A holistic approach for the cognitive control of production systems
Increasing dynamics and a turbulent environment force industrial enterprises to ensure a highly efficient production. The field of production planning and control (PPC) and the sustainable optimization of its methods are hereby of utmost importance. This paper introduces a concept for a cognitive pr...
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Veröffentlicht in: | Advanced engineering informatics 2010-08, Vol.24 (3), p.300-307 |
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creator | Zaeh, Michael F. Reinhart, Gunther Ostgathe, Martin Geiger, Florian Lau, Christian |
description | Increasing dynamics and a turbulent environment force industrial enterprises to ensure a highly efficient production. The field of production planning and control (PPC) and the sustainable optimization of its methods are hereby of utmost importance. This paper introduces a concept for a cognitive production planning and control system, in which so-called smart products store knowledge about the production process and its current state. The RFID (radio frequency identification) technology presents a promising approach to realize those smart products, to enhance the information management on the shop floor and to offer a precise image of individual product states in the production process. The knowledge on production sequences is represented in a graph-based model. The developed concept represents the executable production of every single resource in capability profiles that are used for the allocation of production steps to resources. Material transports are realized by an anticipatory transport control, which updates its model parameters autonomously. During runtime, the product-specific operation times are measured and stored on the smart product, which is subsequently used to update the overall planning data. Thus, the introduced production planning and control system is able to react to unforeseen events (e.g. missing material, insufficient product quality) and autonomously adapts the planning data to the actual elapsed values of the real production. First experiments showed promising results for the approach to provide and process information directly on the shop floor: the idleness of resources due to errors was reduced by 41% from 19.4% to 8.0% during a 3
h test run. The waiting time of resources caused by missing material can be reduced in specific cases by 17.7%. |
doi_str_mv | 10.1016/j.aei.2010.05.014 |
format | Article |
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h test run. 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The field of production planning and control (PPC) and the sustainable optimization of its methods are hereby of utmost importance. This paper introduces a concept for a cognitive production planning and control system, in which so-called smart products store knowledge about the production process and its current state. The RFID (radio frequency identification) technology presents a promising approach to realize those smart products, to enhance the information management on the shop floor and to offer a precise image of individual product states in the production process. The knowledge on production sequences is represented in a graph-based model. The developed concept represents the executable production of every single resource in capability profiles that are used for the allocation of production steps to resources. Material transports are realized by an anticipatory transport control, which updates its model parameters autonomously. During runtime, the product-specific operation times are measured and stored on the smart product, which is subsequently used to update the overall planning data. Thus, the introduced production planning and control system is able to react to unforeseen events (e.g. missing material, insufficient product quality) and autonomously adapts the planning data to the actual elapsed values of the real production. First experiments showed promising results for the approach to provide and process information directly on the shop floor: the idleness of resources due to errors was reduced by 41% from 19.4% to 8.0% during a 3
h test run. The waiting time of resources caused by missing material can be reduced in specific cases by 17.7%.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.aei.2010.05.014</doi><tpages>8</tpages></addata></record> |
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source | ScienceDirect Journals (5 years ago - present) |
subjects | Adaptive automation Allocations Cognitive Factory Control systems Dynamics Flexible manufacturing systems Mathematical models Production control Production planning Radio frequency identification Transport Turbulence |
title | A holistic approach for the cognitive control of production systems |
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