The entirety of each of the above applications is incorporated by reference herein as part of the present disclosure.
The present application is also related to:
1. Field of the Invention
The present invention relates generally to vending machines. More particularly, the present invention relates to a method and apparatus for dynamically managing inventory pricing of a vending machine.
2. Description of the Related Art
Vending machines are well known and have existed since the late 1880s. The first vending machines were rudimentary devices primarily designed to dispense cigarettes and postcards. Modern vending machines are employed to store and dispense a vast array of merchandise in response to a customer request and appropriate payment. Such merchandise includes drinks, candy, frozen deserts, snacks, video tapes and children's toys.
Many entrepreneurs are attracted to the basic concept of selling products using a vending machine. Vending machines are generally considered to have significant advantages over traditional merchandising. Specifically, vending machines enable the automated sale of merchandise at unconventional locations and times; and they do not require sales personnel.
Although the basic advantages of vending machines are significant, prior art vending machines have several significant disadvantages when compared to traditional merchandising, particularly relating to inventory control and pricing. A first disadvantage is the difficulty of maintaining an inventory of perishable items. A second disadvantage is the difficulty of selling or “turning over” an inventory of low demand items or items of inferior quality. Although some vending machine suppliers offer to buy back inventory from operators who no longer want to sell certain products, such suppliers often fail to live up to their offer when an operator tries to exercise this option.
There have been many attempts at addressing the inventory problems of vending machines, including methods for determining what products are the best sellers, what are the appropriate times to re-stock vending machine items and in what quantities. The solutions include methods and systems that enable vending machine operators to remotely monitor inventory and remotely retrieve sales data. Other solutions have been proposed in the forms of accounting software and bar code readers that detect the expiration dates of vending machine items.
Examples of vending machine patent prior art include the following U.S. patents: U.S. Pat. No. 4,412,292, entitled “System for the Remote Monitoring of Vending Machines;” U.S. Pat. No. 4,654,800, entitled “Control and Monitoring Apparatus for Vending Machines;” U.S. Pat. No. 5,091,713, entitled “Inventory, Cash, Security, and Maintenance Control Apparatus and Method for a Plurality of Remote Vending Machines;” U.S. Pat. No. 5,367,452, entitled “Mobile Merchandising Business Management System which Provides Comprehensive Support Services for Transportable Business Operations;” and U.S. Pat. No. 4,282,575, entitled “Control and Monitoring Apparatus for Vending Machines.” These inventions generally disclose remote monitoring systems, currency control systems, and data collection systems designed to address shortcomings of prior art vending devices.
Non-patent prior art includes VendMaster's software product entitled “Windows for Vending PRO with Inventory.” This product enables a vending machine operator to report and analyze various historical sales data. VendMaster's product is intended to enhance a vending machine operator's ability to identify high-demand inventory, determine preferable times to stock the machine and calculate suggested prices.
The aforementioned solutions generally attempt to solve inventory problems by allowing operators to monitor and analyze raw sales data. These solutions fail to adequately address the aforementioned shortcomings of present vending machines. Specifically, the prior art fails to provide adequate solutions to the problems of maintaining an inventory of perishable items; increasing inventory turnover; and recovering the investment in low demand or inferior quality items.
Using the prior art solutions, an operator may use collected supply and demand data to help make pricing decisions, but the fact that operators must manually ratify and implement the decisions renders these solutions burdensome, inaccurate an inefficient. These solutions are burdensome in that the accounting and analysis required to arrive at pricing decisions is time consuming. These solutions are inaccurate as the human decision making process regarding pricing is largely arbitrary. These solutions are inefficient because human decisions and the implementations of those decisions are not dynamically responsive to real-time market pressures; they are delayed until the operator analyzes supply and demand data, arrives at a pricing decision, and posts the pricing decision.
Accordingly, the current methods of implementing new pricing decisions are inconsistent with the fundamental business philosophy of vending machines. Vending entrepreneurs have always adhered to the idea that vending machines manage themselves. Pricing decisions in a vending operation, however, cannot currently be implemented as easily as they may be, for example, in the retail environment where humans are physically present to monitor supply and demand and adjust prices accordingly.
A need therefore exists for a method and apparatus that monitors supply and demand of a vending machine inventory and that dynamically and automatically calculates and implements item prices to increase a vending machine's profitability. A need further exists for a method and apparatus for adjusting item prices of a vending machine to relieve vending machine operators of the burdens, inaccuracies and inefficiencies in management that result from the current methods of pricing items.
