Thesis (Master): Data Quality Analysis of Valves

Vor 6 Tagen

Erlangen, Deutschland Siemens Vollzeit

**Mode of Employment**: Limited**

**Develop what will be important tomorrow.**

Do you like the sound of finding the smartest solution side by side with professionals and experts? If so, complete your bachelor’s or master’s thesis with us. We can help you to combine knowledge, discover connections, and formulate ideas. When you join our team, you will gain an insight into a range of departments and processes. It is a chance like no other to break new ground as we head into the future of electrification, automation, and digitalization. Seize this opportunity today

In the context of Industry 4.0, data quality is an important aspect for ensuring the reliability and efficiency of industrial equipment. This is especially true for diaphragm valves, where inconsistent and unreliable data quality can lead to significant operational disruptions. The aim of this master's thesis is to develop a data quality model for a diaphragm valve using machine learning and statistical methods. This will involve data fusion from multi-sensor and visual data, investigating different features and methods to ensure the data quality with high accuracy.

**What part will you play?**
- Conduct a comprehensive review of existing research on data quality analysis for industrial machinery
- Design a machine learning model that can process and analyze data and its associated data quality from multiple sensors and visual inputs to predict potential failures in diaphragm valves
- Explore various features and methods to improve the reliability and accuracy of the model
- Develop a working prototype of the model on an embedded system and perform tests to assess its accuracy, efficiency, and practicality
- Compare the developed model with existing approaches and discuss the results

**Use your skills to move the world forward.**
- You are enrolled in a master's program in the fields of computer science, data science, mechanical/electrical engineering, or a related field
- You have first experiences in machine learning and statistical analysis
- Understanding of predictive maintenance and data fusion techniques is a plus
- You have advanced knowledge of programming in Python (Jupyter, Numpy, Pandas, Tensorflow/PyTorch, Seaborn, Matplotlib)
- You have basic knowledge of programming microcontrollers in C/C++
- You have a high level of independence and take the initiative
- Fluent English language skills, both written and spoken (German language skills are not necessary, but desirable)

**Make your mark in our exciting world at Siemens.**

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