1. A manufacturing instruction evaluation support system comprising:
a storage device that stores therein a parameter table storing manufacturing instruction parameters associated with product manufacturing, a manufacturing performance table storing manufacturing performance data in a manufacturing step operated in accordance with a manufacturing instruction parameter, and a multiple regression analysis program executing multiple regression analysis;
a data reading part that reads from the parameter table and the manufacturing performance table and stores into a memory, a manufacturing instruction parameter group and manufacturing performance data corresponding thereto;
a parameter sorting part that uses the manufacturing instruction parameter group in the memory as an explanatory variable and the manufacturing performance data as an objective variable to calculate a risk rate for each manufacturing instruction parameters configuring the manufacturing instruction parameter group and an average value of the calculated risk rates among the manufacturing instruction parameters with the multiple regression analysis program, the parameter sorting part identifying manufacturing instruction parameters having a risk rate no greater than the average value in the manufacturing instruction parameter group as available choices;
a parameter identifying part that calculates multiple correlation coefficients, a number of parameters, and a number of samples for the manufacturing instruction parameter group and the manufacturing instruction parameters of the available choices to calculate an explanatory variable selection reference value with the multiple regression analysis program based on the calculated multiple correlation coefficients, the number of parameters, and the number of samples, the parameter identifying part identifying the manufacturing instruction parameter group or the manufacturing instruction parameters of the available choices having a greater calculated explanatory variable selection reference value as an optimum parameter; and
a regression equation calculating part that calculates a regression equation when employing the optimum parameter with the multiple regression analysis program to display the regression equation on an output interface.
2. The manufacturing instruction evaluation support system of claim 1, comprising:
a fixing instruction accepting part that accepts through an input interface a specification for a fixed parameter having a parameter value fixed and a fixed parameter value among the manufacturing instruction parameters stored in the parameter table to replace a parameter value of the fixed parameter in the parameter table with the fixed parameter value.
3. The manufacturing instruction evaluation support system of claim 2, comprising:
a new acquisition instructing part that monitors process results of the risk rate calculation by the parameter selecting part, the multiple correlation coefficient calculation and the explanatory variable selection reference value calculation by the parameter identifying part, and the regression equation calculation by the regression equation calculating part to detect an event that no calculation result is obtained, the new acquisition instructing part giving an instruction to the data reading part for reading out, from the parameter table and the manufacturing performance table, a new manufacturing instruction parameter group whose parameters are in common but parameter values different from the manufacturing instruction parameter group initially read out, and a manufacturing performance data corresponding to the new manufacturing instruction parameter group.
4. The manufacturing instruction evaluation support system of claim 3, comprising:
a communication device that communicates with another apparatus on a network, the new acquisition instructing part detecting an event that the calculation result is not obtained, generating a new manufacturing instruction parameter group whose parameters are in common with the manufacturing instruction parameter group initially read out, and the parameter values are increased or decreased by a predetermined amount to transmit data of the new manufacturing instruction parameter group to a manufacturing apparatus through the communicating device; and
a new manufacturing performance acquiring part that communicates with the manufacturing apparatus through the communicating device to receive manufacturing performance data corresponding to the new manufacturing instruction parameter group, to thereby store the manufacturing performance data in the manufacturing performance table in a manner correlated with the new manufacturing instruction parameter group.
5. The manufacturing instruction evaluation support system of claim 4, wherein
the new acquisition instructing part calculates a parameter value that achieves predetermined reference of manufacturing performance in the regression equation for each manufacturing instruction parameter included in the regression equation to transmit the calculated parameter value of each manufacturing instruction parameter to the manufacturing apparatus through the communicating device, the system comprising:
a new manufacturing performance acquiring part that communicates with the manufacturing apparatus through the communicating device to receive manufacturing performance data corresponding to the parameter values of the manufacturing instruction parameters, to thereby store the manufacturing performance data in the manufacturing performance table in a manner correlated with the manufacturing instruction parameters included in the regression equation.
