Bachelor's Thesis: Detecting Trends in Measurement Data from Series Production

Siemens AG

ThesisGerman needed: fluent

Still open on 3 Nov

You apply on the company's own website.

Key facts

Research the theoretical foundations of trend detection in measurement data and learn relevant algorithms and statistical methods.
Analyse measurement data from series production, considering different target values and identifying relevant factors that influence fluctuations.
Develop and test different algorithms, time periods and data aggregation levels to reliably detect short-term and long-term trends.
Validate the results using suitable metrics and assess the quality of detected trends in relation to tool and equipment wear.
Present your findings and prototypes to develop recommendations for the early detection of failures or downtime.

Education: You are currently making good progress in a degree in data science, artificial intelligence, computer science or a similar subject.
You have practical experience using Python or KNIME and sound knowledge of statistics.
You are interested in analysing large datasets and developing algorithms.
Ideally, you have some initial knowledge of industrial series production or measurement technology.
Working style: You work independently and analytically and show strong initiative.
Language skills: You speak fluent German.

Interesting research and development projects that put your theoretical knowledge into practice
Individual guidance and support from experienced experts in your field
Access to the latest technologies, laboratories and resources
Many opportunities to contribute your ideas and actively shape the work
Excellent career opportunities through contact with potential employers

Research the theoretical foundations of trend detection in measurement data and learn relevant algorithms and statistical methods.
Analyse measurement data from series production, considering different target values and identifying relevant factors that influence fluctuations.
Develop and test different algorithms, time periods and data aggregation levels to reliably detect short-term and long-term trends.
Validate the results using suitable metrics and assess the quality of detected trends in relation to tool and equipment wear.
Present your findings and prototypes to develop recommendations for the early detection of failures or downtime.

Education: You are currently making good progress in a degree in data science, artificial intelligence, computer science or a similar subject.
You have practical experience using Python or KNIME and sound knowledge of statistics.
You are interested in analysing large datasets and developing algorithms.
Ideally, you have some initial knowledge of industrial series production or measurement technology.
Working style: You work independently and analytically and show strong initiative.
Language skills: You speak fluent German.

Interesting research and development projects that put your theoretical knowledge into practice
Individual guidance and support from experienced experts in your field
Access to the latest technologies, laboratories and resources
Many opportunities to contribute your ideas and actively shape the work
Excellent career opportunities through contact with potential employers