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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-2026104693-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-2026-000000425

Systems, apparatuses, methods, and computer program products for scalable and improved asset performance and reliability predictions

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Sensors, Controls & Machine Vision › Industrial Control
Original source
US-2026104693-A1, the United States Patent and Trademark Office, 16 April 2026
Document SHA-256
cafa037a7a1bdd4ab12bb7904221a88b6f5dbca3d9ce3f4e495ee5f24209866f

Abstract

Embodiments of the present disclosure relate to asset monitoring. A plurality of model operations associated with a plurality of assets may be identified. A plurality of model dependency graphs may be generated by applying the plurality of model operations to a graph machine learning model. One or more asset clusters may be generated by applying the plurality of model dependency graphs to a clustering machine learning model. One or more processing groups may be generated based on one or more grouping parameters, each processing group may comprise at least one asset cluster of the one or more asset clusters. Each of the one or more processing groups may be assigned to different processing sub streams of a plurality of processing sub streams such that each processing sub stream is associated with a processing group of the one or more processing groups to facilitate parallel processing.

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OpenTechnical Publication OT-2026-000000425, “Systems, apparatuses, methods, and computer program products for scalable and improved asset performance and reliability predictions,” published September 15, 2026 at 19:02:52 UTC, https://opentechnical.org/p/OT-2026-000000425.

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