6. The manufacturing instruction evaluation support system of claim 5, wherein
the parameter sorting part detects that there are a plurality of manufacturing instruction parameters identified as the available choices and repeatedly executes the risk rate calculation for each of the manufacturing instruction parameters configuring the available choices, calculation of the average risk rate value, and a process of identifying manufacturing instruction parameters having risk rates no greater than the average value in the available choices as new available choices until the new available choices are defined as one manufacturing instruction parameter to identify a plurality of available choices, and
the parameter identifying part calculates multiple correlation coefficients, a number of parameters, and a number of samples for a manufacturing instruction parameter group and the manufacturing instruction parameters of the plurality of the available choices to calculate an explanatory variable selection reference value with the multiple regression analysis program based on the calculated multiple correlation coefficients, the numbers of parameters, and the numbers of samples and identifies the manufacturing instruction parameter group or the manufacturing instruction parameters of the plurality of the available choices having the greater calculated explanatory variable selection reference value as optimum parameters.
7. A manufacturing instruction evaluation support method executed by a computer having a storage device that stores therein a parameter table storing manufacturing instruction parameters associated with product manufacturing, a manufacturing performance table storing manufacturing performance data in a manufacturing process operated in accordance with a manufacturing instruction parameter, and a multiple regression analysis program executing multiple regression analysis, the method comprising the steps of;
reading from the parameter table and the manufacturing performance table and storing into a memory, a manufacturing instruction parameter group and manufacturing performance data corresponding thereto;
using the manufacturing instruction parameter group of the memory as an explanatory variable and the manufacturing performance data as an objective variable to calculate a risk rate for each manufacturing instruction parameter configuring the manufacturing instruction parameter group and an average value of the calculated risk rates among the manufacturing instruction parameters with the multiple regression analysis program and identifying manufacturing instruction parameters having risk rates no greater than the average value in the manufacturing instruction parameter group as available choices;
calculating multiple correlation coefficients, a number of parameters, and a number of samples for the manufacturing instruction parameter group and the manufacturing instruction parameters of the available choices to calculate an explanatory variable selection reference value with the multiple regression analysis program based on the calculated multiple correlation coefficients, the number of parameters, and the number of samples and identifying the manufacturing instruction parameter group or the manufacturing instruction parameters of the available choices having a greater calculated explanatory variable selection reference value as an optimum parameter; and
calculating a regression equation when employing the optimum parameter with the multiple regression analysis program to display the regression equation on an output interface.
8. A manufacturing instruction evaluation support program operable to cause a computer having a storage device that stores therein a parameter table storing manufacturing instruction parameters associated with product manufacturing, a manufacturing performance table storing manufacturing performance data in a manufacturing process operated in accordance with a manufacturing instruction parameter, and a multiple regression analysis program executing multiple regression analysis to execute the steps of:
reading from the parameter table and the manufacturing performance table and storing into a memory, a manufacturing instruction parameter group and manufacturing performance data corresponding to the group;
using the manufacturing instruction parameter group in the memory as an explanatory variable and the manufacturing performance data as an objective variable to calculate a risk rate for each of the manufacturing instruction parameters configuring the manufacturing instruction parameter group and an average value of the calculated risk rates among the manufacturing instruction parameters with the multiple regression analysis program and identifying manufacturing instruction parameters having risk rates no greater than the average value in the manufacturing instruction parameter group as available choices;
calculating multiple correlation coefficients, a number of parameters, and a number of samples for the manufacturing instruction parameter group and the manufacturing instruction parameters of the available choices to calculate an explanatory variable selection reference value with the multiple regression analysis program based on the calculated multiple correlation coefficients, the number of parameters, and the number of samples and identifying the manufacturing instruction parameter group or the manufacturing instruction parameters of the available choices having a greater calculated explanatory variable selection reference value as an optimum parameter; and
calculating a regression equation when employing the optimum parameter with the multiple regression analysis program to display the regression equation on an output interface.
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 digital protractor for measuring an angular displacement from a reference surface, said protractor comprising:
a substantially congruent pair of pivotally interconnected upper and lower arms, which arms are superposable upon one another, each arm having at lease one engagement edge extending longitudinally of said arm, one of said arms being engagable along an engagement edge thereof with the reference surface, at least one engagement edge of each arm carrying a magnetic element;
an electronic sensor secured to one of said arms; and
a digital readout device secured to the other said arm for operatively cooperating with said electronic sensor to measure and display the angular displacement from the arm engaging the reference surface to the other arm.
