Method for improving a manufacturing process

Abstract

A factorial experiment is conducted on a manufacturing process to generate a response matrix. The responses are used to calculate individual contrasts in a document as well as replicates effects. The contrast sums are also calculated and displayed in the document. The largest of the contrast sums are identified, and effects associated with those contrast sums are tested for significance using an end count method. The information from the process transformed into “significant effects” information is used to adjust process variables to improve the manufacturing process by avoiding the effect or imparting it to a measurable response of the process.

1 . A method for improving a manufacturing process wherein there are a plurality of process variables and a value of a measurable response of the manufacturing process is indicative of an improvement to the process, the method comprising:
 conducting a full factorial experiment by setting a plurality of the process variables at a plurality of settings in a plurality of combinations of settings and receiving at least one measurement of the response of the process for each combination of level settings;   calculating individual contrasts for each process variable and each interaction among the process variables using the received responses of the full factorial experiment and displaying the individual contrasts for each variable and each interaction;   verifying that both variables of an interaction contrast must be set at the levels of the interaction to impart an effect substantially equal to the effect of the interaction by evaluating the variance of the contrasts displayed;   setting the process variables as a function of the effect of the verification; and   operating the manufacturing process.   
   
   
       2 . A computer-implemented method of improving a manufacturing process wherein a target is determined for a measurable response, the target being indicative of an improvement in the process, the method comprising:
 conducting a full factorial experiment with at least two process variables being adjusted between at least two level settings with output responses being measurements of the response for which the target is determined;   receiving the responses of the full factorial experiment and using the responses to calculate individual contrasts for each process variable and each interaction among the process variables and displaying each of the contrasts in a document;   adding the individual contrasts of each process variable and each interaction to generate separate contrast sums;   selecting at least one of the contrast sums when it is greater than at least one of the other contrast sums by a predefined factor; and   adjusting the level settings of the process variables as a function of an estimated effect associated with the selected contrast sum.   
   
   
       3 . A computer readable medium for instructing a computer to perform a method for improving a manufacturing process, comprising:
 receiving level settings and responses for a factorial experiment;   calculating individual contrasts for each process variable and each interaction among the process variables; and   testing the significance of effects associated with the contrasts, wherein when an effect is found to be significant and is an interaction effect, it is removed before testing the significance of another affect, the removal being done to achieve the smallest remaining estimates for the lower order effects.