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Optimization-assisted Six Sigma DMAIC/Evidence
Method evidence record

Optimization-assisted Six Sigma DMAIC

Optimization-assisted Six Sigma DMAIC embeds formal mathematical optimization — response surface methods, metaheuristics, or multi-objective solvers — into the Improve phase of the DMAIC cycle. Rather than relying solely on engineering judgment or one-factor-at-a-time trials, the approach uses designed experiments to build a predictive model of the process and then applies an optimization algorithm to locate factor settings that best satisfy quality, cost, or multiple competing performance targets simultaneously.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Optimization-Assisted Six Sigma Define-Measure-Analyze-Improve-Control
Taxonomic method record · process-pipeline / experimental-design
  • Antony, J., & Banuelas, R. (2002). Key ingredients for the effective implementation of Six Sigma program. Measuring Business Excellence, 6(4), 20-27. · URL
  • Six Sigma. Wikipedia. · URL
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Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketDesign of experimentsmachine-suggested · Relational suggestion, not evidence.Used in the same domainResponse Surface Methodologymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Six Sigma DMAICmachine-suggested · Relational suggestion, not evidence.Same method familySix Sigma DMAICmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStatistical Process Controlmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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