Master Assignment
Sensor data Mining for quality assurance OPPORTUNITIES AT eMagiz
Type: Master CS/BIT
Period: TBD
Location: 1. University of Twente and 2. Product Development Team eMagiz Enschede
Student: (Unassigned)
If you are interested please contact :
Background:
This project is about investigating the opportunities sensor data mining can provide to customers of an Enterprise iPaaS supplier, in this case eMagiz. Founded in 2011, eMagiz is a software development company constantly extending their Enterprise iPaaS with innovative features. The product development team is located in Enschede, nearby the University of Twente.
Assignment:
Data mining on sensor data from IoT devices is still fairly new for most manufacturing and maintenance delivery companies. Most sensor data is raw and needs to be processed before useful information can be extracted. Making decisions based on sensor data requires a certain level of quality and the right timing. As an iPaaS supplier, eMagiz has plenty of IoT-related built-in connectivity possibilities and wants to research the options to process the data set, so customers can benefit in their manufacturing and maintenance processes. Many customers could potentially benefit from improving their quality assurance. Quality assurance (QA) aims at signaling and preventing defects in their processes. Their environments can benefit from proper analyses of available data to improve quality assurance. The presence of proper data is vital to enable AI technology to improve QA. In this project, the aim is to research the untapped potential.
This master project has been divided into three different parts:
- The first part of the assignment is focused on researching what already has been done with data mining on sensor data in general. For this, blogs, market research et cetera. It can be used. In the end, these findings will be substantiated and supplemented with findings found in the literature. This should lead to a well-defined overview of the current use of sensor data mining.
- Next, a sensor data mining roadmap for eMagiz will be worked out, containing ideas and opportunities for future research
- The student can choose one of these ideas and scope the additional research in this direction towards a prototype application, validating the potential benefits for eMagiz and their customers.
Profile of the student:
You need to have an interest in AI, Data & IOT as an application field and be willing to interact with stakeholders within the eMagiz organization and (potential) customers. Knowledge of machine learning and AI is not a hard requirement.