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 .
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 therefore, subject to the conditions and requirements of this title.
Claims 1-18 and 25-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Whether a Claim is to a Statutory Category
In the instant case, claims 1-18 recite a method/ process, claim 25 recites a apparatus/ machine and claim 26 recites a computer program product comprising a non-transitory computer readable medium/ machine that are performing a series of functions. Therefore, these claims fall within the four statutory categories of invention of a machine and a process. Step 1 is satisfied.
Step2A – Prong 1: Does the Claim Recite a Judicial Exception
Exemplary claim 1 (and similarly claims 25 and 26) recites the following abstract concepts that are found to include an enumerated “abstract idea”:
A computer-implemented method, comprising:
obtaining data on a plurality of materials for making one or more products;
identifying a first group of one or more materials from the plurality of materials, a respective material in the first group is a replaceable material with respect to at least one of the one or more product;
calculating a maximum consumption of the respective material in the first group in a period using a linear programming model with respect to the at least one of the one or more product;
comparing the maximum consumption of the respective material in the first group in the period with an available inventory amount of the respective material in the first group; and
determining whether the respective material in the first group is overstocked in the period.
[Emphasis added to show the bolded abstract idea being executed by unbolded additional elements that do not meaningfully limit the abstract idea]
This method claim is grouped within the “certain methods of organizing human activity” and “mathematical concepts” groupings of abstract ideas in prong one of step 2A of the Alice/Mayo test because the claims involve a series of steps for commercial or legal interactions through mathematical calculations to determine whether the respective material in the first group is overstocked in the period. This is a process that is encompassed by the abstract ideas of certain methods of organizing human activity and mathematical concepts because the broadest reasonable interpretation of the claim limitations discloses a process for business relations of inventory management. See e.g., MPEP 2106.04(a)(2)(I)(C) & (II)(B). Accordingly, claim 1 (and similarly claims 25 and 26) recite an abstract idea.
Step2A – Prong 2: Does the Claim Recite Additional Elements that Integrate the Judicial Exception into a Practical Application
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test, the additional elements of the claims such as computer and linear programming model merely use a computer as a tool to perform an abstract idea and/or generally link the use of a judicial exception to a particular technological environment. Specifically, the computer and linear programming model perform the steps or functions of commercial or legal interactions through mathematical calculations to determine whether the respective material in the first group is overstocked in the period. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer (or technical elements disclosed at a high level of generality such as computer and linear programming model) performing functions of obtaining, identifying, calculating, comparing and determining that correspond to acts required to carry out the abstract idea (MPEP 2106.05(f) and (h)). Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
Step2B: Does the Claim Amount to Significantly More
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element analysis of Step 2A Prong 2 is equally applied to Step 2B. “Another consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry. This consideration is only evaluated in Step 2B of the eligibility analysis.” MPEP 2106.05(d). The courts have recognized the following computer functions as well‐understood, routine, and conventional (“WURC”) functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. Exemplary claim 1 recites the following limitations that the courts have found to be WURC:
Claim 1 includes several limitations relating to receiving or transmitting data over a network (obtaining data on a plurality of materials …; as claimed). See MPEP 2106.05(d)(II) where courts found to be WURC - i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added));
Claim 1 includes several limitations relating to storing and retrieving information in memory (identifying a first group of one or more materials from the plurality of materials, a respective material in the first group is a replaceable material with respect to at least one of the one or more product; as claimed). See MPEP 2106.05(d)(II) where courts found to be WURC - ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.")
Claim 1 includes several limitations relating to performing repetitive calculations (identifying a first group of one or more materials from the plurality of materials…; calculating a maximum consumption of the respective material in the first group in a period…; comparing the maximum consumption of the respective material in the first group in the period with an available inventory amount of the respective material in the first group; determining whether the respective material in the first group is overstocked in the period; as claimed). See MPEP 2106.05(d)(II) where courts found to be WURC - ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (“The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.”);
Accordingly, when viewed alone and in ordered combination, these additional elements are not found to recite significantly more than the underlying abstract idea.
