as well as the reduction of the number of transitions across multiple production lines (Brown: ¶ 118). The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Schneider wherein the simulation module accounts for transport times between machines in order to facilitate more granular analysis of multiple factors that affect production efficiency in practice, thereby improving the accuracy and efficiency of the corresponding optimization analysis and resulting resource allocation.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chua et al. (US 2005/0114202) – Evaluates machine utilization to assess efficiency of a work center.
Kolodner et al. (US 2020/0210939) – Evaluates a percentage of availability for time windows.
Schneider et al. (US 2023/0115525) – Maximizes utilization of machines.
Venkataraman et al. (US 2023/0061899) – Forecasts resource utilization percentages.
Dar Mousa et al. (US 2020/0175456) – Uses integer programming to allocate jobs in a production line.
Hamilton et al. (US 2015/0106145) – Evaluates a percentage of available skilled employees for work in a queue.
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/SUSANNA M. DIAZ/
Primary Examiner
Art Unit 3625A