Thesis Work – Applied probability and statistics for robot dimensioning
Core
Master thesis on integrating probability and statistics into the mechanical dimensioning process for industrial robots to reduce conservatism and quantify failure probability.
Role type
Master thesis researcher (probabilistic mechanical design)
Builds
Improved methodologies for robot dimensioning and failure probability prediction
Domain
Robotics / Mechanical Engineering / Reliability Engineering
Deliverable
research
Required skills
probabilistic mechanical design, reliability engineering, statistical evaluation, Python, MATLAB, statistical software
Responsibilities
Literature study on probabilistic mechanical design and reliability engineering; Analyze current in-house dimensioning criteria and load calculation methods; Develop and test improved methodologies to predict failure probability; Document findings and provide implementation recommendations
