DETAILED ACTION
Notice to Applicant
The following is a NON-FINAL Office action upon examination of application number 19/215,999 filed on 05/22/2025. In response to the Election/Restriction requirement of 06/15/2026, Applicant, on 06/29/2025, elected Group II, claims 2, 4, 6-7, 9, and 11, for examination. Claims 1-11 are pending in this application, of which claims 2, 4, 6-7, 9, and 11 have been examined on the merits discussed below.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Application 19/215,999 filed 05/22/2025 is a Continuation of PCT/JP2023/000767, filed 01/13/2023.
Information Disclosure Statement
The information disclosure statements (IDS) filed on 05/22/2025 and 09/04/2025 have been acknowledged. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Election/Restrictions
In response to the restriction requirement, dated 06/15/2026, Applicant elected Group II, claims 2, 4, 6-7, 9, and 11. Claims 1, 3, 5, 8, and 10 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim.
The Applicant's response does not point out if the election is with or without traverse. Thus, the required provisional election (see MPEP § 818.01(b)) becomes an election without traverse if accompanied by an incomplete traversal of the requirement for restriction.
Claim Rejections - 35 USC § 112
7. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
8. Claims 2, 4, 6-7, 9, and 11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
9. Claim 2 recites “A demand forecasting apparatus that forecasts a demand that occurs in each unit period comprising: processing circuitry: to assume that an inventory increases due to an order being placed in accordance with an order condition and an order quantity indicated in order model information and the inventory decreases in accordance with a transition of a past inventory quantity indicated in past inventory information at a supply destination of a forecasting subject item, to estimate a future inventory quantity at the supply destination, and for each unit period during a forecasting period starting from the unit period next to the unit period to which a processing execution time point belongs in the order from the oldest to the newest…” The phrases “each unit period” and “the unit period” lack antecedent basis, and therefore render the claim indefinite. Independent claims 9 and 11 recite similar limitations as those recited in claim 2 and therefore are found to be indefinite for the same reasons as claim 2. Appropriate correction is required.
10. Claims 4 and 6-7 depend from claim 2 and fail to cure the §112(b) deficiency noted above, and are therefore rendered indefinite based on dependency.
Claim Rejections - 35 USC § 101
11. 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.
12. Claims 2, 4, 6-7, 9, and 11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
13. Claims 2, 4, 6-7, 9, and 11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The eligibility analysis in support of these findings is provided below, in accordance with MPEP 2106.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted that the apparatus (claims 2, 4, 6-7), method (claim 9), non-transitory computer readable medium (claim 11) is directed to at least one potentially eligible category of subject matter (i.e., machine, process, and article of manufacture). Thus, Step 1 of the Subject Matter Eligibility test for claims 2, 4, 6-7, 9, and 11 is satisfied.
With respect to Step 2A Prong One, it is next noted that the claims recite an abstract idea that falls into the “Certain Methods of Organizing Human Activity” abstract idea set forth in MPEP 2106 because the claims recite steps for managing supply chain relationships, which encompasses activity for managing organizing and coordinating commercial operations, and also falls into the “Mathematical Concepts” such as mathematical relationships, formulas and calculations. With respect to independent claim 2, the limitations reciting the abstract idea are indicated in bold below: processing circuitry: to assume that an inventory increases due to an order being placed in accordance with an order condition and an order quantity indicated in order model information and the inventory decreases in accordance with a transition of a past inventory quantity indicated in past inventory information at a supply destination of a forecasting subject item, to estimate a future inventory quantity at the supply destination, and for each unit period during a forecasting period starting from the unit period next to the unit period to which a processing execution time point belongs in the order from the oldest to the newest, to estimate an inventory quantity in each unit period during the forecasting period by calculating an inventory quantity in a subject unit period by adding an inventory quantity that increases in the subject unit period and subtracting an inventory quantity that decreases in the subject unit period, to/from an inventory quantity in the unit period before the subject unit period; to forecast that a demand for the order quantity indicated in the order model information occurs to a supplier at a time point when the order condition indicated in the order model information is satisfied in the estimated future inventory quantity; to refer to logistics information indicating a transition that occurs in a logistics process for the forecasting subject item at the supply destination, and to estimate an inventory quantity of the supply destination for each unit period of a past reference period up to the unit period to which the processing execution time point belongs; and to estimate a future inventory quantity using the estimated inventory quantity as a past inventory quantity indicated in the past inventory information. These steps are organizing human activity by managing commercial inventory and supply chain relationship’s by determining when a supplier should receive and order and how much should be ordered based on inventory levels,. The claims falls under the mathematical concept category because it recites steps directed to calculating and forecasting inventory and supplier demand based on historical inventory, logistics information and ordering condition. Considered together, these steps set forth an abstract idea of forming a team, which falls under the under the “Certain methods of organizing human activity” and “Mathematical Concepts” abstract idea groupings set forth in MPEP 2106.
