Louis Schäfer, M.Sc
Area of Research:
- Machine Learning in Production Planning and Control
- Industrie 4.0
- Coordinator of the lecture ISS - Integrative Strategien und deren Umsetzung in Produktion und Entwicklung von Sportwagen
- Coordinator of the lecture SmartFactory∂Industry at Carl-Benz School of Engineering
- Coordinator of the lecture Teamproject Management and Technology
- Coordination Seminar “Process Mining in Production” with celonis and Bruker Switzerland
- Learning Factory on Lean Production and Industry 4.0
- MoSyS - Human-oriented design of complex System of Systems
- teamIn - Digital leadership and technologies for the team interaction of tomorrow
Research Associate at the Institute of Production Science (wbk) at Karlsruhe Institute of Technology (KIT)
Study of Mechanical Engineering at Karlsruhe Institute of Technology (KIT)
|[ 1 ]|| Kuhnle, A.; Schäfer, L.; Stricker, N. & Lanza, G. (2019), "Design, Implementation and Evaluation of Reinforcement Learning for an Adaptive Order Dispatching in Job Shop Manufacturing Systems". Procedia CIRP, eds. Elsevier, pp. 234-239.
Modern production systems tend to have smaller batch sizes, a larger product variety and more complex material flow systems. Since a human oftentimes can no longer act in a sufficient manner as a decision maker under these circumstances, the demand for efficient and adaptive control systems is rising. This paper introduces a methodical approach as well as guideline for the design, implementation and evaluation of Reinforcement Learning (RL) algorithms for an adaptive order dispatching. Thereby, it addresses production engineers willing to apply RL. Moreover, a real-world use case shows the successful application of the method and remarkable results supporting real-time decision-making. These findings comprehensively illustrate and extend the knowledge on RL.