Univ.-Prof. Dr.-Ing. Peter Burggräf

Application of stochastic risk simulation to increase depth of production planning

Decision support on membrane electrode assembly (MEA) production and factory concepts

Path Prediction For Efficient Order Release In Matrix-Structured Assembly Systems

Plaftforms for factory planning,Plattformen für die fabrikplanung

"Deep-Dive analysis of the latest Lithium-Ion battery safety testing standards and regulations in Germany and China"

Classification Of Flow-Based Assembly Structures For The Planning Of Flexible Mixed-Model Assembly

Flexibility-Driven Planning Of Flow-Based Mixed-Model Assembly Structures

Der digitale Fabrikzwilling

Boosting the Circular Manufacturing of the Sustainable Paper Industry - A First Approach to Recycle Paper from Unexploited Sources such as Lightweight Packaging, Residual and Commercial Waste

Deep reinforcement learning for layout planning - An MDP-based approach for the facility layout problem

Smart Containers-Enabler for More Sustainability in Food Industries?

“ReLIFE”: Business Models for Data- Based Remanufacturing: AdaptiveRemanufacturing for LifeCycle Optimisation ofNetworked CapitalGoods