Accordingly, the shortcomings associated with the related art have heretofore not been adequately addressed. The present invention addresses such problems by providing an apparatus and processing approach that have not previously been proposed.
The present invention provides a method and apparatus to automatically and dynamically determine, adjust and manage product pricing in a vending machine to account for current market trends. According to a first aspect of the present invention, a method is disclosed for automatically managing a price of a product in a vending machine. The method includes the step of receiving a product identifier specifying the product. The method further includes the step of receiving inventory data. The inventory data includes the quantity of the product in the vending machine.
Next, the method includes the step of determining price management data associated with said product. The price management data specifies supply and demand data associated with the product. The method continues with the step of determining the price for the product, and storing the price management data and the price. This first method of managing inventory pricing is particularly useful if performed upon stocking the vending machine. An apparatus is also disclosed for performing the steps of first method.
According to another aspect of the present invention, a second method is disclosed for automatically managing a price of a product in a vending machine. The second method includes the step of accessing price management data and inventory data associated with the product. The inventory data and price management data are used, in part, to form the basis for the price in the step of determining the price of the product. The determined price is then stored in a memory and preferably displayed. This second method may be performed in response to a particular event, such as a product sale, a change in the environment, or according to a schedule. An apparatus is also disclosed for performing the steps of the second method.
It is an object of the present invention to provide a method and apparatus for dynamically managing the price of a product in a vending machine. The above object and other objects features and advantages are readily apparent from the detailed description when taken in connection with the accompanying drawings.
A more complete appreciation of the invention and many of the attendant advantages thereof may be readily obtained by reference to the following detailed description when considered with the accompanying drawings, wherein:
Apparatus Architecture
An embodiment of the method and system of the present invention will now be discussed with reference to
As shown, vending machine 100 includes an input device 110 for receiving input from a customer indicating a product selection. Input device 110 may also be used for receiving input from an operator during stocking or maintenance of vending machine 100. Although input device 110, as illustrated, includes a set of alpha-numeric keys for providing input to vending machine 100, input device could include a selector dial, a set of buttons associated with a respective set of item dispensers, or any other conventional input device commonly employed by a vending machine designer. Further, vending machine 100 may include more than one input device 110. For example, vending machine 100 may include an exterior input device 110 for receiving customer input and an interior input device (not shown) for receiving operator input. In the illustrated embodiment, input device 110 receives input data from both operators and customers.
As shown, vending machine 100 includes a sensor 115 for sensing surrounding environmental conditions. Sensor 115 is preferably a conventional temperature sensor configured to sense the local outdoor temperature or the external environmental temperature surrounding vending machine 100. Sensor 115 could include a receiver for receiving a local temperature from a weather service.
Vending machine 100 also includes several mechanisms for receiving payment and dispensing change, including coin acceptor 112, bill validator 114, magnetic stripe reader 116 and change dispenser 118. Magnetic stripe reader 116 is a conventional reader for reading data on the magnetic stripe of a credit or debit card, and it may cooperate with conventional remote point-of-sale credit card processing equipment (not shown) to validate credit based purchases through a conventional credit authorization network. Coin acceptor 112, bill validator 114 and change dispenser 118 communicate with currency storage apparatus 120 and may include conventional devices such as Mars models AE-2400, MC5000, TRC200 or CoinCo model 9300-L. Coin acceptor 112 and bill validator 114 receive and validate currency that is stored by currency storage apparatus 120.
Referring now to
In addition to the elements previously mentioned, processing module 144 includes a central processing unit 126 (“CPU”) connected to communication port 142. CPU 126 communicates with random access memory (RAM) 128, read only memory (ROM) 130, clock 132. CPU 126 also communicates with at least one item dispenser 122, at least one price display 124 and storage device 134. Price display 124 may be any display device, preferably a digital display, employing conventional technology such as a light emitting diode (“LED”) display or a liquid crystal display (“LCD”).
Vending machine 100 includes twelve item dispensers 122 and twelve price displays 124, one item dispenser and display corresponding to each product offered for sale by vending machine 100. As in many conventional vending machines, item dispenser 122 may be activated by CPU 126 after a customer has purchased item 136, causing item 136 to be transferred to receptacle 140. A customer has access to a purchased item in receptacle 140 via door 138. Purchased item 136 can then be removed by a customer from receptacle 140 through door 138.
