1. A method of attaching two substrates, comprising:
supplying a first substrate from a first source, wherein the first substrate is a fabric having an indicium thereon;
supplying a second substrate from a second source; and
curing the substrates until the substrates are bonded to each other to form a product, wherein the indicium is visible on the product.
2. The method of claim 1, wherein the second substrate is an elastomeric composition.
3. The method of claim 1, wherein the second substrate is a urethane composition.
4. The method of claim 1, wherein the first substrate is a braid.
5. The method of claim 1, wherein the first and second substrates are bonded thereto to form a substantially unitary product.
6. The method of claim 1, wherein the curing is accomplished through heating from a platen heating system.
7. The method of claim 6, wherein the platen heating system includes plates disposed adjacent a conveyor to heat the second substrate.
8. The method of claim 1, wherein the first and second substrates are attached to each other in a continuous manner.
9. An apparatus for continuously attaching a first substrate to a second substrate, comprising:
a first substrate supply source that continuously dispenses a first substrate onto a top surface of a second substrate, wherein the first substrate includes an indicium thereon;
a second substrate supply source that continuously dispenses the second substrate onto a conveyor;
a secondary conveyor system that presses the first substrate into the second substrate; and
a heating mechanism that heats the first substrate and the second substrate, wherein the first substrate is vulcanized to the second substrate to form a product having a substantially smooth surface and wherein the indicium is visible on the surface.
10. The attaching apparatus of claim 9, wherein the first substrate is a braid.
11. The attaching apparatus of claim 10, wherein the first substrate is a fabric.
12. The attaching apparatus of claim 9, wherein the heating mechanism heats the first and second substrates to a temperature of between about 200\xb0 F. to about 400\xb0 F.
13. The attaching apparatus of claim 9, wherein the heating occurs for a time period between about 4 minutes and about 10 minutes.
14. The attaching apparatus of claim 9, wherein a substantially permanent bond is formed between the first substrate and the second substrate.
15. The attaching apparatus of claim 9, wherein the product is cooled for a period of time less than about a minute after entering a cooling zone.
16. The attaching apparatus of claim 9, wherein the second substrate is an elastomeric composition.
17. The attaching apparatus of claim 16, wherein the elastomeric composition comprises about 20% to about 40% rubber, about 40% to about 60% fillers, about 2% to about 10% process oil, and about 5% to about 15% other additives.
18. A method of identifying a source of goods, comprising:
providing a first substrate comprising a fabric having an indicium thereon;
providing a second substrate comprising an elastomeric composition; and
curing the first substrate to the second substrate to form a product, wherein the indicium is visible on the product to display information about the product.
19. The method of claim 18, wherein the method further includes the step of applying the indicium onto the first substrate before the first substrate is provided.
20. The method of claim 18, wherein the first and second substrates are provided in a substantially continuously manner.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method for optimizing merchandise profitability, comprising:
A. modeling gross margin for a retail enterprise as a function of at least
i. product breadth and product depth for each of at least one class of goods retailed by each of at least one retail site in a group of sites of that retail enterprise, wherein each group of sites comprises one or more retail sites, and
ii. expected discount price for each such class of goods at each such retail site in such group of sites,
B. constraining the gross margin so modeled,
C. determining, for at least one such retail site in such group of sites, an optimal breadth, optimal depth, and optimal discount price, of at least one such class of goods retailed by that site, wherein the determining step includes maximizing the gross margin for the retail enterprise.
2. The method of claim 1, wherein the constraining step includes constraining the gross margin so modeled such that
i. presentation minimums for each such class of goods are satisfied at each such retail site in such group of sites,
ii. expected demand for each such class of goods at each such retail site in such group of sites does not fall below supply of that class of goods at that site, where the expected demand is determined as a function of product breadth and price discount of that class of goods at that retail site,
iii. an expected buying cost of the goods does not exceed a budget therefor,
iv. a sales target for the goods is a function of comp sales of those goods over a prior selling period,
v. a number of units of goods to be bought does not exceed a value that is a function of the space available therefor.
