TITLE: Dataset for anomalies detection in 3D printing 

ABSTRACT: Nowadays, Internet of Things plays a significant role in many domains.
Especially, Industry 4.0 is making a great usage of concepts like smart sensors
and big data analysis. IoT devices are commonly used to monitor industry
machines and detect anomalies in their work. In this paper we present and
describe a set of data streams coming from working 3D printer. Among others, it
contains accelerometer data of printer head, intrusion power and temperatures
of the printer elements. In order to gain data we lead to several printing
malfunctions applied to the 3D model. Resulting dataset can therefore be used
for anomalies detection research.
Nowadays, Internet of Things plays a significant role in many domains.
Especially, Industry 4.0 is making a great usage of concepts like smart sensors
and big data analysis. IoT devices are commonly used to monitor industry
machines and detect anomalies in their work. In this paper we present and
describe a set of data streams coming from working 3D printer. Among others, it
contains accelerometer data of printer head, intrusion power and temperatures
of the printer elements. In order to gain data we lead to several printing
malfunctions applied to the 3D model. Resulting dataset can therefore be used
for anomalies detection research.
Dataset for anomalies detection in 3D printing
http://arxiv.org/abs/2004.08817v1