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Presents current research on robust manufacturing control
Proceedings of the CIRP Sponsored Conference RoMaC, Jacobs University, Bremen, Germany, June 18th - 20th, 2012
Written by leading experts in the field
This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks.
Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to:
sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently,
event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and
non-equilibrium states which increasingly characterize daily business.
These multi-scale changes deeply influence logistic target achievement and call for robust planning and control strategies. Therefore, understanding the cause and effects of multi-scale changes in production networks is of major interest. New methodological approaches from different science disciplines are promising to contribute to a new level comprehension of network processes. Unconventional methods from biology, perturbation ecology or auditory display are gaining increasing importance as they are confronted with similar challenges. Advancements from the classical disciplines such as mathematics, physics and engineering are also becoming of continuing importance.
Content Level »Research
Keywords »Bio-inspired Methods in Logistics - CIRP Sponsored Conference - Data-mining in Logistics - Fluctuations on Networks - Logistics Pattern Analysis - Non-equilibrium Global Production - Production Networks - RoMaC 2012 - Robust Manufacturing Control