Explainable AI-Supported Cyber-Physical Collaboration for Sustainable Manufacturing in Industry 5.0

In this study, we present an innovative approach to the sustainable manufacturing of industrial parts using an explainable artificial intelligence (XAI)- based cyber-physical collaboration system for Industry 5.0. Current cyber-physical human systems (CPHSs) have been found to integrate AI only to a limited extent and often lack explainability. Consequently, there is a need to improve their scalability and flexibility, in keeping with the tenets of Industry 5.0: resilience, long-term viability, and human-centric…

By the Truvace deskSeptember 3, 20261 min read1 sourcePeer-reviewedTRV-2026-0970· cite & verify

In brief

To address these shortcomings, we introduce an architecture that integrates deep learning and explainable AI into the Cyber-Physical System (CPS) ecosystem to enable smart, explainable decision-making. Audio signals undergo spectral transformation to generate spectrogram images, which are then processed by a convolutional neural network (CNN) for spatial feature extraction and a transformer encoder for temporal features.

Main points

In this study, we present an innovative approach to the sustainable manufacturing of industrial parts using an explainable artificial intelligence (XAI)- based cyber-physical collaboration system for Industry 5.0.
Current cyber-physical human systems (CPHSs) have been found to integrate AI only to a limited extent and often lack explainability.
Consequently, there is a need to improve their scalability and flexibility, in keeping with the tenets of Industry 5.0: resilience, long-term viability, and human-centricity.

The gain

Explainable AI-Supported Cyber-Physical Collaboration for Sustainable Manufacturing in Industry 5.0: Experimental findings show that the proposed CNN-Transformer architecture achieves 98.5% accuracy and outperforms existing CPHS systems while maintaining low latency.

The rundown

Consequently, there is a need to improve their scalability and flexibility, in keeping with the tenets of Industry 5.0: resilience, long-term viability, and human-centricity. To address these shortcomings, we introduce an architecture that integrates deep learning and explainable AI into the Cyber-Physical System (CPS) ecosystem to enable smart, explainable decision-making.