As shown in
As shown in
Data Tables
Each record in price management table 500 includes a dispenser identifier 510 and a product identifier 512. Dispenser identifier field 510 stores a dispenser identifier that uniquely identifies a corresponding item dispenser 122 of vending machine 100. Product identifier field 512 identifies the product associated with the dispenser identified by field 510.
In the present embodiment, there is a one to one correspondence between a dispenser and a product, i.e. either field uniquely identifies a record. In other words, each dispenser dispenses only one product, and each product is limited to a single dispenser. One of ordinary skill will recognize that by distributing the price management data among multiple tables, multiple products could be offered in a single dispenser, and/or multiple dispensers could dispense the same product.
The remaining fields shown in
Current price field 518 contains the selling price of the product associated with the item dispenser. Current price field 518 may be populated by the operator during stocking or routine maintenance, and may be determined according to the process steps of the present invention. Exemplary process steps which may be executed to automatically determine a current price are described with reference to
The next two fields of price management table 500 define shelf times for the product identified by field 512. Total shelf time field 524 defines the maximum allowable shelf time for the product. The contents of field 524 are calculated by CPU 126 based on stock date field 520 and termination date field 522 upon stocking. Remaining shelf time field 526 defines the remaining shelf time of the product and is periodically calculated by CPU 126 based on the system date, and the contents of field 522.
Evaluation frequency field 528 stores a code representing a rule defining the frequency with which the CPU 126 should evaluate the price of the product identified by field 512. Although field 528 only contains a code, the contents of field 528 illustrated in
Of course, the present invention envisions numerous alternative evaluation frequency rules. For example, a rule could be defined to evaluate the price whenever sensor 115 senses a predetermined condition. If sensor 115 is a thermostat, CPU 126 could be programmed to evaluate the price whenever the temperature exceeded a predefined temperature. Other evaluation frequency rules could be implemented to evaluate the price when demand for a product rapidly changes or if at the current demand level items will remain stocked past the termination date in field 522. Further, CPU 126 could be programmed to evaluate prices during periods of low activity, such as during the early morning.
Last evaluation date/time field 530 stores a timestamp identifying the time of last sale, and field 532 stores the number of sales of the associated product made since the last price evaluation. These fields are periodically updated by CPU 126, and are periodically accessed by CPU 126 based on the evaluation rule represented by the contents of field 528.
Fields 534-538 define demand-based price evaluation parameters. Previous demand field 534 stores the level of demand as of the last price evaluation. Current demand field stores the current demand level for the product in the dispenser identified by the contents of field 510. CPU 126 periodically calculates the current demand and stores it in field 536. After each evaluation, CPU 126 sets the contents of previous demand field 534 equal to the contents of current demand field 536. Demand increment field 538 defines the incremental difference between the previous demand and the current demand that is required to trigger a price evaluation process.
Fields 542-546 define price parameters for the product identified by field 512. The minimum price to be charged for the product is stored in minimum price field 542; the manufacturer's suggested retail price for the product is stored in suggested price field 544; and the maximum price to be charged for the product is stored in maximum price field 546.
The manufacturer's suggested retail price of field 544 may be used as the initial current price after stocking, or it may be used as a factor to determine future prices. The minimum price and maximum price fields 542 and 546 are used to prevent the calculated price from falling outside a predetermined range. This financially protects both the vending machine operator and the consumer.
Evaluation Process Steps
Having thus described the system architecture and components of the present embodiment, the operation of the system will now be described in greater detail with reference to
According to the present invention, there are generally three times at which it is appropriate to determine the price of a product in a vending machine: after stocking, after a sale of an item and after a period of time.
Referring now to
At step 612, CPU 126 retrieves a record from authorization table 400 using the received operator identifier as an index. CPU 126 then, as shown at step 614, compares operator identifier and authorization code received at step 610 with the contents of operator identifier field 402 and authorization code field 404 retrieved at step 612, respectively. It may then be determined, according to some embodiments, if the operator is authorized to access the price management table, at 616. If the comparison yields a match of the respective data, CPU 126 may proceed to execute step 620, for example, otherwise, CPU 126 may deny the operator access to price management table 500 at 618.