Independent claim 25 describes an apparatus performing the functions of obtaining, identifying, calculating, comparing and determining also relating to mathematical calculations without additional elements beyond technical elements disclosed at a high level of generality such as a memory, processors and linear programming model that provide significantly more than the abstract idea of commercial or legal interactions through mathematical calculations to determine whether the respective material in the first group is overstocked in the period as noted above regarding claim 1. Therefore, this independent claim is also not patent eligible.
Independent claim 26 describes an apparatus performing the functions of obtaining, identifying, calculating, comparing and determining also relating to mathematical calculations without additional elements beyond technical elements disclosed at a high level of generality such as a computer program, non-transitory computer readable medium, processors and linear programming model that provide significantly more than the abstract idea of commercial or legal interactions through mathematical calculations to determine whether the respective material in the first group is overstocked in the period as noted above regarding claim 1. Therefore, this independent claim is also not patent eligible.
Dependent claims 2-18 further describe the abstract idea of commercial or legal interactions through mathematical calculations to determine whether the respective material in the first group is overstocked in the period. These claims merely include descriptive material expressing the mathematical formulas used to perform the mathematical calculations or otherwise do not include additional elements to perform their respective functions of identifying, comparing, determining, calculating, subtracting, summation, multiplication, performing, extracting, updating, adjusting, indicating and producing beyond the technical elements disclosed at a high level of generality such as a computer and as disclosed in independent claim 1 that integrate the abstract idea into a practical application or that provide significantly more than the abstract idea. Therefore, these dependent claims are also not patent eligible. Further, the dependency of these claims on ineligible independent claim 1 also renders dependent claims 2-18 as not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 5-9 and 11-18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dietrich et al. (US 5,630,070).
Regarding claim 1, Dietrich teaches:
A computer-implemented method (See Dietrich Abstract - A method for constrained material requirements planning, optimal resource allocation, and production planning provides for an optimization of a manufacturing process by designating the amounts of various manufactured products to be produced, … are presented as a set of linear mathematical relationships in matrix form to be inserted in a computer which determines the optimum number of each end product in accordance with an LP optimization algorithm), comprising:
obtaining data on a plurality of materials for making one or more products (See Dietrich Fig. 10: inputs 1-6 - Demand Data; Inventory Data; Bill of Material Data; Bill of Resource Data; Resource Availability Data; Cost & Revenue Data);
identifying a first group of one or more materials from the plurality of materials, a respective material in the first group is a replaceable material with respect to at least one of the one or more product (See Dietrich Col. 25 lines 6-24 - Often a product can be built using a part or resource other than the one specified on its BOM or BOR. For example, fast memory modules can be substituted for slow memory modules, but slow modules cannot usually be substituted for fast ones. If substitute part and substitute resource information is given, the resource allocation tool can be used to determine the optimal use of primary and substitution resources. Additional inputs: for each BOM entry, substitute information consisting of the substitute part, usage quantity, effectivity dates, and cost or priority information; For each BOR entry, substitute information consisting of the substitute resource, usage quantity, effectivity dates, and cost or priority information);
calculating a maximum consumption of the respective material in the first group in a period using a linear programming model with respect to the at least one of the one or more product (See Dietrich Col. 1 lines 40-45 - One method of representing such allocation decision problems is known as a linear programming model. Such a model consists of a number of linear relationships, set forth in matrix format, and representing quantitatively the relationships among allocations, constraints and results of an industrial or other technological process, Col. 24 lines 53-57 - If desirable, the formulation can be augmented to include minimum and maximum production quantities in each period, maximum backlog per demand and period, and minimum and maximum stock quantities for each p/n in each period and Col. 31 lines 58-61 - Bill of materials: Can include alternate bill-of-materials for a part. Can include substitution parts for a product component pair. Includes effectivity dates, usage rate, fallout, usage offset);
comparing the maximum consumption of the respective material in the first group in the period with an available inventory amount of the respective material in the first group (See Dietrich Col. 17 lines 21-27 - Notice that in the single period model the resource and material availability constraints were inequalities. In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period); and
determining whether the respective material in the first group is overstocked in the period (See Dietrich Col. 7 lines 35-40 - In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich).
