In the context of Industry 4.0 (I 4.0), one of the most important aspects is data, followed by the
capital required to deploy advanced technologies. However, most Small and Medium …

The application of Industrial Data Science in context of connected Smart Products requires
modeling and structuring data for its design, development and use. Especially for Smart …

Technical innovations to improve production systems flexibility have been extensively
investigated and are already available to industrial practice. However, the production …

Maintenance is defined as the actions that allow machines and equipment to work for an
extended period of time by retaining and restoring equipment to its original state. In Industry …

The decade-long trend toward process automation and end-to-end machine connectivity
has fueled an enormous growth of data recorded in the manufacturing industry. Leveraging …

This paper presents a global approach for implementing Digital Predictive Maintenance
(DPM), based on the principles of the digital industry. The proposed approach is applicable …

The increasing global competition demands continuous optimization of products and
processes from companies in the process industry. Where conventional methods of Lean …

Data-driven analytical approaches such as machine learning bear great potential for
increasing productivity in industrial applications. The primary requirement for using those …

Industrial Data Analytics needs access to huge amounts of data, which is scattered across
different IT systems. As part of an integrated reference kit for Industrial Data Analytics, there …

Recycling of refrigerating appliances plays a major role in protecting the Earth's atmosphere
from ozone depletion and emissions of greenhouse gases. The performance of refrigerator …