TY  - CPAPER
U1  - Konferenzveröffentlichung
A1  - Rieder, Mathias
A1  - Bonini, Marco
A1  - Verbeet, Richard
A1  - Urru, Augusto
A1  - Bartneck, Norbert
A1  - Echelmeyer, Wolfgang
T1  - Evaluation of human-robot order picking systems considering the evolution of object detection
T2  - 2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 13-16 December 2021, Singapore, proceedings
N2  - The automation of intralogistic processes is a major trend, but order picking, one of the core and most cost-intensive tasks in this field, remains mostly manual due to the flexibility required during picking. Reacting to its hard physical and ergonomic strain, the automation of this process is however highly relevant. Robotic picking system would enable the automation of this process from a technical point of view, but the necessity for the system to evolve in time, due to dynamics of logistic environments, faces operations with new challenges that are hardly treated in literature. This unknown scares potential investors, hindering the application of technically feasible solutions. In this paper, a model for the evaluation of the additional cost of training of automated systems during operations is presented, that also considers the savings enabled by the system after its evolution. The proposed approach, that considers different parameters such as capacity, ergonomics and cost, is validated with a case study and discussed.
KW  - ergonomics
KW  - human-robot-interaction
KW  - object detection
KW  - order picking
KW  - machine learning
KW  - resource utilization
Y1  - 2022
SN  - 978-1-6654-3771-4
SB  - 978-1-6654-3771-4
U6  - https://doi.org/10.1109/IEEM50564.2021.9673091
DO  - https://doi.org/10.1109/IEEM50564.2021.9673091
SP  - 8
S1  - 8
PB  - IEEE
CY  - Piscataway, NJ
ER  -