Regarding claim 5, Dietrich teaches:
The computer-implemented method of claim 1, further comprising
identifying a second group of one or more materials from the plurality of materials, a respective material in the second group is a non-replaceable material with respect to at least one of the one or more product (See Dietrich Col. 25 lines 6-24 - Often a product can be built using a part or resource other than the one specified on its BOM or BOR. For example, fast memory modules can be substituted for slow memory modules, but slow modules cannot usually be substituted for fast ones);
comparing a respective theoretical consumption of the respective material in the second group in the period with a respective inventory amount of the respective material in the second group (See Dietrich Col. 17 lines 21-27 - Notice that in the single period model the resource and material availability constraints were inequalities. In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period and Col. 31 lines 28-61 - In the diagram, the demand data, bill-of-material data, and inventory data are extracted from the Material Requirements Planning System, the bill-of resource data and the resource availability data are extracted from the Capacity Requirements Planning system… Use the Optimal Resource Allocation procedure to determine an optimal shipment schedule and the corresponding production schedule and part usage schedule [theoretical consumption by example]… Demand data: can include backlogged orders, accepted orders, planned orders, and forecasted orders [theoretical consumption by example]); and
determining that whether the respective material in the second group is overstocked in the period (See Dietrich Col. 7 lines 25-40 - Accordingly, the foregoing quantities of each of the four ingredients of the vegetable omelet would be multiplied by six to obtain the total amount of raw materials employed in meeting the customer demand for vegetable omelet. Similar calculations would be employed for each of the other food products, and the results are to be summed together to give a grand total of the quantities of the raw materials of all the demanded food products. In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich).
Regarding claim 6, Dietrich teaches:
The computer-implemented method of claim 5, upon determination that the respective theoretical consumption of the respective material in the second group in the period is equal to or greater than the respective inventory amount of the respective material in the second group, comprising determining that the respective material in the second group is not overstocked in the period (See Dietrich Col. 7 lines 44-52 - As will be seen in the following example, there is an insufficiency, or shortage, for each ingredient except for mushrooms wherein there is an excess, as indicated in Table 5. Note that, in Table 5, the amount of the shortage of mushrooms is shown as zero to avoid the appearance of negative amounts in the ensuing mathematical explanation and as shown in Table 5).
Regarding claim 7, Dietrich teaches:
The computer-implemented method of claim 5, upon determination that the respective theoretical consumption of the respective material in the second group in the period is less than the respective inventory amount of the respective material in the second group, further comprising:
determining whether the respective material in the second group is a replaceable material with respect to another product of the one or more products. (See Dietrich Col. 25 lines 13-16 - If substitute part and substitute resource information is given, the resource allocation tool can be used to determine the optimal use of primary and substitution resources and 33 lines 53-56 - Inventory data for raw material part numbers which are not on the pre-specified critical parts list and have demand are replaced by the total demand for that part number in each time period).
Regarding claim 8, Dietrich teaches:
The computer-implemented method of claim 7, upon determination that the respective material in the second group is not a replaceable material with respect to any product of the one or more products, further comprising determining that the respective material in the second group is overstocked in the period (See Dietrich Col. 7 lines 25-40 - Accordingly, the foregoing quantities of each of the four ingredients of the vegetable omelet would be multiplied by six to obtain the total amount of raw materials employed in meeting the customer demand for vegetable omelet. Similar calculations would be employed for each of the other food products, and the results are to be summed together to give a grand total of the quantities of the raw materials of all the demanded food products. In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich and Col. 33 lines 46-56 - the bill-of material data is processed to eliminate from each bill-of materials all raw material part numbers which are not in the pre-specified set of critical [not replaceable by example] parts, and all product part numbers which do not use, either directly or on subassemblies, raw materials in the pre-specified set of critical parts. A resulting "stripped" bill-of materials may have no component parts. Inventory data for raw material part numbers which are not on the pre-specified critical parts list and have demand are replaced by the total demand for that part number in each time period).
