Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial
intelligence (AI) has empowered smart manufacturing and digital transformation. AI …

Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …

The mining industry contributes to the expansion of the global economy by generating vital
commodities. For continuous production, the industry relies significantly on machinery and …

Predictive maintenance of lithium-ion batteries has been one of the popular research
subjects in recent years. Lithium-ion batteries can be used as the energy supply for …

The Cross-Industry Standard Process for Data Mining (CRISP-DM) is a widely accepted
framework in production and manufacturing. This data-driven knowledge discovery …

Driven by ongoing migration for Industry 4.0, the increasing adoption of artificial intelligence,
big data analytics, cloud computing, Internet of Things, and robotics have empowered smart …

Featured Application The proposed robust health prognostics technique identifies outer race
bearing failures and predicts the remaining useful lifetimes of the bearings of electric motors …

Abstract Industry 4.0 encapsulates methods, technologies, and procedures that transform
data into informed decisions and added value in an industrial context. In this regard …

Anomaly detection is a frequently discussed topic in manufacturing. However, the issues of
anomaly detection are typically attributed to the manufacturing process or equipment itself …

In every business, the production of knowledge, coming from the process of effective
information, is recognized as a strategic asset and source of competitive advantage. In the …