Translating Multimodal AI into Real-World Inspection: TEMAI Evaluation Framework and Pathways for Implementation
Journal:
arXiv
Published Date:
Mar 31, 2025
Abstract
This paper introduces the Translational Evaluation of Multimodal AI for
Inspection (TEMAI) framework, bridging multimodal AI capabilities with
industrial inspection implementation. Adapting translational research
principles from healthcare to industrial contexts, TEMAI establishes three core
dimensions: Capability (technical feasibility), Adoption (organizational
readiness), and Utility (value realization). The framework demonstrates that
technical capability alone yields limited value without corresponding adoption
mechanisms. TEMAI incorporates specialized metrics including the Value Density
Coefficient and structured implementation pathways. Empirical validation
through retail and photovoltaic inspection implementations revealed significant
differences in value realization patterns despite similar capability reduction
rates, confirming the framework's effectiveness across diverse industrial
sectors while highlighting the importance of industry-specific adaptation
strategies.