Regarding claim 9, Dietrich teaches:
The computer-implemented method of claim 7, upon determination that the respective material in the second group is a replaceable material with respect to the another product (See Dietrich Col. 25 lines 13-16 - If substitute part and substitute resource information is given, the resource allocation tool can be used to determine the optimal use of primary and substitution resources and 33 lines 53-56 - Inventory data for raw material part numbers which are not on the pre-specified critical parts list and have demand are replaced by the total demand for that part number in each time period), further comprising:
calculating a maximum consumption of the replaceable material in the period using a linear programming model with respect to the another product (See Dietrich Col. 1 lines 40-45 - One method of representing such allocation decision problems is known as a linear programming model. Such a model consists of a number of linear relationships, set forth in matrix format, and representing quantitatively the relationships among allocations, constraints and results of an industrial or other technological process, Col. 24 lines 53-57 - If desirable, the formulation can be augmented to include minimum and maximum production quantities in each period, maximum backlog per demand and period, and minimum and maximum stock quantities for each p/n in each period and Col. 31 lines 58-61 - Bill of materials: Can include alternate bill-of-materials for a part. Can include substitution parts for a product component pair. Includes effectivity dates, usage rate, fallout, usage offset);
comparing the maximum consumption of the replaceable material in the period with an available inventory amount of the replaceable material (See Dietrich Col. 17 lines 21-27 - Notice that in the single period model the resource and material availability constraints were inequalities. In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period); and
determining whether the replaceable material is overstocked in the period (See Dietrich Col. 7 lines 35-40 - In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich);
wherein the available inventory amount of the replaceable material is equal to the respective inventory amount subtracted by the respective theoretical consumption of the replaceable material in the period (See Dietrich Col. 17 lines 22-26 - In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period).
Regarding claim 11, Dietrich teaches:
The computer-implemented method of claim 5, comprising a plurality of first steps and a plurality of second steps;
wherein at least one first step of the plurality of first steps is performed prior to performing at least one second step of the plurality of second steps (See Dietrich Col. 33 lines 44-51 - in Step 1, demand data, bill-of-material data, inventory data, and cost and revenue data are extracted from an MRP system. In a subsequent step (Step 1a) the bill-of material data is processed to eliminate from each bill-of materials all raw material part numbers which are not in the pre-specified set of critical parts, and all product part numbers which do not use, either directly or on subassemblies, raw materials in the pre-specified set of critical parts.);
wherein the plurality of first steps comprise at least one of:
identifying the second group of one or more materials from the plurality of materials (See Dietrich Col. 33 lines 44-51 - in Step 1, demand data, bill-of-material data, inventory data, and cost and revenue data are extracted from an MRP system. In a subsequent step (Step 1a) the bill-of material data is processed to eliminate from each bill-of materials all raw material part numbers which are not in the pre-specified set of critical parts [second group by example], and all product part numbers which do not use, either directly or on subassemblies, raw materials in the pre-specified set of critical parts.);
comparing the respective theoretical consumption of the respective material in the second group in the period with the respective inventory amount of the respective material in the second group (See Dietrich Col. 17 lines 21-27 - Notice that in the single period model the resource and material availability constraints were inequalities. In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period and Col. 31 lines 28-61 - In the diagram, the demand data, bill-of-material data, and inventory data are extracted from the Material Requirements Planning System, the bill-of resource data and the resource availability data are extracted from the Capacity Requirements Planning system… Use the Optimal Resource Allocation procedure to determine an optimal shipment schedule and the corresponding production schedule and part usage schedule [theoretical consumption by example]… Demand data: can include backlogged orders, accepted orders, planned orders, and forecasted orders [theoretical consumption by example]); or
determining that whether the respective material in the second group is overstocked in the period (See Dietrich Col. 7 lines 25-40 - Accordingly, the foregoing quantities of each of the four ingredients of the vegetable omelet would be multiplied by six to obtain the total amount of raw materials employed in meeting the customer demand for vegetable omelet. Similar calculations would be employed for each of the other food products, and the results are to be summed together to give a grand total of the quantities of the raw materials of all the demanded food products. In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich);
wherein the plurality of second steps comprise at least one of:
identifying the first group of one or more materials from the plurality of materials (See Dietrich Col. 34 lines 5-10 - Subsequent to Step 1 in Step 1b the inventory data for every raw-material not on the per-specified critical component list [first group of materials by example], the inventory data is replaced by the vector (MMM, ... M) where M is some very large quantity (e.g., expected total annual part usage));
calculating the maximum consumption of the respective material in the first group in the period using the linear programming model with respect to the at least one of the one or more product (See Dietrich Col. 1 lines 40-45 - One method of representing such allocation decision problems is known as a linear programming model. Such a model consists of a number of linear relationships, set forth in matrix format, and representing quantitatively the relationships among allocations, constraints and results of an industrial or other technological process, Col. 24 lines 53-57 - If desirable, the formulation can be augmented to include minimum and maximum production quantities in each period, maximum backlog per demand and period, and minimum and maximum stock quantities for each p/n in each period and Col. 31 lines 58-61 - Bill of materials: Can include alternate bill-of-materials for a part. Can include substitution parts for a product component pair. Includes effectivity dates, usage rate, fallout, usage offset);
comparing the maximum consumption of the respective material in the first group in the period with the available inventory amount of the respective material in the first group (See Dietrich Col. 17 lines 21-27 - Notice that in the single period model the resource and material availability constraints were inequalities. In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period); or
determining whether the respective material in the first group is overstocked in the period (See Dietrich Col. 7 lines 35-40 - In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich).
