跳到正文
研踪PaperTrail

YOUR RESEARCH, IN SIGHT

让下一篇重要论文,不再错过。

覆盖计算机全学科,以 AI 为快捷入口。关注方向、作者和关键词,把发现变成持续的研究积累。

采集已暂停
正在读取账号与研究记录…

全站更新概况

+0新增论文
+0其中 AI 相关
+0已有论文修订
+0新增 AI 导读

arXiv 最近完成扫描:等待完成 · 全站最近入库:2026-11-02 00:39各信源进度 →

统计口径与数据新鲜度

统计 2026-11-03 07:15 — 2026-11-04 07:15(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:尚未完成最近发现新增版本:2026-11-02 00:39库内论文最新更新时间:2026-10-30 01:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

8,677 已收录论文7,675 AI 相关1,866 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。

找到 1 篇论文 · 按版本更新时间排序等待首次采集
新论文 · v1arXiv:2610.40239

Engineering process plants as code in the age of agentic AI

Artur M. Schweidtmann, Davy Demeyer

Agentic artificial intelligence (AI) could one day shorten process plant engineering from years to weeks. Today, however, plant information is scattered across documents and tools and must be carried between them by hand, so an AI agent placed into current workflows inherits the same silos. In this Comment, we argue for Plant-as-Code: defining the engineering of a plant as a version-controlled collection of machine-readable files that follow, where possible, existing standards such as DEXPI and IFC. On this foundation, Design-Ops extends DevOps principles to plant engineering, linking every engineering item to the information it derives from and replacing manual checking with automated tests. Agents can then coordinate routine work across disciplines while deterministic tools perform the calculations. Verification sets the pace: agents propose, tools check, and engineers review and authorize every change. We outline the risks of this shift and the research, industry and policy actions it requires.

尚无 AI 解读,展示原文摘要

cs.CE
arXiv ↗PDF ↗