{"ID":3050169,"CreatedAt":"2026-06-04T02:13:16.786527022Z","UpdatedAt":"2026-06-06T08:26:15.225160212Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.04599","arxiv_id":"2606.04599","title":"Plan First, Judge Later, Run Better: A DMAIC-Inspired Agentic System for Industrial Anomaly Detection","abstract":"Large language model (LLM) agents have shown promise in automating complex data-analysis workflows, but their reliable deployment remains challenging in high-stakes industrial scenarios. Industrial anomaly detection (IAD) is essential for manufacturing quality, safety, and efficiency, yet existing LLM-based IAD agents mainly focus on execution while under-exploiting strategy formulation. Consequently, they struggle to handle heterogeneous modalities in a unified and cost-effective manner. Inspired by the DMAIC quality-management framework, we propose DMAIC-IAD (DMAIC-inspired Agentic Industrial Anomaly Detection), a \"Plan First, Judge Later\" multi-agent system that aligns LLM agents with structured industrial problem-solving. DMAIC-IAD distills heterogeneous references into standardized operating procedures (SOPs) before strategy generation, and introduces a pre-trained execution-free judge model to rank candidate strategies without costly runtime trials. Extensive experiments across four modalities show that DMAIC-IAD improves average detection performance over applicable agentic baselines by 37.76%.","short_abstract":"Large language model (LLM) agents have shown promise in automating complex data-analysis workflows, but their reliable deployment remains challenging in high-stakes industrial scenarios. Industrial anomaly detection (IAD) is essential for manufacturing quality, safety, and efficiency, yet existing LLM-based IAD agents...","url_abs":"https://arxiv.org/abs/2606.04599","url_pdf":"https://arxiv.org/pdf/2606.04599v1","authors":"[\"Yongzi Yu\",\"Ao Li\",\"Le Wang\",\"Ziyue Li\",\"Fugee Tsung\",\"Yuxuan Liang\",\"Man Li\"]","published":"2026-06-03T08:38:14Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.CE\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}