Regarding claim 12, Dietrich teaches:
The computer-implemented method of claim 1, further comprising:
extracting data on materials in the first group from the data on the plurality of materials for making one or more products (See Dietrich Col. 33 lines 44-51 - demand data, bill-of-material data, inventory data, and cost and revenue data are extracted from an MRP system. In a subsequent step (Step 1a) the bill-of material data is processed to eliminate from each bill-of materials all raw material part numbers which are not in the pre-specified set of critical parts, and all product part numbers which do not use, either directly or on subassemblies, raw materials in the pre-specified set of critical parts.); and
updating the data on materials in the first group upon determination an individual material in the first group is also a non-replaceable material with respect to another product of the one or more products (See Dietrich Col. 33 lines 44-51 - demand data, bill-of-material data, inventory data, and cost and revenue data are extracted from an MRP system. In a subsequent step (Step 1a) the bill-of material data is processed to eliminate from each bill-of materials all raw material part numbers which are not in the pre-specified set of critical parts [updating the data on materials in the first group upon determination an individual material in the first group is also a non-replaceable material by example], and all product part numbers which do not use, either directly or on subassemblies, raw materials in the pre-specified set of critical parts.).
Regarding claim 13, Dietrich teaches:
The computer-implemented method of claim 12, wherein an available inventory amount of the individual material for the purpose of calculating a maximum consumption thereof is updated as being equal to an actual inventory amount of the individual material subtracted by a respective theoretical consumption in the period of the individual material as the non-replaceable material with respect to the another product (See Dietrich Col. 17 lines 21-27 - In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period).
Regarding claim 14, Dietrich teaches:
The computer-implemented method of claim1, upon determination the respective material in the first group or the respective material in the second group is overstocked in the period, further comprising determining an overstock status for the respective material in the first group or the respective material in the second group that is overstocked in the period (See Dietrich Col. 7 lines 25-40 - Accordingly, the foregoing quantities of each of the four ingredients of the vegetable omelet would be multiplied by six to obtain the total amount of raw materials employed in meeting the customer demand for vegetable omelet. Similar calculations would be employed for each of the other food products, and the results are to be summed together to give a grand total of the quantities of the raw materials of all the demanded food products. In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich);
wherein the overstock status is one of a first status, a second status, a third status, or a fourth status (See Dietrich teaching multiple stocking statuses by example below);
wherein, in the first status, a demand for an overstocked material is zero in an entirety of the period (See Dietrich Col. 8 Table 2 – demand for a plain sandwich is zero);
the period comprises a first sub-period followed by a second sub-period (See Dietrich Col. 16 lines 10-16 – requirements [demand by example] for an early lunch and a late lunch period);
in the second status, the demand for the overstocked material is zero in the second sub-period, and is non-zero in the first sub-period (See Dietrich Col. 15 lines 41-50 – plain sandwiches are non-zero initially, then zero secondarily);
in the third status, the demand for the overstocked material is zero in the first sub- period, and is non-zero in the second sub-period (See Dietrich Col. 16 lines 10-16 – requirements for cheese are null/ zero for an early lunch and non-zero for a late lunch period); and
in the fourth status, the demand for the overstocked material is non-zero in the first sub-period, and is non-zero in the second sub-period (See Dietrich Col. 16 lines 10-16 – requirements for bread are non-zero for both early and late lunch periods).