Because the above-noted limitations recite steps falling within the “Mathematical Concepts” abstract idea grouping and the “Mental Processes” abstract idea grouping, they have been determined to recite at least one abstract idea when evaluated under Step 2A Prong One of the eligibility inquiry. Independent claims 9 and 11 recite similar limitations as those recited in claim 2 and therefore are found to recite the same abstract idea(s) as claim 2.
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. The additional elements recited are: processing circuitry (claim 2), a non-transitory computer readable medium, a demand forecasting program, a computer, and a demand forecasting apparatus (claim 11). These additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or computer-executable instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment. See MPEP 2106.05(f) and 2106.05(h). In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. With respect to independent claim 9, it is noted that the claim does not recite additional elements (i.e., claim 9 is a method that recites several disembodied steps).
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements recited are: processing circuitry (claim 2), a non-transitory computer readable medium, a demand forecasting program, a computer, and a demand forecasting apparatus (claim 11). These elements have been considered individually and in combination, but fail to add significantly more to the claims because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment and does not amount to significantly more than the abstract idea itself. Notably, Applicant’s Specification acknowledges that the claimed invention relies on nothing more than a general purpose computer executing instructions to implement the invention (Specification, paragraphs 0042, 0046, 0047). Accordingly, the generic computer involvement in performing the claim steps merely serves to generally link the use of the judicial exception to a particular technological environment, which does not add significantly more to the claim. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976.).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself. As set forth above, with respect to independent claim 9, it is noted that the claim does not recite additional elements (i.e., claim 9 is a method that recites several disembodied steps).
Dependent claims 4, 6-7, 9, and 11 recite the same abstract idea as recited in the independent claims, and when evaluated under Step 2A Prong One are found to recite details that narrow the same abstracts idea(s) recited in the independent claims, i.e., activities falling within the Certain methods of organizing human activity abstract idea grouping as described in MPEP 2106, along with, at most, additional elements that fail to integrate the abstract idea into a practical application or add significantly more. In particular, dependent claims 4 and 6-7 recite steps for “wherein when the order condition is satisfied in a unit period before only a procurement lead time of the subject unit period, treats the order quantity as an inventory quantity that increases in the subject unit period,” “sets an initial value for an inventory quantity in the unit period before the reference period of the unit period to which the processing execution time point belongs, and for unit periods in the order from the unit period next to the unit period before the reference period to the unit period to which the processing execution time point belongs, estimates an inventory quantity in the unit period to which the processing execution time point belongs by calculating an inventory quantity in the subject unit period by adding an inventory quantity that increases in the subject unit period indicated in the logistics information and subtracting an inventory quantity that decreases in the subject unit period indicated in the logistics information, to/from an inventory quantity in the unit period before the subject unit period,” “wherein the logistics information indicates a transition that occurs in a logistics process for a usage product that is a product to be produced using the forecasting subject item as a component, and refers to component configuration information indicating the number of forecasting subject items to be used in the usage product, and specifies an inventory quantity that decreases in the subject unit period by taking into account a usage quantity of the forecasting subject item calculated from a production number of the usage products,” however these limitations are part of the same abstract idea as addressed in the independent claims that falls within the “Certain Methods of Organizing Human Activity” and “Mathematical Concepts” abstract idea groupings. Accordingly, these steps are part of the same abstract idea(s) set forth in the independent claims. Dependent claims recite additional elements of: the processing circuitry (claims 4, 7). However, when evaluated under Step 2A Prong Two and Step 2B, these additional elements do not amount to a practical application or significantly more since they merely require generic computing devices (or computer-implemented instructions/code) which as noted in the discussion of the independent claims above is not enough to render the claims as eligible.
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself.
For more information, see MPEP 2106.
Claim Rejections - 35 USC § 103
14. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
15. 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 of this title, 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.
16. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
17. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
18. Claims 2, 6-7, 9, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Maurer et al., Patent No.: US 9,805,402 B1, [hereinafter Maurer], in view of Landvater et al., Patent No.: US 7,552,066 B1, [hereinafter Landvater], in further view of Huang et al., Patent No.: US 6,151,582, [hereinafter Huang].
