Bachelor's or Master's thesis: Use of AI in maintenance
Karriere bei FIR e. V. an der RWTH Aachen
- AI
- Data-Science
- Industrial-Engineering
- Maintenance-Digitization
- Maintenance-Engineering
- Research
- Thesis-In-Predictive-Maintenance
Assessed from original listing evidence
The role
Job description
Yourtasks:
- Literature and market research on current trends and technologies in the field of AI/ML for maintenance
- Analysis of existing maintenance processes and identification of optimization potential through AI
- Derivation of recommendations for action and creation of practice-oriented documentation
Your profile:
- You are studying industrial engineering, mechanical engineering, computer science or similar
- You have very good written and spoken English skills
- You are characterized by an independent and committed as well as careful and goal-oriented way of working
- You are confident in using the common MS Office programs
Our offer:
- Insights into the industrial and research business in collaboration with well-known companies and research partners
- Interesting, challenging and varied tasks in a qualified and dynamic team
- The opportunity for flexible time management and independent work
- A modern, collegial and digital working environment
- Room for creativity and your personal development
The Service Management department optimizes processes in the operation, maintenance and repair of technical systems. We use modern technologies and innovative concepts to create sustainable added value. AI and ML are playing an increasingly important role in enabling predictive and condition-based maintenance. Your thesis will make an important contribution to this.
Thesis objective: The aim of your thesis is to analyze and evaluate innovative applications of AI in maintenance and to develop a practice-oriented approach. You will investigate how algorithms can help to minimize downtimes, optimize maintenance processes and reduce costs. Based on your results, you will derive recommendations for practical implementation in real application scenarios.
Originally posted on Himalayas
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