  As systems in smart manufacturing become increasingly complex, producing an
abundance of data, the potential for production failures becomes increasingly
more likely. There arises the need to minimize or eradicate production
failures, one of which is by means of anomaly detection. However, with the
deployment of anomaly detection systems, there are many aspects to be
considered. In this paper, an overview of the components, benefits, challenges,
methods, and open problems of anomaly detection in smart manufacturing and
robotic finishing systems are discussed.