As per Claim 2, Maurer teaches a demand forecasting apparatus that forecasts a demand that occurs in each unit period (col. 6, lines 20-30; col. 16, lines 50-67) comprising:
processing circuitry (col. 6, lines 20-30, discussing at least one or more processing units (or processor devices(s)) and one memory. The processor device(s) may be implemented as appropriate in hardware, or as computer-executable instructions, software or firmware implemented in hardware);
to assume that an inventory increases due to an order being placed in accordance with an order quantity indicated in order model information and the inventory decreases in accordance with a transition of a past inventory quantity indicated in past inventory information at a supply destination of a forecasting subject item, to estimate a future inventory quantity at the supply destination, and for each unit period during a forecasting period starting from the unit period next to the unit period to which a processing execution time point belongs in the order from the oldest to the newest, to estimate an inventory quantity in each unit period during the forecasting period by calculating an inventory quantity in a subject unit period by adding an inventory quantity that increases in the subject unit period and subtracting an inventory quantity that decreases in the subject unit period, to/from an inventory quantity in the unit period before the subject unit period (col. 2, lines 30-54, discussing that the inventory management system may implement a number of tools including, for example, an adaptive capacity control tool and a multi-period ordering model tool. The adaptive capacity control tool may be configured to generate, based on a set of constraints associated with inventory capacities, a set of opportunity costs over a time horizon (e.g., a plurality of weeks or months). An opportunity cost can be generated for a category of items by, for example, simulating consumptions of a capacity, such as an inventory capacity, over the time horizon to determine an optimized use of the capacity. This opportunity cost may represent a value, such as a cost, associated with storing that category of items during the time horizon. The multi-mode ordering model may be configured to use the opportunity cost and other parameters to generate various purchase plans. A purchase plan may include a decision to acquire a number of units of a particular item from a category of items within an immediate short time period (e.g., next week) and an inventory plan for acquiring additional units during the remaining portion of the time horizon; col. 3, lines 7-17, discussing that the multi-period ordering model tool may generate a number of units for the first week. This number of units may not only satisfy the potential consumer demand in that first week, but may also account for the potential capacity constraints in the fifteenth week. As such, the generated purchase plan may provide buy-in early decisions, and/or buy-in late decisions, in each time period (e.g., week) of the time horizon given the capacity constraints of the time periods; col. 12, lines 30-67, discussing an existing outstanding order quantity for item i that will arrive at the end of time period t; col. 19, lines 32-50, discussing that the ordering model tool may use various variables, functions, and algorithms in generating the ordering decision. In particular, the ordering model tool can model the multi-period problem as a single-item and, optionally a single-location, inventory system that can implement a periodic review base-stock policy. At the beginning of each time period ,a quantity can be ordered…; col. 20, lines 24-44, discussing that the major difference between constant and stochastic lead times can be that, each order may not be associated with a future receipt in a one-to-one manner if lead times were stochastic, because in a particular period, orders from multiple earlier periods can be received. This may complicate the notation significantly, but may not alter the essence of the model and the solution method. For brevity, consider the simpler case of constant lead times. The extension to stochastic lead times is further described below. Let
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so that on-hand inventory level can be denoted as
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and backorders as
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. Inventory position wt can be equal to the sum of inventory level xt and the orders qi−L=zi that may be received in the coming periods (e.g., i=t+1, . . . , t+L). An order of qt=zt+L=yt−wt, units can be placed if the order-up-to level yt is higher than the inventory position wt. Beginning inventory level in the next period is the current inventory level xt minus the period's sales (which can be demand dt less the lost sales (1−α)(dt−(xt)+)+), if any; and the receipt zt+1, which can be due at period t+1); col. 24, lines 37-50, discussing calculating inventory flow: forward);
to forecast that a demand for the order quantity indicated in the order model information occurs to a supplier at a time point (col. 2, lines 55-67 & col. 3, lines 1-17, discussing that considering a consumer demand peak, such as one observed during a holiday season. Demand may exceed inventoried items. A service provider may react by attempting to increase the inventory in an ad-hoc manner. However, sellers may not have the capacity to timely satisfy the surge in demand. By implementing the adaptive capacity control tool and the multi-period ordering model tool, the service provider may consider constraints over a long time horizon up to and including the peak, such as a fifteen week time period. The constraints may be associated with the capacity of the service to receive and store items in an inventory. The constraints may also include seller capacities to provide the items. The adaptive capacity control tool may allow the service provider to perceive a value of stocking a certain category of items across the fifteen weeks given the various capacity constraints. This value can be used by the multi-period ordering tool to determine how many units of a particular item should be purchased and stored over time. For example, the multi-period ordering model tool may generate a number of units for the first week. This number of units may not only satisfy the potential consumer demand in that first week, but may also account for the potential capacity constraints in the fifteenth week. As such, the generated purchase plan may provide buy-in early decisions, and/or buy-in late decisions, in each time period of the time horizon given the capacity constraints of the time periods. Accordingly, the plan can help manage the capacity constraints over the time horizon and mitigate potential risks; col. 8, lines 3-23, discussing that the adaptive capacity control tool can simulate and/or interface with the ordering model tool to simulate supply and demand; col. 12, lines 4-12, discussing that the simulation can simulate multiple scenarios of supply, arrivals, demand, and/or expected purchases from