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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65988
Volume:
10 |
7 |
Jul 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Department of Computer Science & Engineering
IET, SAGE University

Department of Computer Science & Engineering
IET, SAGE University
Large language model (LLM)-based multi-agent systems have demonstrated, in simulation, that they can negotiate production allocation, reason about disruptions, and coordinate shop-floor functions. What none of them yet offer is a principled answer to the question a plant manager will ask first: what stops an agent from doing something wrong to a physical machine? This paper proposes VeriMAS, a multi-agent framework whose defining structural commitment is that no agent proposal reaches equipment without passing an independent verification gate. The architecture comprises four role-specialized LLM agents grounded through retrieval-augmented generation over plant documentation; a verification layer combining digital twin simulation, a deterministic rule-based safety envelope, and calibrated risk scoring; a graduated escalation policy that routes uncertain proposals to a human oversight console with the agent's reasoning and the twin's counterfactual trace; and an execution layer confined to auditable connectors. We specify the decision workflow and escalation algorithm, discuss implementation with locally deployed open-weight models against latency and confidentiality constraints, and define a proposed evaluation methodology—simulation testbed, baselines, ablations, and metrics including unsafe-proposal interception rate—explicitly identified as future experimental work rather than reported results. The framework converts trust in shop-floor agents from an assumption into an architectural property, and each gate component yields a testable hypothesis about the cost and value of verification.
KEYWORDS
The multi-agent LLM literature has shown that language models can fill the roles classical manufacturing agents defined; it has not shown that plants can afford to let them. VeriMAS reframes the problem: autonomy is not a property of capable agents but of a system that can bound what capable agents are permitted to do. By making every agent output a proposal, every execution a verified event, and every uncertain case a human decision supported by simulation evidence, the framework converts trust from an assumption into an architecture—and, through its proposed evaluation, into a measurable one. If verification gates prove cheap relative to the failures they intercept, the path from simulated shopfloors to real ones becomes an engineering program rather than a leap of faith.
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Publication Date
7/10/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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