2. The device of claim 1 in which said digital readout includes a calibration switch that is engaged for said readout to display an angular displacement of zero degrees regardless of the angular displacement between said arms.
3. The device of claim 1 in which said arms comprise respective extruded components.
4. The device of claim 1 in which each arm has a pair of substantially parallel engagement edges and each engagement edge carries a magnetic element for adhering to a magnetically attracted material carried by the reference surface.
5. The device of claim 4 in which each engagement edge includes a longitudinal channel for receiving a respective magnetic element.
6. The device of claim 5 in which said magnetic element is confined within said channel such that said magnetic element does not extend beyond said engagement edge.
7. The device of claim 6 in which said channel extends longitudinally of said engagement edge.
8. The device of claim 1 in which said sensor includes a capacitive sensor disk fixed to said lower arm and said readout includes a signal generating circuit attached to said upper arm for operatively cooperating with said capacitive sensor to measure an angular displacement between said arms and a display device connected to said signal generating circuit for displaying the measured angular displacement between said arms.
9. The device of claim 1 further including a locking apparatus for holding said arms together to maintain a selected angular displacement between said arms.
10. The device of claim 6 in which said upper arm includes a longitudinal central channel for accommodating said signal generating circuit therein.
11. The device of claim 6 in which said arms are connected by a pivot pin and said annular disk is disposed about said pin.
12. The device of claim 1 in which said upper and lower arms comprise a respective pair of superposable plates interconnected by a pivot pin that extends transversely through superposed, generally flat surfaces of said plates.
13. The device of claim 6 in which said annular disk and said signal generating circuit are enclosed by a housing from which said display is exposed.
14. The device of claim 12 in which said plates are pivotable relative to one another in a generally laminar manner with a substantially flat bottom surface of said upper arm being substantially parallel to an opposing flat top surface of said lower arm.
15. A digital protractor for measuring an angular displacement from a reference surface to a second surface, each of which surfaces includes a magnetically attracted material, said protractor comprising:
a pair of pivotally interconnected upper and lower arms, which arms are superposable upon and pivotable in a generally laminar manner relative to one another, each arm having a pair of substantially parallel engagement edges extending longitudinally of said arm, one of said arms being engagable with the reference surface along a selected engagement edge of said arm, the other said arm being engagable with the second surface along a selected engagement edge of said other arm, at least one said engagement edge in each said arm including a channel for receiving a respective said magnetic element, which magnetic element is confined within said channel such that said magnetic element does not extend laterally beyond said engagement edge;
an electronic sensor secured to said lower arm; and
a digital readout device secured to said upper arm for operatively cooperating with said electronic sensor to measure and display the angular displacement from said arm engaging the reference surface to the other said arm engaging the second surface, a respective pair of said magnetic elements for holding the angular displacement set between the arms and the resulting measurement thereof.
16. The device of claim 15 in which each said engagement edge of each said arm extends to a distal end of said arm.
17. The device of claim 18 in which each said channel extends longitudinally through a respective said engagement edge to said distal end of said arm, and wherein a respective said magnetic element extends through said channel to said distal end of said arm.
18. A digital protractor for measuring an angular displacement from a reference surface, which reference surface carries a magnetically attracted material, said protractor comprising:
a pair of pivotally interconnected upper and lower arms, which arms are superposable upon one another, each arm having a pair of substantially parallel engagement edges extending longitudinally of said arm, one of said arms being engagable with the reference surface along a selected one of said engagement edges of said arm, at lease one said engagement edge of each said arm having a channel formed therein for receiving a respective magnetic element that is confined within and does not protrude laterally from said channel, which magnetic element is for adhering to the magnetically attracted material carried by the reference surface when the engagement edge carrying said magnetic element is engaged with the reference surface;
an electronic sensor secured to said lower arm; and
a digital readout device secured to said upper arm for operatively cooperating with said electronic sensor to measure and display the angular displacement from the arm engaging the reference surface to the other arm.
19. The device of claim ______ in which each said engagement edge includes a pair of substantially parallel ridges formed respectively above and below said channel and said magnetic element carried therein for selectively directly engaging the reference surface such that said magnetic element adheres to the magnetically attracted material carried by the reference element.
20. The device of claim 18 in which each channel extends longitudinally in a respective engagement edge.