At step 620, CPU 126 receives input from the operator. The operator inputs a dispenser identifier, a product identifier and relevant portions of the inventory, evaluation and pricing data pertaining to the stocked product and associated dispenser to be stored in price management table 500. The inventory data received from the operator includes a stocked quantity, and a current price. The evaluation data received from the operator includes a termination date, an evaluation frequency and a demand increment. The pricing data received from the operator includes a price adjustment increment, a minimum price, a suggested price and a maximum price. The data received from the operator is stored by CPU 126 in the appropriate fields of price management table 500. Of course, receiving data for one or more of these fields from the operator may be optional as CPU 126 could supply default values for certain fields. In addition, the data for one or more of these fields could be automatically received from a remote source using the network configuration illustrated in
At step 622, CPU 126 calculates the remaining price management data to be stored in price management inventory table 500. Specifically, CPU 126 calculates the total shelf time, remaining shelf time and current price for the associated product. Although, the current price may be input by the operator, the current price would preferably be set equal to the manufacturer's suggested price stored in field 544. Of course, in an alternate embodiment, the current price could be determined in accordance with the price evaluations described below with reference to the post-purchase evaluation process and the periodic evaluation process.
At step 624, the stocking process concludes with the step of adjusting the price display 124 corresponding to item dispensers 122 dispensing the associated product. The price displays 124 are adjusted to display the price determined at step 620.
Referring now to
At step 722, CPU 126 updates the price management data pertaining to the product selected by the customer and stores the updated data in price management table 500. The step of updating includes the step of decrementing the contents of available quantity field 516, incrementing the contents of field 532 to reflect the sale and updating the contents of current demand field 536. At step 724, a determination is made whether the necessary events have occurred to require a price evaluation for the selected product. In the present embodiment, this step includes comparing the parameter identified by evaluation frequency field 528 to either last evaluation date/time field 530 or sales since last evaluation field 532. If it is time to evaluate the price of the selected product, CPU processes step 726.
At step 726, CPU 126 calculates the change in demand for the specified product and at step 728 compares the calculated change in demand to the demand increment data stored in field 538. If the demand for the specified product has changed by at least the demand increment stored in field 538, CPU 126 processes step 730 and determines a new current price for the specified product. One preferred formula that can be used to determine a new current price is:
i Pnc=Pcurrent±Pincrement
where:
Pnc represents the new current price;
Pcurrent represents the current price stored in field 518; and
Pincrement represents the price increment stored in field 540.
If the demand for the product has increased, the new current price equals the contents of current price field 518 plus the contents of price adjustment field 540. If the demand for the product has decreased, the new current price equals the contents of current price field 518 less the contents of price adjustment field 540. At step 732, CPU 126 verifies that the new current price falls within the range of acceptable prices as defined by minimum price field 542 and maximum price field 546.
If the new current price is within the acceptable range, current price field 518 is updated to reflect the new current price as shown at step 734. It is important to note that although a specific price determination formula has been described herein, the method and apparatus of the present invention is intended to work with many different price determination formulas applicable to product pricing. Various formulas may easily be implemented by one of ordinary skill in the art with minor design variations. Finally, at step 736, CPU 126 updates the price display 124 associated with subject item dispenser to reflect the new current price of the product.
Referring now to
At step 810, CPU 126 begins the periodic price evaluation process by retrieving a record associated with a specified product from price management table 500. At step 812, CPU 126 accesses the contents of evaluation frequency field 528 to determine if the price evaluation frequency is based on time, as shown at step 814. If the evaluation of the product's price is not based on time, the process ends. Otherwise, the process proceeds to step 816. In an alternate embodiment, step 814 may include determining whether the quantity of the product is non-zero. If the quantity of the product is zero, CPU 126 would terminate the process to avoid evaluating the price of an unavailable product.
At step 816, CPU 126 determines the time elapsed since the price of the product was last evaluated. This is accomplished by retrieving the system date and time from clock 132 and comparing the system date and time to the date and time stored in last evaluation date/time field 530. At step 818, the result is compared to the evaluation frequency parameter indicated by field 528. It may then be determined, according to some embodiments, if sufficient time has elapsed to evaluate the price, at 820. If sufficient time has elapsed, the process may proceed, for example, with step 822. Otherwise, the process may ends.
At step 822, CPU 126 calculates the change in demand for the specified product and compares the calculated change in demand to the demand increment data stored in field 538. It may then be determined, according to some embodiments, if the demand level has changed by an amount appropriate to require an adjustment of the price, at 824. If the demand for the specified product has changed by at least the demand increment stored in field 538, for example, CPU 126 processes step 826 and determines a new current price for the specified product. One possible formula that can be used to determine a new current price is:
Pnc=[(STremain/STtotal)×(Pmaximum−Pminimum )]+Pminimum
where:
Pnc represents the new current price;
STremain represents the remaining shelf time stored in field 526;
STtotal represents the total shelf time stored in field 524;
Pmaximum represents the maximum price stored in field 542; and
Pminimum represents the minimum price stored in field 546.
