1. An enhanced golf ball and method for its construction that works as part of a system; said system further comprising:
a. a plurality of enhanced components that work in concert as an automated system to capture, analyze, score, save, archive, track and communicate real-time relevant golf data specific to individual golfers; said enhanced components to include a PDA and at least one golf ball, said enhanced components further comprising:
i. means for inter-component communications;
ii. means for mapped golf course access;
iii. means for data processing access;
iv. means for virtual caddy access;
v. means for virtual trainer access;
whereby enabling the communication of information captured by the enhanced components to the golfer during a round of golf, training or practice via the virtual caddyvirtual trainer application software, in the same way routine information such as the ending location of the golf ball once struck, is made available to the tour golfer by his support structure; for example spotters, live caddy or trainer.
2. An enhanced golf ball as recited in claim 1, said enhanced golf ball comprising computing intelligence:
a. said computing intelligence encased in said enhanced golf ball comprising:
i. at least one microchip; said microchip(s) comprising communications, one or more impact sensor(s), unique identifier, pressure sensor(s), power source(s), antenna circuit(s) and other common computer circuitry as an integral part of the enhanced golf ball;
b. a packaged microchip buffer; said packaged microchip buffer comprising said computing intelligence embedded in a protective buffer layer; whereby the computing intelligence is protected during the enhanced golf ball manufacturing process;
c. a compression prevention package; said compression prevention package comprising said packaged microchip buffer embedded in a compression prevention layer; whereby the outer layers of the enhanced golf ball are prevented from collapsing on the packaged microchip buffer during ball compression caused by the impact of the golf club; thereby protecting the computing intelligence;
d. a core; said core comprising said compression prevention package embedded in a compression layer comprising a highly elastic material; whereby the elastic nature of the core together with the design characteristics of the layers including the a ball cover determine the performance characteristics of the enhanced golf ball;
e. at least one antenna.
3. An enhanced golf ball as recited in claim 2, said antenna(s) is located in a mantle layer(s); said mantle layer(s) comprising:
a. material with elastic properties selected from the members of the group with elastic properties greater than, equal to and less than the elastic properties of said core; whereby the characteristics of the numerous combinations of core(s), mantle(s) and ball cover(s) could be adjusted to build various models of the enhanced golf ball to target high, mid and low handicap golfers;
b. said ball cover with cover properties selected from members of the group plastic, rubber and blend of both.
4. An enhanced golf ball as recited in claim 2, said antenna(s) is located just inside the outer core.
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 production instruction system which creates production instructions of a product in which a characteristic value of each product is liable to vary from a standard value aimed in design due to instability of production processes, comprising;
an information collection unit configured to collect performance information of results selected as a product in accordance with design when each product satisfies an original design standard value, selected as other products having different standard values when each product does not satisfy the original design standard value, or selected as detective products when each product does not satisfy any standard value according to measured characteristic values by measuring characteristic values of each inputted product in a test process in plural production processes;
a statistical work calculation unit configured to calculate the average number of performance and a standard deviation in an arbitrary period by using the collected performance information;
a target achievement probability calculation unit configured to calculate a target achievement probability to a final target in production performance at present time in accordance with information obtained from the information collection unit and the statistical work calculation unit;
a production instruction change determination unit configured to fix the change of product mixes of all products, determining production instruction change by comparing the target achievement probability to the final target calculated in the target achievement probability calculation unit with a threshold set in advance, and repeating processing of changing the product mix until the target achievement probability becomes the threshold or more; and
a production instruction creation unit configured to create production instructions based on the product mix information fixed by the production instruction change determination unit and production plan information.
2. The production instruction system according to claim 1,
wherein a target achievement probability \u03b1 to the final target in the production performance at present time is represented by the following formula:
x
i
=
–
(
\u03bc
i
–
Q
)
\ue89e
(
R
–
t
)
R
–
Z
\ue8a0
(
1
–
\u03b1
)
\ue89e
\u03c3
\ue89e
R
–
t
R
and
wherein the above formula satisfies that, the difference between an input plan and production performance in a certain point \u201ct\u201d (0=<t=<R) during a certain production period R of a certain product \u201ci\u201d is Xi, the average of the production performance of the certain product \u201ci\u201d is \u03bc, the dispersion is \u03c3, and the completion requirement volume in the production period R is Q, and Z(1\u2212\u03b1) indicates a value of an inverse function of the cumulative distribution function in the normal distribution when the target achievement probability is \u03b1.
