Integration of multimodal data and explainable artificial intelligence for root cause analysis in manufacturing processes

2024/01/01 by Matteo Calaon, Tingting Chen, Guido Tosello · 1 citation
Engineering · Computer Science · Business, Management and Accounting · #Fault Detection and Control Systems #Explainable Artificial Intelligence (XAI) #Big Data and Business Intelligence

paper · doi:10.1016/j.cirp.2024.04.014

Abstract

Nowadays, the growing complexities of manufacturing processes and systems make it difficult to identify the root causes of critical deviations in performance. Conventional methods often fall short in capturing the multifaceted nature of these challenges, despite a wealth of diverse untapped manufacturing data. To harness the full potential of diverse data sets and transform them into a valuable asset to guide root cause exploration, this paper presents an innovative approach that combines multimodal predictive analysis and explainable artificial intelligence (XAI) to uncover insights into system dynamics. This work contributes to a paradigm shift in industrial decision-making regarding manufacturing diagnostics.

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• Multimodal Integration in Health Care: Development With Applications in Disease Management. [europepmc]

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