What is claimed is:
1. A power shut-off method for an injection molding machine, comprising the steps of:
determining, in response to turn off of a power switch, whether a present state of the injection molding machine is a previously-set confirmation-requiring state which requires a confirmation before power is shut off;
shutting off the power when the present state is not the confirmation-requiring state; and
displaying on a display a confirmation window for confirmation of power shut off, without shutting off the power, when the present state is the confirmation-requiring state, and shutting off the power in accordance with a shut-off operation performed on the basis of the confirmation window.
2. A power shut-off method for an injection molding machine according to claim 1, wherein the confirmation-requiring state is a lockup state of a mold clamping unit using a toggle link mechanism.
3. A power shut-off method for an injection molding machine according to claim 2, wherein the lockup state is determined on the basis of at least one of an instruction value within a controller and a detection value output from a sensor.
4. A power shut-off method for an injection molding machine according to claim 2, wherein when the present state is the confirmation-requiring state, information indicating that the present state is the confirmation-requiring state is displayed in a predetermined display section of the display.
5. A power shut-off method for an injection molding machine according to claim 1, wherein the confirmation-requiring state is a nozzle touch state of an injection unit.
6. A power shut-off method for an injection molding machine according to claim 5, wherein the nozzle touch state is determined on the basis of at least one of an instruction value within a controller and a detection value output from a sensor.
7. A power shut-off method for an injection molding machine according to claim 5, wherein when the present state is the confirmation-requiring state, information indicating that the present state is the confirmation-requiring state is displayed in a predetermined display section of the display.
8. A power shut-off method for an injection molding machine according to claim 1, wherein an OFF key for shutting off the power and a cancel key for canceling the power shut off are displayed within the confirmation window, and operations of the OFF key and the cancel key are detected by use of a touch panel.
9. A power shut-off method for an injection molding machine according to claim 1, wherein the confirmation window includes a message display area, and a message is displayed in the message display area.
10. A power shut-off method for an injection molding machine according to claim 1, wherein a determination at to whether an opened file is present is performed when the power is shut off, and when an opened file is present, file closing processing is performed in order to close the opened file.
11. A power shut-off method for an injection molding machine according to claim 1, wherein a determination at to whether data to be stored have been stored into a memory is performed when the power is shut off, and when the data have not yet been stored, write processing is performed in order to write the data into a nonvolatile memory.
12. A power shut-off method for an injection molding machine according to claim 1, wherein the power switch is independently provided on a side panel at a predetermined position.
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. An attribute extraction method executable by a machine operatively connected to an archival memory and a work memory, the archival memory storing documents, registration dates thereof and attributes thereof, said method comprising:
extracting, vis-a-vis a plurality of documents in the archival memory that have registration dates falling within a desired time period, feature words for each attribute value of corresponding attributes of the plurality of documents;
registering, into said work memory, said desired time period, and said extracted feature words for said each attribute value of the corresponding attributes of the plurality of documents;
determining, amongst the extracted feature words in said work memory, first feature words for which an attribute has a first attribute value and second feature words for which said attribute has a second attribute value;
calculating a similarity between said first feature words and said second feature words;
identifying, a single unit time as said desired time period in case of absence of successive unit time periods in which a value of similarity between said first feature words is greater than or equal to a threshold value and adjacent unit time period in which a value of similarity between said first feature words is greater than or equal to the threshold value;
judging, based on the step of the identifying, whether the similarity satisfies a condition;
and outputting said second attribute value when said similarity satisfies the condition.
2. The attribute extraction processing method according to claim 1, further comprising: identifying, amongst the first feature words in the work memory, successive unit time periods in which a value of similarity between said feature words is greater than or equal to a threshold.
3. The attribute extraction processing method according to claim 1, wherein said desired time period includes a beginning unit time period and a last unit time period, and said determining includes: identifying, amongst the extracted feature words in said work memory, third feature words for which said attribute has the first attribute value and which correspond to said beginning unit time period, fourth feature words for which said attribute has the second attribute value and which correspond to said beginning unit time period; calculating a first value of similarity between said third feature words and said fourth feature words; identifying, amongst the extracted feature words in said work memory, fifth feature words for which said attribute has the first attribute value and which correspond to said last unit time period, and sixth feature words for which said attribute has the second attribute value and which correspond to said last unit time period; calculating a second value similarity between said fifth feature words and said sixth feature words; and judging whether the first value of similarity and the second value of similarity are greater than or equal to a threshold value, respectively.
