Artificial intelligence (AI) is a driving force behind Industry 4.0 in manufacturing. Specifically,
machine learning has been applied to all parts of the manufacturing process: from product …

The manufacturing process strongly affects the electrochemical properties and performance
of lithium-ion batteries. In particular, the flow of electrode slurry during the coating process is …

Industry 4.0 has transformed manufacturing with real-time plant data collection across
operations and effective analysis is crucial to unlock the full potential of Internet-of-Things …

Estimating the cycle time ranges of jobs is a critical task in a factory. this study proposes a
fuzzy collaborative intelligence (FCI) approach to improve the precision of cycle time range …

Smart manufacturing processes, building upon machine learning (ML) models could
potentially reduce the pre-production testing and validation time for new processes. Beyond …

In this paper, we discuss the trends and challenges of the integration of Artificial Intelligence
(AI) methods in the workplace. An important aspect towards creating positive AI futures in the …

Data-driven artificial intelligence models require explainability in intelligent manufacturing to
streamline adoption and trust in modern industry. However, recently developed explainable …

Explainable Artificial Intelligence (XAI) has gained significant attention as a means to
address the transparency and interpretability challenges posed by black box AI models. In …

In recent years there is a surge of interest in the interpretability and explainability of AI
systems, which is largely motivated by the need for ensuring the transparency and …

In the realm of manufacturing processes, equipment failures can result in substantial
financial losses and pose significant safety hazards. Consequently, prior research has …