suppliers over the time horizon using different objective functions. An output of the simulation can include a realization of demand and an estimate of how much inventory may be carried in every time period of the time horizon; col. 17, lines 63-67 & col. 18, lines 1-8, discussing that for an item i, in order to derive an ordering constraint curve, demand forecast data per time period (e.g., weekly) until the end of the peak may be needed. For example, a mean demand forecast can be collected. Similar to the treatment to the realized demand of the previous time horizon, an average demand forecast for the current time horizon may be taken; col. 19, lines 16-50, discussing that by considering constraints across a time horizon and the different parameters, the ordering model tool may generate the ordering decision for what to purchase in a particular time period given constraints across the entire time horizon. In other words, the ordering model tool can take into account future inventory and/or supplier constraints and associated values, economic or otherwise, to determine what to purchase immediately. This can enable early and late purchases such that constraints can be mitigated throughout the entire time horizon. In addition, by considering constraints at an item category level, the ordering model tool may bring cross-item awareness into ordering decision. In other words, a decision to purchase a certain number of units of an item can account for parameters associated with another purchase decision related to another item of the same item category; col 26, lines 55-62, discussing that the optimal value function and the objective function should consider more previous orders than the constant lead time case. Since inventory position can be the threshold for ordering [i.e., the order condition], the objective and value functions can be altered to consider all previous orders; col. 11, lines 42-60); and
to estimate a future inventory quantity using the estimated inventory quantity as a past inventory quantity indicated in the past inventory information (col. 16, lines 36-49, discussing that because the ordering model tool can output future-looking ordering decisions or plans, the supplier constraint model can be configured to re-allocate orders close to a peak time period (e.g., a busy holiday season) to earlier buying days. This may prevent a service provider from facing the hazard of not being able to acquire enough items immediately before the peak; col. 16, lines 50-67 & col. 17, lines 1-6, discussing that the supplier constraint model can derive an estimation of this quantity based on the service provider's ordering/receiving and demand profile from previous time horizon(s) (e.g., the previous year). At an item category, the supplier constraint model can calculate the ratio between receiving quantity per time period and peak demand of the previous time horizon. The supplier constraint model can apply the same ratio to the peak demand forecast of the current time horizon at individual item levels, thus obtaining estimated ordering/receiving quantity for each time period. This estimated quantity can be inputted to the ordering model tool as a constraint on the ordering quantity per time period for all time periods until the demand peak demand time period; col. 19, lines 16-50, discussing that by considering constraints across a time horizon and the different parameters, the ordering model tool may generate the ordering decision for what to purchase in a particular time period given constraints across the entire time horizon. In other words, the ordering model tool can take into account future inventory and/or supplier constraints and associated values, economic or otherwise, to determine what to purchase immediately…; col. 31, lines 27-41, discussing that an adaptive capacity control tool may access a constraint associated with a capacity for a category of items. The capacity may include an inventory capacity such as receipt and/or storage capacities. In an embodiment, the capacity may additionally or alternatively include a supplier capacity. The constraint may be associated with an item category over a time horizon including a plurality of time periods. Various techniques may be implemented to access the constraint. For example, the adaptive capacity control tool may provide or interact with an interface configured to receive user input defining the constraint. In another example, the adaptive capacity control tool may derive the constraint based on analyzing historical data about past performances; col. 26, lines 33-54).
Maurer does not explicitly teach an order being placed in accordance with an order condition; to forecast that a demand for the order quantity indicated in the order model information occurs to a supplier at a time point when the order condition indicated in the order model information is satisfied in the estimated future inventory quantity; and to refer to logistics information indicating a transition that occurs in a logistics process for the forecasting subject item at the supply destination, and to estimate an inventory quantity of the supply destination for each unit period of a past reference period up to the unit period to which the processing execution time point belongs. Landvater in the analogous art of forecasting systems teaches:
an order being placed in accordance with an order condition (col. 1, lines 20-32, discussing that if the on-hand balance is below a preset number (the reorder point), an order is created to replenish inventory. If the on-hand balance is above the reorder point, no further action is taken);
to forecast that a demand for the order quantity indicated in the order model information occurs to a supplier at a time point when the order condition indicated in the order model information is satisfied in the estimated future inventory quantity (col. 2, lines 21-37, discussing subtracting the forecast from the projected on-hand balance to give the new projected on-hand balance. If the new projected on-hand balance is below the safety stock, a planned replenishment shipment is either created, or an existing planned replenishment shipment is automatically rescheduled to the need date. In this context, rescheduling means changing the receipt date from whatever value currently exists to the date of the forecast which caused the projected on-hand balance to drop below the safety stock. In addition, rescheduling means changing the ship date of the planned replenishment shipment to the receipt date less the lead time; col. 10, lines 36-55, discussing reducing the beginning on-hand balance by the forecast quantity. Then, a determination is made if the resulting projected on-hand balance is less than the safety stock. If not, this process is repeated. If the projected on-hand balance is determined to be less than the safety stock, then a planned replenishment shipment is calculated. There, the quantity of the planned shipment is calculated based on the preferred shipping quantity, desired number of days of supply, dates when the store can receive deliveries, and other ordering parameters…).