This formula determines the new current price based on the remaining shelf life and the maximum and minimum price boundaries. In this embodiment, the calculated price may be rounded to the nearest price adjustment increment indicated in field 540. At step 830, current price field 518 is updated to reflect the new current price as shown at step 830. Finally, at step 832 CPU 126 updates the price display associated with subject item dispenser to reflect the new current price of the product.
Referring back to
Pnc=[(STremain/STtotal)×(Pmaximum−Pminimum)]+Pminimum
Pnc=[(62/70)×($1.15−$0.35)]+$0.35
Pnc=$1.0586
Rounding the result to the nearest price adjustment increment stored in field 540, the selling price is $1.05.
As described, the price evaluation formulas discussed with reference to
Referring now to
In this configuration, the previously described functionality provided by processing module 144 (i.e. inventory management and dynamic price adjustment) can be remotely performed by price management server 900. The resulting price adjustments are transmitted from price management server 900 to each of the plurality of vending machines.
Conventional cryptographic techniques may be employed to ensure the authenticity of remote data received by the nodes. Further, authentication table 400, or a functional equivalent, may be employed at price management server 900, the node or both.
While the best mode for carrying out the invention has been described in detail, those familiar with the art to which the invention relates will recognize various alternative designs and embodiments for practicing the invention. These alternative embodiments are within the scope of the present invention. Accordingly, the scope of the present invention embodies the scope of the claims appended hereto.
The present application is a divisional of U.S. patent application Ser. No. 08/947,798, filed Oct. 9, 1997 in the name of Tedesco et al., entitled “METHOD AND APPARATUS FOR DYNAMICALLY MANAGING VENDING MACHINE INVENTORY PRICES”.
Number | Name | Date | Kind |
---|---|---|---|
3688276 | Quinn | Aug 1972 | A |
3937929 | Knauer | Feb 1976 | A |
4008792 | Levasseur et al. | Feb 1977 | A |
4237537 | Pitches et al. | Dec 1980 | A |
4245730 | Bachmann et al. | Jan 1981 | A |
4282575 | Hoskinson et al. | Aug 1981 | A |
4359147 | Levasseur et al. | Nov 1982 | A |
4412292 | Sedam et al. | Oct 1983 | A |
4417671 | Kawasaki et al. | Nov 1983 | A |
4478353 | Levasseur et al. | Oct 1984 | A |
4498570 | King et al. | Feb 1985 | A |
4593361 | Otten | Jun 1986 | A |
4636963 | Nakajima et al. | Jan 1987 | A |
4654800 | Hayashi et al. | Mar 1987 | A |
4679150 | Hayashi et al. | Jul 1987 | A |
4766548 | Cedrone et al. | Aug 1988 | A |
4882688 | Kondziolka et al. | Nov 1989 | A |
5036472 | Buckley et al. | Jul 1991 | A |
5091713 | Horne et al. | Feb 1992 | A |
5257179 | DeMar | Oct 1993 | A |
5339250 | Durbin | Aug 1994 | A |
5353219 | Mueller et al. | Oct 1994 | A |
5367452 | Gallery et al. | Nov 1994 | A |
5450938 | Rademacher | Sep 1995 | A |
5452344 | Larson | Sep 1995 | A |
5511646 | Maldanis et al. | Apr 1996 | A |
5521364 | Kimura et al. | May 1996 | A |
5544288 | Morgan et al. | Aug 1996 | A |
5608643 | Wichter et al. | Mar 1997 | A |
5613620 | Center et al. | Mar 1997 | A |
5615109 | Eder | Mar 1997 | A |
