Publications

@inproceedings{antons2020modelling,

title = {Modelling Autonomous Production Control: A Guide to Select the Most Suitable Modelling Approach},

author = {Oliver Antons and Julia C. Arlinghaus},

url = {https://link.springer.com/chapter/10.1007/978-3-030-44783-0_24},

doi = {10.1007/978-3-030-44783-0_24},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {International Conference on Dynamics in Logistics},

pages = {245--253},

organization = {Springer},

abstract = {This paper studies and compares Minimal Models, Linear Programming and Discrete-event Simulation as approaches to model Production Planning and Control with regard to their ability to include the concept of autonomous control. After a brief explanation of autonomous control in production planning, the three aforementioned concepts are introduced in detail. We derive their benefits and drawbacks for different scenarios, and subsequently give advice when to deploy each method, applicable for researchers and practioners alike.},

keywords = {Autonomous production control, Autonomy \& Decision-making Authority, Discrete-event simulation, Linear programming, Minimal models, Production planning and control},

pubstate = {published},

tppubtype = {inproceedings}

}