The Internet of Things (IoT) and Cyber-Physical Systems (CPS) are the backbones of
Industry 4.0, where data quality is crucial for decision support. Data quality in these systems …

Abstract Machine learning (ML) has recently enabled many modeling tasks in design,
manufacturing, and condition monitoring due to its unparalleled learning ability using …

In this paper the idea of Self-Optimizing Machining Systems (SOMS) is introduced and
discussed. Against the background of Industry 4.0, here the focus is the technological level …

Advanced analytics are fundamental to transform large manufacturing data into resourceful
knowledge for various purposes. In its very nature, such “industrial big data” can relay its …

Purpose This study proposes a machine learning framework to predict customer complaints
from production line tests in an automotive company's lot-release process, enhancing …

This paper details the selection of machine learning models for predicting the effectiveness
of a heat pipe system in a concentric tube exchanger. Heat exchanger experiments with …

In context of the fourth industrial revolution (industry 4.0), the industrial big data is subject to
grow rapidly to respond the agile industrial computing and manufacturing technologies. This …

The adoption of machine learning (ML) in organizations is characterized by the use of
multiple ML software components. When building ML systems out of these software …

Each country needs to monitor progress on their Sustainable Development Goals (SDGs) to
develop strategies that meet the expectations of the United Nations. Data envelope analysis …

Implementing machine learning technologies in manufacturing environment relies heavily
on human expertise in terms of domain and machine learning knowledge. Yet, the required …