5638985 | Fitzgerald et al. | Jun 1997 | A |
5649114 | Deaton et al. | Jul 1997 | A |
5685435 | Picioccio et al. | Nov 1997 | A |
5701252 | Facchin et al. | Dec 1997 | A |
5724518 | Helbling | Mar 1998 | A |
5768142 | Jacobs | Jun 1998 | A |
5802015 | Rothschild et al. | Sep 1998 | A |
5835896 | Fisher et al. | Nov 1998 | A |
5844808 | Konsmo et al. | Dec 1998 | A |
5873069 | Reuhl et al. | Feb 1999 | A |
5878401 | Joseph | Mar 1999 | A |
5930771 | Stapp | Jul 1999 | A |
5933814 | Rosenberg | Aug 1999 | A |
5959869 | Miller et al. | Sep 1999 | A |
5997928 | Kaish et al. | Dec 1999 | A |
6012834 | Dueck et al. | Jan 2000 | A |
6021394 | Takahashi | Feb 2000 | A |
6056151 | Peery et al. | May 2000 | A |
6056194 | Kolls | May 2000 | A |
6078893 | Ouimet et al. | Jun 2000 | A |
6085164 | Smith et al. | Jul 2000 | A |
6119099 | Walker et al. | Sep 2000 | A |
6181981 | Varga et al. | Jan 2001 | B1 |
6193154 | Phillips et al. | Feb 2001 | B1 |
6243691 | Fisher et al. | Jun 2001 | B1 |
6324520 | Walker et al. | Nov 2001 | B1 |
6748296 | Banerjee et al. | Jun 2004 | B2 |
20020111157 | Stieber et al. | Aug 2002 | A1 |
20080046113 | Tedesco et al. | Feb 2008 | A1 |
20080051934 | Tedesco et al. | Feb 2008 | A1 |
Number | Date | Country |
---|---|---|
2070736 | Jun 1992 | CA |
2217739 | Apr 1996 | CA |
4037689 | Jun 1992 | DE |
0 085 546 | Aug 1983 | EP |
0323383 | Jul 1989 | EP |
512413 | Nov 1992 | EP |
0512509 | Nov 1992 | EP |
0526118 | Feb 1993 | EP |
0619662 | Oct 1994 | EP |
0697793 | Feb 1996 | EP |
0779587 | Sep 1996 | EP |
0779587 | Sep 1996 | EP |
0744856 | Nov 1996 | EP |
0 817 138 | Jan 1998 | EP |
0 862 150 | Sep 1998 | EP |
2109305 | Jun 1983 | GB |
2265032 | Sep 1993 | GB |
2 317 257 | Mar 1998 | GB |
58-132886 | Aug 1983 | JP |
2001093 | Jan 1990 | JP |
2208798 | Aug 1990 | JP |
4235700 | Aug 1992 | JP |
5242363 | Sep 1993 | JP |
6035946 | Feb 1994 | JP |
7065218 | Mar 1995 | JP |
7078274 | Mar 1995 | JP |
07098779 | Apr 1995 | JP |
95139380 | Jun 1995 | JP |
95162556 | Jun 1995 | JP |
07249176 | Sep 1995 | JP |
7272012 | Oct 1995 | JP |
8030848 | Feb 1996 | JP |
08137951 | May 1996 | JP |
8221484 | Aug 1996 | JP |
8221645 | Aug 1996 | JP |
8329323 | Dec 1996 | JP |
9016836 | Jan 1997 | JP |
9062908 | Mar 1997 | JP |
9097288 | Apr 1997 | JP |
9190478 | Jul 1997 | JP |
9190479 | Jul 1997 | JP |
H9 198554 | Jul 1997 | JP |
10187820 | Jul 1998 | JP |
10214284 | Aug 1998 | JP |
10240830 | Sep 1998 | JP |
10269049 | Oct 1998 | JP |
10289372 | Oct 1998 | JP |
11088560 | Mar 1999 | JP |
9503826 | Apr 1995 | KR |
WO 9708638 | Mar 1987 | WO |
WO 9848388 | Oct 1988 | WO |
WO 9016033 | Dec 1990 | WO |
WO 9409440 | Apr 1994 | WO |
WO 9527242 | Oct 1995 | WO |
WO 9632701 | Oct 1996 | WO |
WO 9708638 | Mar 1997 | WO |
WO 9716797 | May 1997 | WO |
WO 9716897 | May 1997 | WO |
WO 9720279 | Jun 1997 | WO |
WO 9721200 | Jun 1997 | WO |
WO 9723838 | Jul 1997 | WO |
WO 9724701 | Jul 1997 | WO |
WO 9725684 | Jul 1997 | WO |
WO 9728510 | Aug 1997 | WO |
WO 9744749 | Nov 1997 | WO |
WO 9750064 | Dec 1997 | WO |
WO 9806050 | Feb 1998 | WO |
WO 9815907 | Apr 1998 | WO |
WO 9828699 | Jul 1998 | WO |
Number | Date | Country | |
---|---|---|---|
20080046118 A1 | Feb 2008 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 08947798 | Oct 1997 | US |
Child | 11926948 | US |