Maurer is directed towards a system and method for demand forecasting and inventory management. Landvater describes a method and system for forecasting. Therefore, they are deemed to be analogous as they both are directed towards forecasting systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Maurer with Landvater because the references are analogous art because they are both directed to solutions for forecasting and inventory management, which falls within applicant’s field of endeavor (demand forecasting apparatus and method), and because modifying Maurer to include Landvater’s features for including an order being placed in accordance with an order condition, and forecasting that a demand for the order quantity indicated in the order model information occurs to a supplier at a time point when the order condition indicated in the order model information is satisfied in the estimated future inventory quantity, in the manner claimed, would serve the motivation of providing a more accurate projection of demand (Landvater at col. 6, lines 63-65); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely 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.
The Maurer-Landvater combination does not explicitly teach to refer to logistics information indicating a transition that occurs in a logistics process for the forecasting subject item at the supply destination, and to estimate an inventory quantity of the supply destination for each unit period of a past reference period up to the unit period to which the processing execution time point belongs. However, Huang in the analogous art of supply chain management teaches this concept. Huang teaches:
to refer to logistics information indicating a transition that occurs in a logistics process for the forecasting subject item at the supply destination, and to estimate an inventory quantity of the supply destination for each unit period of a past reference period up to the unit period to which the processing execution time point belongs (col. 42, lines 39-44, discussing inventory status verification. To verify the inventory status, the POS (point-of-sales) data can be used in combination with the shipment data, and the inventory balance equation to compute the deduced inventory status. Then, the deduced inventory status can be compared to the reported inventory status; col. 36, lines 38-49, discussing that based on the forecasts of the future sell-through, user defined VMR (Vendor Managed Replenishment) operating parameters, and other related indicators (e.g., last reported customer DC inventory level), the system will generate a suggested replenishment quantity for a future replenishment date; col. 75, lines 59-65, discussing system dynamics: (expected) beginning DC echelon inventory=(expected) beginning inventory of last period+delivery quantity to the DC during the last period-expected demand in the last period...; col. 122, lines 51-67 & col. 123, lines 1-44, discussing database specification for the supply chain and data tables for the supply chain including Point of Sale data for the customer-products identified in the header, Time Period (beginning of the time period), Shipments, DCInventory Status (on hand inventory at the ship to location), StoreInventory Status (aggregate on hand inventory of stores served by the customer ship to location).
Examiner notes that Huang, in addition to Landvater as cited above, also teaches an order being placed in accordance with an order condition (col. 98, lines 35-38, discussing that inventory is depleted by demand and whenever it reaches the replenishment point an order is placed to a supplier).
The Maurer-Landvater combination describes features related to demand forecasting and inventory management. Huang describes a method and system for supply chain management. Therefore, they are deemed to be analogous as they both are directed towards forecasting systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Maurer-Landvater combination with Huang because the references are analogous art because they are both directed to solutions for forecasting and inventory management, which falls within applicant’s field of endeavor (demand forecasting apparatus and method), and because modifying the Maurer-Landvater combination to include Huang’s features for including to refer to logistics information indicating a transition that occurs in a logistics process for the forecasting subject item at the supply destination, and to estimate an inventory quantity of the supply destination for each unit period of a past reference period up to the unit period to which the processing execution time point belongs, in the manner claimed, would serve the motivation of enhancing and encouraging supply-chain-wide thinking and decision making in the enterprise (Huang at col. 12, lines 47-50); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely 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.
As per Claim 6, the Maurer-Landvater-Huang combination teaches the demand forecasting apparatus according to claim 2. Maurer further teaches wherein the processing circuitry sets an initial value for an inventory quantity in the unit period before the reference period of the unit period to which the processing execution time point belongs (col. 19, lines 38-42, discussing that at the beginning of each time period, a quantity can be ordered, where the quantity can be equal to the difference between an order-up-to level (e.g., TIP or base-stock) and the inventory position, if any, from suppliers; col. 20, lines 16-17, discussing the inventory position at the beginning of period t, before the order for period t is input; col. 21, lines 14-16, discussing the beginning inventory level; col. 6, lines 20-30), and
for unit periods in the order from the unit period next to the unit period before the reference period to the unit period to which the processing execution time point belongs, estimates an inventory quantity in the unit period to which the processing execution time point belongs by calculating an inventory quantity in the subject unit period by adding an inventory quantity that increases in the subject unit period indicated in the information and subtracting an inventory quantity that decreases in the subject unit period indicated in the information, to/from an inventory quantity in the unit period before the subject unit period (col. 2, lines 30-54, discussing that the inventory management system may implement a number of tools including, for example, an adaptive capacity control tool and a multi-period ordering model tool. The adaptive capacity control tool may be configured to generate, based on a set of constraints associated with inventory capacities, a set of opportunity costs over a time horizon (e.g., a plurality of weeks or months). An opportunity cost can be generated for a category