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Part of the book series: EcoProduction ((ECOPROD))

Abstract

Picking is a core process of logistics. The challenge of acquiring personnel for operations and handling steadily changing product ranges can be tackled by partwise automated picking systems to create a cooperative working environment for human pickers and picking robots. This chapter is motivated to enable a stepwise transformation from manual picking to highly automated picking processes by cooperative and learning robots. The main goal is to guarantee reliable order fulfilment by implementation of a feedback-loop between humans and robots for error handling and to gather data for machine learning algorithms to increase the performance of object detection. In this chapter a concept for measurement and evaluation of system performance is introduced ensuring successful processing of picking orders and training of picking robots to improve their ability for object detection. It is based on the amount of picking orders, the picking capacity of humans and robots, and the probability for successful automated order picking considering the training effort during system design. The proposed concept can be used for overall capacity planning as well as for operational control of picking processes.

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Acknowledgments

This work is part of the project “ZAFH Intralogistik”, funded by the European Regional Development Fund and the Ministry of Science, Research and Arts of Baden-Württemberg, Germany (F.No. 32-7545.24-17/3/1). It is also done within the post graduate school “Cognitive Computing in Socio-Technical Systems“ of Ulm University of Applied Sciences and Ulm University, which is funded by Ministry for Science, Research and Arts of the State of Baden-Württemberg, Germany.

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Correspondence to Mathias Rieder .

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Rieder, M., Verbeet, R. (2020). Evaluation and Control of a Collaborative Automated Picking System. In: Golinska-Dawson, P., Tsai, KM., Kosacka-Olejnik, M. (eds) Smart and Sustainable Supply Chain and Logistics – Trends, Challenges, Methods and Best Practices. EcoProduction. Springer, Cham. https://doi.org/10.1007/978-3-030-61947-3_3

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