4. The attribute extraction processing method according to claim 1, wherein said judging includes: identifying, amongst the extracted feature words in from work contents storage section, seventh feature words for which said attribute has the first attribute value and which correspond to a first one of desired time periods and, eighth feature words for which said attribute has the second attribute value and which correspond to the first one of said desired time periods; calculating a third value of similarity between said seventh feature words and said eighth feature words; identifying, amongst the extracted feature words in said work memory, ninth feature words for which said attribute has the first attribute value and which correspond to a second one of said desired time periods, and tenth feature words for which said attribute has the second attribute value and which correspond to the second one of said desired time periods; calculating a fourth value similarity between said ninth feature words and said tenth feature words; and judging whether the third value of similarity and the fourth value of similarity are greater than or equal to a threshold value, respectively.
5. The attribute extraction processing method according to claim 1, wherein said judging includes: identifying, amongst the extracted feature words in said work memory, eleventh feature words for which said attribute has the first attribute value and which correspond to a first interval within a first one of desired time periods, and twelfth feature words for which said attribute has the second attribute value and which correspond to said first interval; calculating a fifth value of similarity between said eleventh feature words and said twelfth feature words; identifying, amongst the extracted feature words in said work memory, thirteenth feature words for which said attribute has the first attribute value and which correspond to a second time interval within a second one of said desired time periods, and fourteenth feature words for which said attribute has the second attribute value and which correspond to said second interval; calculating a sixth value of similarity between said thirteenth feature words and said fourteenth feature words; and judging whether the fifth value of similarity and the sixth value of similarity are greater than or equal to a threshold value, respectively.
6. A computer-readable recording medium comprising computer-executable instructions for performing a method, execution of which by a computer facilitates attribute extraction by a computer operatively connected to an archival memory and a work memory, the archival memory storing documents, registration dates thereof and attributes thereof, said method comprising:
extracting, vis-a-vis a plurality of documents in the archival memory that have registration dates falling within a desired time period, feature words for each attribute value of corresponding attributes of the plurality of documents;
registering into said work memory said desired time period, and said extracted feature words for said each attribute value of the corresponding attributes of the plurality of documents;
determining, amongst the extracted feature words in said work memory, first feature words for which an attribute has a first attribute value and second feature words for which said attribute has a second attribute value;
calculating a similarity between said first feature words and said second feature words;
identifying, a single unit time as said desired time period in case of absence of successive unit time periods in which a value of similarity between said first feature words is greater than or equal to a threshold value and adjacent unit time period in which a value of similarity between said first feature words is greater than or equal to the threshold value;
judging, based on the step of the identifying, whether the similarity satisfies a condition;
and outputting said second attribute value when said similarity satisfies the condition.
7. An attribute extraction processing apparatus comprising:
an archival memory to store documents, registration dates thereof and attributes thereof; a work memory;
a processor to do at least the following:
extract, vis-a-vis a plurality of documents in the archival memory that have registration dates falling within a desired time period, feature words for each attribute value of corresponding attributes of the plurality of documents;
register into said work memory said desired time period, and said extracted feature words for said each attribute value of the corresponding attributes of the plurality of documents;
determine, amongst the extracted feature words in said work memory, first feature words for which an attribute has a first attribute and value second feature words for which said attribute has a second attribute value;
calculate a similarity between said first feature words and said second feature words;
identify, a single unit time as said desired time period in case of absence of successive unit time periods in which a value of similarity between said first feature words is greater than or equal to a threshold value and adjacent unit time period in which a value of similarity between said first feature words is greater than or equal to the threshold value;
judging, based on the step of the identifying, whether the similarity satisfies a condition;
and output said second attribute value when said similarity satisfies the condition.