3. The production instruction system according to claim 2,
wherein the difference Xi between the input plan and the production performance in the point \u201ct\u201d of the production period R can be found by the following formula:
x
i
=
I
i
\xb7
(
R
–
t
)
R
–
C
i
,
t
and
wherein, in the above formula, the planned number of inputs of the product \u201ci\u201d per day is Ii, the production performance of the product \u201ci\u201d at the point \u201ct\u201d in the production period R is Ci,t.
4. The production instruction system according to claim 1,
wherein processing of changing a product mix Pi to P\u2032i until the target achievement probability becomes a threshold Thi or more can be found by the following formula:
P\u2032i=Pi(1+(Thi\u2212Xi)),
wherein the product mix Pi can be found by the following formula:
P
i
=
I
i
\u2211
k
=
1
n
\ue89e
I
k
and
wherein, in the above formula, the planned number of inputs of the product \u201ci\u201d per day is Ii, the number of products is \u201cn\u201d.
5. The production instruction system according to claim 1,
wherein the new number of inputs I\u2032i created by the production instruction creation unit can be found by the following formula:
I
i
\u2032
=
P
i
\u2032
\ue89e
\u2211
k
=
1
n
\ue89e
I
k
and
wherein, in the above, the planned number of inputs of the product \u201ci\u201d is Ii, the number of products is \u201cn\u201d.
6. A production instruction method which creates production instructions of a product in which a characteristic value of each product is liable to vary from a standard value aimed in design due to instability of production processes, comprising the steps of:
collecting performance information of results selected as a product in accordance with design when each product satisfies an original design standard value, selected as other products having different standard values when each product does not satisfy the original design standard value, or selected as detective products when each product does not satisfy any standard value according to measured characteristic values by measuring characteristic values of each inputted product in a test process in plural production processes;
calculating the average number of performance and a standard deviation in an arbitrary period by using the collected performance information;
calculating a target achievement probability to a final target in production performance at present time in accordance with information obtained from the information collection step and the statistical work calculation step;
fixing the change of product mixes of all products, determining production instruction change by comparing the target achievement probability to the final target calculated in the target achievement probability calculation step with a threshold set in advance, and repeating processing of changing the product mix until the target achievement probability becomes the threshold or more; and
creating production instructions based on the product mix information fixed by the production instruction change determination step and production plan information.
7. The production instruction method according to claim 6,
wherein a target achievement probability \u03b1 to the final target in the production performance at present time is represented by the following formula:
x
i
=
–
(
\u03bc
i
–
Q
)
\ue89e
(
R
–
t
)
R
–
Z
\ue8a0
(
1
–
\u03b1
)
\ue89e
\u03c3
\ue89e
R
–
t
R
and
wherein the above formula satisfies that, the difference between an input plan and production performance in a certain point \u201ct\u201d (0=<t=<R) during a certain production period R of a certain product \u201ci\u201d is Xi, the average of the production performance of the certain product \u201ci\u201d is \u03bc, the dispersion is \u03c3, and the completion requirement volume in the production period R is Q, and Z(1\u2212\u03b1) indicates a value of an inverse function of the cumulative distribution function in the normal distribution when the target achievement probability is \u03b1.
8. The production instruction method according to claim 6,
wherein the difference Xi between the input plan and the production performance in the point \u201ct\u201d of the production period R can be found by the following formula:
x
i
=
I
i
\xb7
(
R
–
t
)
R
–
C
i
,
t
and
wherein, in the above formula, the planned number of inputs of the product \u201ci\u201d per day is Ii, the production performance at the point \u201ct\u201d in the production period R of the product \u201ci\u201d is Ci,t.
9. The production instruction method according to claim 6,
wherein processing of changing a product mix Pi to P\u2032i until the target achievement probability becomes a threshold Thi or more can be found by the following formula:
P\u2032i=Pi(1+(Thi\u2212Xi)),
wherein the product mix Pi can be found by the following formula:
P
i
=
I
i
\u2211
k
=
1
n
\ue89e
I
k
and
wherein, in the above formula, the planned number of inputs of the product \u201ci\u201d per day is Ii, the number of products is \u201cn\u201d.
10. The production instruction method according to claim 6,
wherein the new number of inputs I\u2032i created by the production instruction creation step can be found by the following formula:
I
i
\u2032
=
P
i
\u2032
\ue89e
\u2211
k
=
1
n
\ue89e
I
k
and
wherein, in the above, the planned number of inputs of the product \u201ci\u201d is Ii, the number of products is \u201cn\u201d.