Paper

Skill-Constrained Model Predictive Control for Resilient Manufacturing Supply Chains

Unreadunread

AI summary

arXiv:2606. 17269v1 Announce Type: new Abstract: In skill-constrained production-inventory systems, the qualified human capacity available tomorrow depends on training decisions made today: production requires certified workers, certifications decay unless maintained, and training consumes the same scarce worker hours that production needs now.

Reading status

Priority

About this paper

Authors: Carlos Eduardo Sanoja
Released: 2026-06-18 (21d ago)
Topic: Related to current project
Relation to my work: Read next because Skill-Constrained Model Predictive Control for Resilient Manufacturing Supply Chains overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: strong, class, under, eval, rate, control, chain, trained. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2606.17269

Ask Claude about this paper

Posts a comment with @claude so the runner spins up a Claude Code session scoped to Skill-Constrained Model Predictive Control for Resilient Manufacturing Supply Chains. Replies appear in the conversation below.

Comments

No comments yet.

Related records

No links yet.