Regarding claim 15, Dietrich teaches:
The computer-implemented method of claim1, upon determination the respective material in the first group or the respective material in the second group is overstocked in the period, further comprising:
determining one or more underlying reasons for material overstock (See Dietrich Col. 2 lines 37-41 – An attempt to run an infeasible production plan can result in missed customer shipments, excess raw material inventory, long cycle times, production bottlenecks, poorly utilized capacity, and idle workers.); and
adjusting one or more production parameters in the period for the one or more products to minimize the material overstock (See Dietrich Col. 24 lines 53-57 – the formulation can be augmented to include minimum and maximum production quantities in each 55 period, maximum backlog per demand and period, and minimum and maximum stock quantities for each p/n in each period.).
Regarding claim 16, Dietrich teaches:
The computer-implemented method of claim1, wherein the data comprises data on priority level of the one or more materials in the first group (See Dietrich Col. 25 lines 18-21 – for each BOM entry, substitute information consisting of the substitute part, usage quantity, effectivity dates, and cost or priority information);
a higher priority level for a material in the first group indicates the material is more preferred in producing a corresponding product over one having a lower priority level (See Dietrich Col. 37 lines 15-25 – LP variables, translates these values into a shipment schedule and a production schedule. In addition, the “dual variable” are also extracted from the LP solver, and those corresponding to material availability constraints and capacity availability constraints are sorted in decreasing order [higher priority level over a lower priority by example]. Among this set, the constraint with the largest dual variable corresponds to a capacity or material, and a time period such that obtaining more of that capacity or resource in that time period will have the greatest impact on total profit [more preferred by example]. A list of pairs (material or resource, time period) that have the most potential for impacting profit are reported.).
Regarding claim 17, Dietrich teaches:
The computer-implemented method of claim 16, upon determination the respective material in the first group is overstocked in the period, further comprising:
adjusting the priority level of the respective material in the first group; and
producing the one or more products based on adjusted priority level of the one or more materials in the first group (See Dietrich Col. 37 lines 15-25 – LP variables, translates these values into a shipment schedule and a production schedule. In addition, the “dual variable” are also extracted from the LP solver, and those corresponding to material availability constraints and capacity availability constraints are sorted [adjusting by example] in decreasing order. Among this set, the constraint with the largest dual variable corresponds to a capacity or material, and a time period such that obtaining [producing by example] more of that capacity or resource in that time period will have the greatest impact on total profit. A list of pairs (material or resource, time period) that have the most potential for impacting profit are reported.).
Regarding claim 18, Dietrich teaches:
The computer-implemented method of claim1, upon determination the respective material in the first group or the respective material in the second group is overstocked in the period (See Dietrich Col. 7 lines 25-40 - Accordingly, the foregoing quantities of each of the four ingredients of the vegetable omelet would be multiplied by six to obtain the total amount of raw materials employed in meeting the customer demand for vegetable omelet. Similar calculations would be employed for each of the other food products, and the results are to be summed together to give a grand total of the quantities of the raw materials of all the demanded food products. In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich), further comprising:
adjusting a demand in the period for the one or more products to minimize material overstock (See Dietrich Col. 37 lines 26-52 - determines the optimal allocation of on-hand materials and capacities to products so as to minimize the value of the remaining inventory [minimize material overstock by example]... The demand data is adjusted, if necessary, to reflect potential demand for each of the possible end products. …Since the only coefficients in the objective function are holding costs for inventory in the final period, production and shipment schedule correspond to an allocation of resources that minimizes the value of the final inventory.); and
producing the one or more products based on adjusted demand in the period for the one or more products (See Dietrich Col. 37 lines 26-52 - determines the optimal allocation of on-hand materials and capacities to products so as to minimize the value of the remaining inventory... Inventory data is extracted for on-hand and firm order inventory only. The demand data is adjusted, if necessary, to reflect potential demand for each of the possible end products... In Step 2, the Optimal Resource Allocation Procedure processes this data and formulates the Linear Program. The then LP solver is invoked, and the optimal values of the Lp variables are extracted and translated into a shipment schedule and a production schedule [producing by example]. Since the only coefficients in the objective function are holding costs for inventory in the final period, production and shipment schedule correspond to an allocation of resources that minimizes the value of the final inventory.).
