1 research outputs found
Data science on industrial data -- Today's challenges in brown field applications
Much research is done on data analytics and machine learning. In industrial
processes large amounts of data are available and many researchers are trying
to work with this data. In practical approaches one finds many pitfalls
restraining the application of modern technologies especially in brown field
applications. With this paper we want to show state of the art and what to
expect when working with stock machines in the field. A major focus in this
paper is on data collection which can be more cumbersome than most people might
expect. Also data quality for machine learning applications is a challenge once
leaving the laboratory. In this area one has to expect the lack of semantic
description of the data as well as very little ground truth being available for
training and verification of machine learning models. A last challenge is IT
security and passing data through firewalls