3. The method of claim 1, wherein the modeling step includes modeling the gross margin in accord with the relation:
GM$
=
\u2211
c
\u2062
\u2211
s
\u2062
N
s
\u2062
x
cs
\u2061
(
P
cs
\u2061
(
1
–
d
cs
)
–
C
cs
)
where
Ns represents a number of sites in each such group of sites;
xcs represents total units to be bought for class of goods c at each such site in such group of sites s;
Pcs represents a full price for an average item in class of goods c in each such site in each such group of sites;
dcs represents an expected discount for each such class of goods c in each such site in each such group of sites s; and
Ccs represents average cost for goods to be bought for each such class of goods c in such site in such group of sites s.
4. The method of claim 1, wherein the modeling step includes modeling the gross margin, further, as function of one or more of: a presentation minimum for a class of goods in at least one site in a group of sites, a full price of an average item in each class of goods in at least one site in a group of sites, a unit cost of an average item in each class of goods in at least one site in a group of sites, a length of a selling season for the retail enterprise, a number of sites in each of the groups of sites, a price elasticity of demand faced by goods in each class in at least one site in a group of sites, and expected full-price weekly sales for goods in each class of goods in at least one site in a group of sites as a function of breadth for each of such goods.
5. The method of claim 1, wherein step (B)(i) includes constraining the gross margin so modeled such that a value of the depth for each class of goods at each such site is bounded by a value that is a function of the breadth of that class at that site and of the presentation minimum of that class at that site.
6. The method of claim 1, wherein step (B)(i) includes constraining the gross margin so modeled such that the depth for each such class of goods at each such site satisfies the relation:
xcs\u2267ycsPMcs \u2200s,c
where,
xcs represents total units to be bought for class of goods c at each such site in such group of sites s;
ycs represents the breadth of class of goods c at each such site in such group of sites s; and
PM represents the presentation minimum for each class of goods c at each such site in such group of sites s.
7. The method of claim 1, wherein step (B)(ii) includes constraining the gross margin so modeled such that a value of the depth for each class of goods at each such site in such group of sites is bounded by to a value that is a function of an expected discount for each such class of goods at each site in such group of sites, and of the expected full-price weekly sales for each such class of goods at each such site in such group of sites, and of the price elasticity for each such class of goods at each such site in such group of sites.
8. The method of claim 1, wherein step (B)(ii) includes constraining the gross margin so modeled such that the depth for each such class of goods at each such site satisfies the relation:
xcs\u2266(1\u2212dcs)\u2212\u03b3csWDcs(ycs) \u2200s,c
where,
xcs represents total units to be bought for each such class of goods c in such site in such group of sites s;
dcs represents expected discount for class of goods c in such site in such group of sites s;
W represents a length of a selling season for the retail enterprise; and
Dcs(ycs) represents expected full-price weekly sales for such class of goods c in each such site in such group of sites s as a function of breadth (ycs).
9. The method of claim 8, further comprising the step of determining the expected full-price weekly sales Dcs(ycs) for each such class of good at each such site based on historical sales data.
10. The method of claim 8, further comprising the step of determining the expected full-price weekly sales Dcs(ycs) for each such class of good at each such site by applying econometric demand modeling techniques to sales data.
11. The method of claim 1, wherein step (B) further includes constraining the gross margin so modeled such that values for depth and breadth for each class of goods for each site are greater than or equal to zero and constraining a value of the expected discount for each class of goods for each site in a group of sites to a range of zero to one.
12. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that a total of expected buying cost of all goods over all sites does not exceed a total budget.
13. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that the total expected buying cost for all the classes of goods for all the retail sites satisfies the relation
\u2211
c
\u2062
\u2211
s
\u2062
C
cs
\u2062
x
cs
\u2264
B
where,
xcs represents total units to be bought for each such class of goods c in such site in such group of sites s;
Ccs represents average cost for goods to be bought for each such class of goods c in such site in such group of sites s; and
B represents total budget.
14. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that the expected buying cost for each class of goods does not exceed the a budget for that respective class of goods.
15. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that the expected buying cost for each retail site does not exceed a budget for that respective retail site.
16. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that a total number of units to be bought for each group of sites does not exceed a value that is a function of the space available for the average site in that group of sites.
17. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that the total buy for each group of sites satisfies the relation
\u2211
c
\u2062
x
cs
\u2062
F
c
\u2264
AF
s
\u2062
R
s
\u2062
\u2003
where,
xcs represents total units to be bought for each such class of goods c in such site in such group of sites s;
Fc represents space needed for each item in class of goods c;
AFs represents available space in each such site in each such group of sites s; and
Rs represents the number of replenishments in a selling time period for each such site in each such group of sites s.
18. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that total sales of all classes of goods in all sites is bounded by a value that is a function of the depth of each such class of goods at each such site in such group of sites and of the expected discount of each such class of goods at each such site in such group of sites.
19. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that a sales target for the retail enterprise satisfies the relation
\u2211
c
\u2062
\u2211
s
\u2062
N
s
\u2062
x
cs
\u2062
P
cs
\u2061
(
1
–
d
cs
)
\u2265
S
where,
xcs represents total units to be bought for each such class of goods c in such site in such group of sites s;
Ns represents a number of sites in each such group of sites;
Pcs represents a full price for an average item in class of goods c in each such site in each such group of sites;
dcs represents an expected discount for each such class of goods c in each such site in each such group of sites s; and
S represents a sales target for the retail enterprise.
20. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that a sales target for each such class of goods is bounded by a value that is a function of the depth of that class of goods in each such site in each such group of sites and of an expected discount of that class of goods in each such site.
21. The method of claim 1, wherein step (B) further includes the step of constraining the gross margin so modeled such that a sales target for the retail enterprise is bounded by a value that is a function of the depth of each such class of goods in each such site in each such group of sites and of an expected discount of each such class of goods in each such site.
22. The method of claim 1, further comprising the step of selecting an assortment of goods for allocation to a retail site based on the optimal breadth, depth, and discount price determined in step (C).
23. The method of claim 1, further comprising the step of selecting an assortment of goods for display at retail site based on the optimal breadth, depth, and discount price determined in step (C).
24. The method of claim 1, further comprising the step of selecting goods for display at a said retail site based on the optimal breadth, depth, and discount price determined in step (C).
25. A method for optimizing merchandise profitability, comprising:
A. modeling gross margin for a retail enterprise in accord with the relation:
GM
\u2062
\u2003
\u2062
$
=
\u2211
c
\u2062
\u2211
s
\u2062
N
s
\u2062
x
cs
\u2061
(
P
cs
\u2061
(
1
–
d
cs
)
–
C
cs
)
where
GM$ represents gross margin for the retail enterprise;
Ns represents a number of sites in each such group of sites;
xcs represents total units to be bought for class of goods c at each such site in such group of sites s;
Pcs represents a full price for an average item in class of goods c in each such site in each such group of sites;
dcs represents an expected discount for each such class of goods c in each such site in each such group of sites s; and
Ccs represents average cost for goods to be bought for each such class of goods c in such site in such group of sites s;
B. constraining the gross margin so modeled such that
i. a depth for each such class of goods at each such site satisfies the relation:
xcs\u2267ycsPMcs \u2200s,c
where,
xcs represents total units to be bought for class of goods c at each such site in such group of sites s;
ycs represents the breadth of class of goods c at each such site in such group of sites s; and
PM represents the presentation minimum for each class of goods c at each such site in such group of sites s;
ii. expected demand for each such class of goods at each such retail site in such group of sites does not fall below supply of that class of goods at that site in accord with the relation:
xcs\u2266(1\u2212dcs)\u03b3csWDcs(ycs) \u2200s,c
where,
xcs represents total units to be bought for each such class of goods c in such site in such group of sites s;
dcs represents expected discount for class of goods c in such site in such group of sites s;
W represents a length of a selling season for the retail enterprise; and
Dcs(ycs) represents expected full-price weekly sales for such class of goods c in each such site in such group of sites s as a function of breadth (ycs),
iii. values for depth and breadth for each class of goods for each site are greater than or equal to zero,
iv. a value of an expected discount for each class of goods for each site in a group of sites to a range of zero to one, and
C. determining, for at least one such retail site in such group of sites, an optimal breadth, optimal depth, and optimal discount price, of at least one such class of goods retailed by that site, wherein the determining step includes maximizing the gross margin for the retail enterprise.