https://mituan-ai.github.io/tags/industrial-ai/Industrial AIHugoBlox Kit (https://hugoblox.com)en-usTue, 07 Jul 2026 11:29:45 +0000https://mituan-ai.github.io/media/logo_hu_c35fdb5ffffc5275.pnghttps://mituan-ai.github.io/tags/industrial-ai/https://mituan-ai.github.io/publications/zong-2026-roam/Tue, 07 Jul 2026 11:29:45 +0000https://mituan-ai.github.io/publications/zong-2026-roam/https://mituan-ai.github.io/projects/thickening-dewatering-decision-support/Sun, 01 Mar 2026 00:00:00 +0000https://mituan-ai.github.io/projects/thickening-dewatering-decision-support/<p>This project developed an operational decision-support workflow for a thickening–dewatering line. It joins field measurements, condition recognition, a process digital twin, and an LLM layer with retrieval, Text2SQL, and controlled tool use. The public description omits the industrial partner, site, and operating values.</p> <p> <figure > <div class="flex justify-center "> <div class="w-full" ><img alt="Anonymous thickening–dewatering system architecture" src="https://mituan-ai.github.io/projects/thickening-dewatering-decision-support/system.svg" loading="lazy" data-zoomable /></div> </div></figure> </p> <h2 id="system-scope">System scope</h2> <ul> <li>process-data access and online condition recognition;</li> <li>a digital representation of the thickening–dewatering equipment;</li> <li>retrieval over technical documents and structured production data;</li> <li>tool-mediated analysis with the operator retained in the decision loop.</li> </ul> <h2 id="research-connection">Research connection</h2> <p>The project supplied an application setting for work on specialist-model adaptation under operating shifts. The associated preprint presents the method and evaluation protocol without exposing production identifiers.</p>