of items by, for example, simulating consumptions of a capacity, such as an inventory capacity, over the time horizon to determine an optimized use of the capacity. This opportunity cost may represent a value, such as a cost, associated with storing that category of items during the time horizon. The multi-mode ordering model may be configured to use the opportunity cost and other parameters to generate various purchase plans. A purchase plan may include a decision to acquire a number of units of a particular item from a category of items within an immediate short time period (e.g., next week) and an inventory plan for acquiring additional units during the remaining portion of the time horizon; col. 3, lines 7-17, discussing that the multi-period ordering model tool may generate a number of units for the first week. This number of units may not only satisfy the potential consumer demand in that first week, but may also account for the potential capacity constraints in the fifteenth week. As such, the generated purchase plan may provide buy-in early decisions, and/or buy-in late decisions, in each time period (e.g., week) of the time horizon given the capacity constraints of the time periods; col. 12, lines 30-67, discussing an existing outstanding order quantity for item i that will arrive at the end of time period t; col. 19, lines 32-50, discussing that the ordering model tool may use various variables, functions, and algorithms in generating the ordering decision. In particular, the ordering model tool can model the multi-period problem as a single-item and, optionally a single-location, inventory system that can implement a periodic review base-stock policy. At the beginning of each time period ,a quantity can be ordered…; col. 20, lines 24-44, discussing that the major difference between constant and stochastic lead times can be that, each order may not be associated with a future receipt in a one-to-one manner if lead times were stochastic, because in a particular period, orders from multiple earlier periods can be received. This may complicate the notation significantly, but may not alter the essence of the model and the solution method. For brevity, consider the simpler case of constant lead times. The extension to stochastic lead times is further described below. Let
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so that on-hand inventory level can be denoted as
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and backorders as
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. Inventory position wt can be equal to the sum of inventory level xt and the orders qi−L=zi that may be received in the coming periods (e.g., i=t+1, . . . , t+L). An order of qt=zt+L=yt−wt, units can be placed if the order-up-to level yt is higher than the inventory position wt. Beginning inventory level in the next period is the current inventory level xt minus the period's sales (which can be demand dt less the lost sales (1−α)(dt−(xt)+)+), if any; and the receipt zt+1, which can be due at period t+1); col. 24, lines 37-50, discussing calculating inventory flow: forward).
The Maurer-Landvater combination does not explicitly teach the logistics information. However, Huang in the analogous art of supply chain management teaches this concept. Huang teaches:
the logistics information (col. 13, lines 9-44, discussing that PSI Planning is a process to determine a set of feasible sales, production and inventory requirements for medium to long-term capacity and resource planning for the logistics operations. At the beginning of each fiscal year, an initial PSI plan can be developed based on the long-term top-down sales forecast and budget plans. The planning process then becomes a continuous effort to update the existing PSI plan to accommodate the changes in the requirements before and after a series of monthly PSI planning meetings whose participants include decision makers representing all key functional areas at the enterprise. The meetings integrate the inputs from various sources, resolve possible conflicts, and balance the concerns of different functions in order to reconcile, develop and approve a new set of feasible sales, production and inventory requirements. The process represents a focal point for the entire logistics planning process, and interacts and coordinates with all major decision making processes; col. 14, lines 5-20, discussing developing a strategic analysis tool to determine mutually beneficial VMR contracts based on financial and logistics factors; col. 42, lines 39-44, discussing inventory status verification. To verify the inventory status, the POS (point-of-sales) data can be used in combination with the shipment data, and the inventory balance equation to compute the deduced inventory status. Then, the deduced inventory status can be compared to the reported inventory status; col. 36, lines 38-49, discussing that based on the forecasts of the future sell-through, user defined VMR (Vendor Managed Replenishment) operating parameters, and other related indicators (e.g., last reported customer DC inventory level), the system will generate a suggested replenishment quantity for a future replenishment date; col. 75, lines 59-65, discussing system dynamics: (expected) beginning DC echelon inventory=(expected) beginning inventory of last period+delivery quantity to the DC during the last period-expected demand in the last period...; col. 122, lines 51-67 & col. 123, lines 1-44, discussing database specification for the supply chain and data tables for the supply chain including Point of Sale data for the customer-products identified in the header, Time Period (beginning of the time period), Shipments, DCInventory Status (on hand inventory at the ship to location), StoreInventory Status (aggregate on hand inventory of stores served by the customer ship to location).
The Maurer-Landvater combination describes features related to demand forecasting and inventory management. Huang describes a method and system for supply chain management. Therefore, they are deemed to be analogous as they both are directed towards forecasting systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Maurer-Landvater combination with Huang because the references are analogous art because they are both directed to solutions for forecasting and inventory management, which falls within applicant’s field of endeavor (demand forecasting apparatus and method), and because modifying the Maurer-Landvater combination to include Huang’s feature for including the logistics information, in the manner claimed, would serve the motivation of enhancing and encouraging supply-chain-wide thinking and decision making in the enterprise (Huang at col. 12, lines 47-50); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely 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.
