Controlling multi-stage manufacturing process based on internet of things (iot) sensors and cognitive rule induction
US-2018292811-A1 · Oct 11, 2018 · US
US10928801B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10928801-B2 |
| Application number | US-201816184293-A |
| Country | US |
| Kind code | B2 |
| Filing date | Nov 8, 2018 |
| Priority date | Nov 8, 2018 |
| Publication date | Feb 23, 2021 |
| Grant date | Feb 23, 2021 |
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Techniques for qualifying for use in an overall manufacturing process items produced by a bulk manufacturing process that has a plurality of batch effects are presented. The techniques can include obtaining a collection of items produced by a bulk manufacturing process that has a plurality of batch effects; measuring a quantifiable property of a sample of items from the collection of items; developing a linear mixed model for the quantifiable property based on the measuring; determining a statistical process control standard deviation for the collection of items based on the linear mixed model; computing a statistical process control parameter from the statistical process control standard deviation; determining that at least a portion of the collection of items conform to the statistical process control parameter; accepting at least a portion of the collection of items; and using at least a portion of the collection of items in the overall manufacturing process.
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What is claimed is: 1. A method of qualifying for use in an overall manufacturing process items produced by a bulk manufacturing process that has a plurality of batch effects, the method comprising: obtaining a collection of items produced by the bulk manufacturing process that has the plurality of batch effects; measuring a quantifiable property of a sample of items from the collection of items; developing a linear mixed model for the quantifiable property based on the measuring; determining a statistical process control standard deviation for the collection of items based on the linear mixed model; computing a statistical process control parameter from the statistical process control standard deviation; determining that at least a portion of the collection of items conform to the statistical process control parameter; accepting at least the portion of the collection of items; and using at least the portion of the collection of items in the overall manufacturing process. 2. The method of claim 1 , wherein the collection of items comprise a plurality of forged metal parts. 3. The method of claim 2 , wherein the plurality of batch effects comprise at least a heat treatment batch effect and a mill heat batch effect. 4. The method of claim 1 , wherein the statistical process control parameter comprises a process capability index requirement. 5. The method of claim 4 , further comprising implementing a statistical process control reduced sampling plan for at least one future collection of items produced by the bulk manufacturing process that has the plurality of batch effects. 6. The method of claim 4 , wherein the process capability index requirement is of the form C p k * = n - 1 n 1 3 n * - 1 t n * - 1 , C 0 n * , 1 - α , where n is a total sample size, n * = ( ∑ i = 1 B ( ∑ i = 1 B ) + ∑ j ∈ J ( n j n ) 2 + 1 n ∑ i = 1 B + ) - 1 , B represents a number of batch effects, J represents a set of possible batch effect level combinations from all batch effects, represents a standard deviation for batch effect i, represents a standard deviation representing a within-batch batch variation, n j represents a sample size of items in batch effect level combination j, and t n*−1,C 0 √{square root over (n*)},1−α represents a (1−α) quantile of a non-central t-distribution with n* degrees of freedom and non-centrality parameter C 0 √{square root over (n*)}, where α is a Type I error rate associated with a confidence level. 7. The method o
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