TY  - JOUR
AB  - The transformation of today's manufacturing lines into truly adaptive systems facilitating individualized mass production requires new approaches for the efficient integration, configuration and control of robotics and automation components.
Recently, various types of Plug-and-Produce architectures were proposed that support the discovery, integration and configuration of field devices, automation equipment or industrial robots during commissioning or even operation of manufacturing systems.
However, in many of these approaches, the configuration possibilities are limited, which is a particular problem if robots operate in dynamic environments with constrained workspaces and exchangeable automation components as typically required for flexible manufacturing processes.

In this article, we introduce an extended Plug-and-Produce concept based on dynamic motion planning, co-simulation and a collaborative human-robot interaction scheme that facilitates the quick adaptation of robotics behaviors in the context of a modular production system. 
To confirm our hypothesis on the efficiency and usability of this concept, we carried out a feasibility study where participants performed a flexible workcell setup. 
The results indicate that the assistance and features for planning effectively support the users in tasks of different complexity and that a quick adaption is indeed possible. 
Based on our observations, we identify further research challenges in the context of Plug, Plan and Produce applied to smart manufacturing.
DA  - 2019
DO  - 10.1007/s13218-019-00595-0
LA  - eng
IS  - 2
M2  - 151
PY  - 2019
SN  - 0933-1875
SP  - 151-161
T2  - KI - Künstliche Intelligenz. German Journal of Artificial Intelligence
TI  - Plug, Plan and Produce as Enabler for Easy Workcell Setup and Collaborative Robot Programming in Smart Factories
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-29355003
Y2  - 2024-11-24T22:20:26
ER  -