Master Thesis in Applied Machine Learning in Root Cause Pattern Identification
Master Thesis in Applied Machine Learning in Root Cause Pattern Identification
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
- During your thesis you will conduct a comprehensive review of existing literature on 8D problemsolving methodology AI and ML applications in quality management.
- You will investigate current stateoftheart ML algorithms and their applications in root cause analysis and error correction.
- Furthermore you will analyze the current manual process used by quality engineers for defining actions root cause analysis and error correction.
- You will collect and evaluate data on personal experiences risk assessments historical complaint data and production data.
- In addition you will design and develop an ML model that can generate suggestions for actions and assign relevance to predictions as well as train the ML model using historical data and validate its accuracy and effectiveness in supporting quality engineers.
- Moreover you will implement the ML model in a realworld setting within the organization.
- You will conduct testing to evaluate the models performance in generating actionable suggestions and its ability to support quality engineers in decisionmaking.
- Further to this you will assess the impact of the ML model on the efficiency and effectiveness of the quality management process.
- Last but not least you will gather feedback from quality engineers and other stakeholders to identify areas for improvement and optimize the ML model based on feedback and performance metrics to enhance its support for the quality management process.
Qualifications :
- Education: Master studies in the field of Industrial Engineering Mechanical Engineering Computer Science Data Science Applied Mathematics Statistics or comparable
- Experience and Knowledge: proficiency in programming languages such as SQL Python; strong background in AI Machine Learning
- Personality and Working Practice: you are a selfstarter who works effectively both independently and as part of a team; you identify challenges proactively propose innovative solutions and have a structured organized approach to research combined with excellent analytical and critical thinking skills
- Languages: very good in English or German
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Felipe Bolanos (Functional Department)
49 5
Andreas Alber (Functional Department)
49 8
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