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 25 and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Dietrich et al. (US 5,630,070) in view of Wessela et al. (US 2021/0312377 A1).
Regarding claim 25, Dietrich teaches:
An apparatus for managing production of one or more products (See Dietrich Col. 4 lines 1-6 - data describing elemental steps in the manufacturing process for the production of each end product, as well as the quantity or demand for each end product which is to be supplied, are presented as a set of linear mathematical relationships in matrix form to be inserted in a computer), comprising:
…
obtain data on a plurality of materials for making one or more products (See Dietrich Fig. 10: inputs 1-6 - Demand Data; Inventory Data; Bill of Material Data; Bill of Resource Data; Resource Availability Data; Cost & Revenue Data);
identify a first group of one or more materials from the plurality of materials, a respective material in the first group is a replaceable material with respect to at least one of the one or more product (See Dietrich Col. 25 lines 6-24 - Often a product can be built using a part or resource other than the one specified on its BOM or BOR. For example, fast memory modules can be substituted for slow memory modules, but slow modules cannot usually be substituted for fast ones. If substitute part and substitute resource information is given, the resource allocation tool can be used to determine the optimal use of primary and substitution resources. Additional inputs: for each BOM entry, substitute information consisting of the substitute part, usage quantity, effectivity dates, and cost or priority information; For each BOR entry, substitute information consisting of the substitute resource, usage quantity, effectivity dates, and cost or priority information);
calculate a maximum consumption of the respective material in the first group in a period using a linear programming model with respect to the at least one of the one or more product (See Dietrich Col. 1 lines 40-45 - One method of representing such allocation decision problems is known as a linear programming model. Such a model consists of a number of linear relationships, set forth in matrix format, and representing quantitatively the relationships among allocations, constraints and results of an industrial or other technological process, Col. 24 lines 53-57 - If desirable, the formulation can be augmented to include minimum and maximum production quantities in each period, maximum backlog per demand and period, and minimum and maximum stock quantities for each p/n in each period and Col. 31 lines 58-61 - Bill of materials: Can include alternate bill-of-materials for a part. Can include substitution parts for a product component pair. Includes effectivity dates, usage rate, fallout, usage offset);
compare the maximum consumption of the respective material in the first group in the period with an available inventory amount of the respective material in the first group (See Dietrich Col. 17 lines 21-27 - Notice that in the single period model the resource and material availability constraints were inequalities. In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period); and
determine whether the respective material in the first group is overstocked in the period (See Dietrich Col. 7 lines 35-40 - In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich).
While Dietrich teaches a system for managing a manufacturing process based on linear program optimization algorithm that is inserted into a computer, (Dietrich Abstract), Dietrich does not explicitly teach that said computer comprises a memory; one or more processors; wherein the memory and the one or more processors are connected with each other; and the memory stores computer-executable instructions for controlling the one or more processors. This is taught by Wessela (See ¶ [0070] – The computer programs (also referred to as programs, software, software applications, “apps”, or code) may include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, apparatus, cloud storage, internet of things, and/or device (e.g., magnetic discs, optical disks, memory, programmable logic devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the computer implemented manufacturing process management system of Dietrich the use of memory and multiple processors to execute the computer instructions as taught by Wessela because doing so is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 26, Dietrich teaches:
A computer-program product (See Dietrich Abstract - A method for constrained material requirements planning, optimal resource allocation, and production planning provides for an optimization of a manufacturing process by designating the amounts of various manufactured products to be produced, … are presented as a set of linear mathematical relationships in matrix form to be inserted in a computer which determines the optimum number of each end product in accordance with an LP optimization algorithm), …:
obtaining data on a plurality of materials for making one or more products (See Dietrich Fig. 10: inputs 1-6 - Demand Data; Inventory Data; Bill of Material Data; Bill of Resource Data; Resource Availability Data; Cost & Revenue Data);
identifying a first group of one or more materials from the plurality of materials, a respective material in the first group is a replaceable material with respect to at least one of the one or more product (See Dietrich Col. 25 lines 6-24 - Often a product can be built using a part or resource other than the one specified on its BOM or BOR. For example, fast memory modules can be substituted for slow memory modules, but slow modules cannot usually be substituted for fast ones. If substitute part and substitute resource information is given, the resource allocation tool can be used to determine the optimal use of primary and substitution resources. Additional inputs: for each BOM entry, substitute information consisting of the substitute part, usage quantity, effectivity dates, and cost or priority information; For each BOR entry, substitute information consisting of the substitute resource, usage quantity, effectivity dates, and cost or priority information);
