PhD session

• Lukas Meitz, M.Sc.
• Philipp von Rußdorf, M.Sc. (cancelled)
• Elisabeth Mess, M.A. (sostituted)
• Fabian Kopf (cancelled)
• Adrian Petter

Lukas Meitz, M.Sc. Informatik, Augsburg University of Applied Sciences Distributed Systems
Group

• PhD in progress, collaboration with Augsburg University Chair of Organic Computing
• Short Project Description:
  • Predictive Analytics Solutions for Professional Cooking Machines (PAS4PCM)
  • Three years overall, 22 months in, working together with Rational AG in Landsberg
  • Keywords: Predictive Maintenance, Data Science, Machine Learning, Industrial Application
  • Goal of the Project: Predictive Maintenance (PdM) aims to extract relevant maintenance information from machine data collected via the Internet of Things infrastructure. Using suitable algorithms, anomalies, and trends can be detected in recorded data, which in turn can be helpful in forecasting and scheduling proper maintenance actions just in time. The project aim is to implement selected PdM methods for the machines of Rational AG, who provide expert insights and recorded machine data for research of real-world scenarios.

Philipp von Rußdorf, M.Sc., computer science, Augsburg University of Applied Sciences,
THA_comp (Composites for Lightweight Structures) (cancelled)

• PhD in preparation
• Project description:
  • Project Name: tbd
  • Duration: not specified, partner: Trying to get Hufschmied Zerspannungssysteme on board
  • Keywords: Machining, CMCs, acoustic emissions, condition monitoring
  • Goal: Using a dynamometer to measure cutting forces Is a well-established way to determine the wear of a tool during machining. Dynamometers have one significant drawback: They are relatively expensive. Sensors for acoustic emissions are far less expensive and have been used to determine tool wear under very controlled conditions (same tool, exact positioning and material of the workpiece, etc.). The project aims to train a model capable of determining tool wear despite parameter changes.

Elisabeth Mess, M.A., User-Centered Systems & Data, Augsburg University of Applied
Sciences Institut for Agile Software Development (sostituted)

• PhD in progress, collaboration with Augsburg University Chair of IT Infrastructures for
  Translational Medical Research
• Short description:
  • Digitalization of Care Transition Records in Healthcare (Joint Research Project CARE REGIO, Subproject DigiPÜB)
  • Four years overall, 34 months in, working together with one hospital and two care facilities in Augsburg
  • Process optimization, web application development and design, machine learning, interoperability
  • Goal: Challenges often arise in transferring crucial nursing data, causing delays that burden nursing staff and patients. Project DigiPÜB aims to streamline and digitize care transition records and their transfer, improving the overall data exchange among healthcare stakeholders. Augsburg University of Applied Sciences collaborates closely with Augsburg University Hospital.

Fabian Kopf, HSA_ias (cancelled)

• No PhD planned
• Short description of the research topic/project:
  • SMILe - Development and Testing of an Integrated Model of Care in the Continuum of Allogeneic Hematopoietic SteM  Cell TransplantatIon faciLitated by eHealth
  • Project started 2017, studies have been completed, Partners: University Base, University Hospital Freiburg
  • eHealth, Integrated care, Allogeneic stem cell transplantation, Implementation science
  • Goal: (1) to develop an integrated care model for allogeneic stem cell transplantation using eHealth (SMILe) by combining implementation, behavioral and computational science methods (e.g. context analysis, behavior change wheel and user-centered design combined with agile software development) (2) to describe the characteristics of this model and its application in clinical practice.