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This is a record of a document published elsewhere, first published by the United States Patent and Trademark Office, as US-2026104682-A1, on 16 April 2026. OpenTechnical did not first disclose it. The identifier, hashes and timestamps below record what this library served and when, not when the material became public. View the original.

OT-2026-000000599

Controlling a manufacturing process using causal models

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Sensors, Controls & Machine Vision › Industrial Control
Original source
US-2026104682-A1, the United States Patent and Trademark Office, 16 April 2026
Document SHA-256
30103bf0ad280ca095536b0f300139d3c4e4dfcf3eef61c84a1e7d060ad1899d

Abstract

An example method includes selecting treatment assignments for operation of a system in an environment based on a causal model mapped to a probability distribution over possible treatment assignments, where the causal model measures causal relationships between the treatment assignments and a performance metric associated with the environment. The method further includes mapping causal effects between the treatment assignments and measures of uncertainty associated with the environment in the causal model to corresponding probabilities using probability matching. The method further includes determining the performance metric using the treatment assignments and corresponding dependent variables obtained from the environment in response to the treatment assignments. The method further includes adjusting, based on the performance metric, the causal model, and re-computing the adjusted causal model by computing overall causal effects based on the measures of uncertainty around the overall causal effects.

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OpenTechnical Publication OT-2026-000000599, “Controlling a manufacturing process using causal models,” published September 15, 2026 at 19:03:08 UTC, https://opentechnical.org/p/OT-2026-000000599.

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