calculating a maximum consumption of the respective material in the first group in a period using a linear programming model with respect to the at least one of the one or more product (See Dietrich Col. 1 lines 40-45 - One method of representing such allocation decision problems is known as a linear programming model. Such a model consists of a number of linear relationships, set forth in matrix format, and representing quantitatively the relationships among allocations, constraints and results of an industrial or other technological process, Col. 24 lines 53-57 - If desirable, the formulation can be augmented to include minimum and maximum production quantities in each period, maximum backlog per demand and period, and minimum and maximum stock quantities for each p/n in each period and Col. 31 lines 58-61 - Bill of materials: Can include alternate bill-of-materials for a part. Can include substitution parts for a product component pair. Includes effectivity dates, usage rate, fallout, usage offset);
comparing the maximum consumption of the respective material in the first group in the period with an available inventory amount of the respective material in the first group (See Dietrich Col. 17 lines 21-27 - Notice that in the single period model the resource and material availability constraints were inequalities. In the multi-period model, it is necessary to track the carry-over of inventory from one period to the next. Inventory carried from one period to the next is exactly equal to the amount of material that was available at the beginning of the period, minus what is used during the period); and
determining whether the respective material in the first group is overstocked in the period (See Dietrich Col. 7 lines 35-40 - In the event that the restaurant has a cheese sandwich left over from a previous production run, which sandwich is to be used to meet the present customer demand, then the total amount of raw materials required for the present production run can be reduced by the amount in the left-over cheese sandwich).
While Dietrich teaches a system for managing a manufacturing process based on linear program optimization algorithm that is inserted into a computer, (Dietrich Abstract), Dietrich does not explicitly teach that said computer comprises a non-transitory tangible computer-readable medium having computer-readable instructions thereon, the computer-readable instructions being executable by a processor to cause the processor to perform. This is taught by Wessela (See ¶ [0070] – The computer programs (also referred to as programs, software, software applications, “apps”, or code) may include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, apparatus, cloud storage, internet of things, and/or device (e.g., magnetic discs, optical disks, memory, programmable logic devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the computer implemented manufacturing process management system of Dietrich the use of memory and multiple processors to execute the computer instructions as taught by Wessela because doing so is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Allowable Subject Matter
Claim 2 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
While Dietrich teaches using a linear programming model to determine material consumption in a product manufacturing process as noted above regarding claim 1, Dietrich does not teach that the objective function of said linear programming model is expressed as:
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This objective function expression has not been found in prior art.
Claim 3 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
While Dietrich teaches using a linear programming model to determine material consumption in a product manufacturing process as noted above regarding claim 2, Dietrich does not teach that a constraint of the objective function of said linear programming model is expressed as:
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This expression of a constraint for the objective function has not been found in prior art.
Claim 4 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
While Dietrich teaches using a linear programming model to determine material consumption in a product manufacturing process as noted above regarding claim 2, Dietrich does not teach that a constraint of the objective function of said linear programming model is expressed as:
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This expression of a constraint for the objective function has not been found in prior art.
Claim 10 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
While Dietrich teaches comparing a respective theoretical consumption of the respective material in the second group in the period with a respective inventory amount of the respective material in the second group as noted above regarding claim 5, Dietrich does not explicitly teach that “the respective theoretical consumption of the respective material in the second group in the period is equal to a sum of values of one or more demands in the period for one or more products requiring the respective material in the second group as a non-replaceable material respectively multiplied by respective unit consumptions of the respective material in the second group with respect to the one or more products”, as required by claim 10.
These features have not been found in prior art.
Conclusion
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/MATTHEW S WERONSKI/Examiner, Art Unit 3627
/MICHAEL JARED WALKER/Primary Examiner, Art Unit 3627
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