As per Claim 7, the Maurer-Landvater-Huang combination teaches the demand forecasting apparatus according to claim 6. Although not explicitly taught by the Maurer-Landvater combination, Huang in the analogous art of supply chain management teaches wherein the logistics information indicates a transition that occurs in a logistics process for a usage product that is a product to be produced using the forecasting subject item as a component (col. 7, lines 36-56, discussing that a data space is a fundamental domain to characterize basic data elements associated with the supply chain management: demand, supply and inventory data. The data spaces tie the structural data to the process data. It has three principal dimensions: Product/Component; Time; and Node related structural element. As the node-related structural element can be a customer, an inventory location, or a production resource. The data in each data space can be at any resolution (in terms of level of aggregation) along the three dimensions and can be expressed as a quantity or value. Thus, each point in the data space characterizes the resolution of the product (or component), the time and the node-related structural element. For example, when describing the aggregate production plan data, a product can be at the resolution of product, time at a resolution of week, and the node-related structural element (Production resource in this case) at a resolution of production resource group. On the other hand, in describing bottom-up forecasts, a product can be at the resolution of product, time at a resolution of month, and node related structural element at the resolution of customer; col. 12, lines 37-50, discussing that given the uncertainty in the medium-to long-term sales forecasts, determine whether or not the enterprise should expand, maintain or reduce its production capacity and/or stocks for the critical components; col. 13, lines 9-44, discussing that PSI (production, sales and inventory) Planning is a process to determine a set of feasible sales, production and inventory requirements for medium to long-term capacity and resource planning for the logistics operations. At the beginning of each fiscal year, an initial PSI plan can be developed based on the long-term top-down sales forecast and budget plans. The planning process then becomes a continuous effort to update the existing PSI plan to accommodate the changes in the requirements before and after a series of monthly PSI planning meetings whose participants include decision makers representing all key functional areas at the enterprise. The meetings integrate the inputs from various sources, resolve possible conflicts, and balance the concerns of different functions in order to reconcile, develop and approve a new set of feasible sales, production and inventory requirements. The process represents a focal point for the entire logistics planning process, and interacts and coordinates with all major decision making processes…Generate forecasts for new products and managing product transitions. Facilitate development of medium-term top-down and bottom-up sales forecasts for the enterprise. Facilitate development of production plans and the associated requirements plans for critical components. Evaluate the effects and understand the implications of specific changes in the sales or production plans; col. 23, lines 60-63, discussing choosing model for statistical forecast of future usage; col. 93, lines 43-67 & col. 94, lines 1-40), and
the processing circuitry refers to component configuration information indicating the number of forecasting subject items to be used in the usage product, and specifies an inventory quantity that decreases in the subject unit period by taking into account a usage quantity of the forecasting subject item calculated from a production number of the usage products (col. 1, lines 22-28, discussing that inventory control processes tend to determine when the inventory of an item is projected to be depleted and when to order goods to prevent such depletion; col. 12, lines 37-50, discussing that given the uncertainty in the medium-to long-term sales forecasts, determine whether or not the enterprise should expand, maintain or reduce its production capacity and/or stocks for the critical components; col. 13, lines 9-44, discussing that PSI (production, sales and inventory) Planning is a process to determine a set of feasible sales, production and inventory requirements for medium to long-term capacity and resource planning for the logistics operations. At the beginning of each fiscal year, an initial PSI plan can be developed based on the long-term top-down sales forecast and budget plans; col. 28, lines 18-23, discussing that the unavailability of production resources at certain periods requires the decrease in corresponding inventory levels; col. 5, lines 24-26).
The Maurer-Landvater combination describes features related to demand forecasting and inventory management. Huang describes a method and system for supply chain management. Therefore, they are deemed to be analogous as they both are directed towards forecasting systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Maurer-Landvater combination with Huang because the references are analogous art because they are both directed to solutions for forecasting and inventory management, which falls within applicant’s field of endeavor (demand forecasting apparatus and method), and because modifying the Maurer-Landvater combination to include Huang’s features for including wherein the logistics information indicates a transition that occurs in a logistics process for a usage product that is a product to be produced using the forecasting subject item as a component, and the processing circuitry refers to component configuration information indicating the number of forecasting subject items to be used in the usage product, and specifies an inventory quantity that decreases in the subject unit period by taking into account a usage quantity of the forecasting subject item calculated from a production number of the usage products, in the manner claimed, would serve the motivation of enhancing and encouraging supply-chain-wide thinking and decision making in the enterprise (Huang at col. 12, lines 47-50); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely 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.
Claim 9 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 2, as discussed above. Further, as per claim 9 the Maurer-Landvater-Huang combination teaches a demand forecasting method that forecasts a demand that occurs in each unit period (col. 40, lines 39-56 : “Non-transitory storage media and computer-readable media for containing code, or portions of code, can include any appropriate media known or used in the art, including storage media and communication media such as, but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information such as computer-readable instructions, data structures, program modules or other data, including RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other medium which can be used to store the desired information and which can be accessed by a system device. Based on the disclosure and teachings provided herein, a person of skilled in the art will appreciate other ways and/or methods to implement the various embodiments.”).
Claim 11 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 2, as discussed above. Further, as per claim 11 the Maurer-Landvater-Huang combination teaches a non-transitory computer readable medium storing a demand forecasting program that forecasts a demand that occurs in each unit period for causing a computer to function as a demand forecasting apparatus (col. 40, lines 39-56 : “Non-transitory storage media and computer-readable media for containing code, or portions of code, can include any appropriate media known or used in the art, including storage media and communication media such as, but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information such as computer-readable instructions, data structures, program modules or other data, including RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other medium which can be used to store the desired information and which can be accessed by a system device. Based on the disclosure and teachings provided herein, a person of skilled in the art will appreciate other ways and/or methods to implement the various embodiments.”).
19. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Maurer in view of Landvater, in view of Huang, in further view of Tsujibe., Patent No.: WO 2018/0618083 A1, [hereinafter Tsujibe].
As per Claim 4, the Maurer-Landvater-Huang combination teaches the demand forecasting apparatus according to claim 2, but it does not explicitly teach wherein when the order condition is satisfied in a unit period before only a procurement lead time of the subject unit period, the processing circuitry treats the order quantity as an inventory quantity that increases in the subject unit period. However, Tsujibe in the analogous art of inventory management systems teaches this concept. Tsujibe teaches:
wherein when the order condition is satisfied in a unit period before only a procurement lead time of the subject unit period, the processing circuitry treats the order quantity as an inventory quantity that increases in the subject unit period (page 10, paragraph 8, discussing that
the shortage 1represents the necessary number of procurement (the number of shortages of inventory) calculated by subtracting the consumption from the sum of the stock and the warehousing of each date. The order represents the order quantity to the supplier considering the purchase unit with respect to the value of the shortage; page 11, paragraph 3, discussing that since the procurement lead time is “21” days (3 weeks), the inventory transition simulation unit 117 needs to order the quantity required by “3/14” three weeks ahead at “2/22”. The required number is “430” obtained by adding “50” which is the safety stock quantity to “380” (100 + 30 + 200 + 50) from the consumption 1313. Since “110” in stock 1311 and “80”, “90”, and “100” in warehousing have already been arranged, the total “380” is the arranged quantity; page 11, paragraph 4, discussing that the inventory transition simulation unit calculates the number of shortages by subtracting the arranged number from the necessary number. In this example, “50” (430-380) is the shortage number. The inventory transition simulation unit sets “50” to the shortage. The order is determined by rounding up the shortage so as to be a multiple of the purchase unit which is one of the ordering parameters. In this example, since the purchase unit is “50”, “50” is set in the order . Further, since this order is received on 3/14, “50” is set in the “3/14” column of the receipt; page 11, paragraph 5, discussing that in addition, by subtracting the consumption from the sum of the stock and the receipt, the stock quantity on the next date can be obtained. In this example, the stock quantity of “2/29” is “90” (110 + 80-100). The inventory transition simulation unit sets “90” to the inventory having a date of “2/29”; page 11, paragraph 7, discussing that the inventory transition simulation unit repeats this process until the date of the inventory transition simulation information reaches the final date included in the consumption plan information or the assumed scenario information; page 3, paragraphs 2, 4).
The Maurer-Landvater-Huang combination describes features related to demand forecasting and inventory management. Tsujibe describes a system and method for inventory transition simulation. Therefore, they are deemed to be analogous as they both are directed towards forecasting systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Maurer-Landvater-Huang combination with Tsujibe because the references are analogous art because they are both directed to solutions for forecasting and inventory management, which falls within applicant’s field of endeavor (demand forecasting apparatus and method), and because modifying the Maurer-Landvater-Huang combination to include Tsujibe’s features for including wherein when the order condition is satisfied in a unit period before only a procurement lead time of the subject unit period, the processing circuitry treats the order quantity as an inventory quantity that increases in the subject unit period, in the manner claimed, would serve the motivation of recommending a plan change (Tsujibe); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Deshpande et al., Pub. No.: US 2017/0330123 A1 – describes a system and method for setting inventory thresholds for offering and fulfillment across retail supply networks.
Chickering et al., Pub. No.: US 2011/0258045 A1 – describes techniques for inventory management.
Kourentzes, Nikolaos, Juan R. Trapero, and Devon K. Barrow. "Optimising forecasting models for inventory planning." International Journal of Production Economics 225 (2020): 107597 – describes a way to combine the competing multiple inventory objectives, i.e. meeting demand, while eliminating excessive stock, and use the resulting cost function to identify inventory optimal parameters for forecasting models.
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/Darlene Garcia-Guerra/
Primary Examiner, Art Unit 3625
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