Abstract
In order to remain competitive many companies are forced to exploit the existing potential for improvement across their entire manufacturing network in terms of efficiency, cost reduction, robustness and agility. In particular, the lack of a systematic decision-making process and the fact that decisions are often based on individual experience and imitative behavior lead to unfavorably structured manufacturing networks. Additionally, in increasingly volatile business environments, companies are forced to constantly rethink and thus continuously reconfigure their existing manufacturing network. Today, there are several planning approaches on factory and network level that build on modern decision support tools to enable targeted and transparent reconfiguration of manufacturing networks despite high complexity. However, the subsequent migration process (transformation of the existing network to a new target state) is mostly neglected in literature. This contribution presents an original framework for a systematic reconfiguration process of manufacturing networks. The framework combines existing approaches in literature with identified challenges in the context of three conducted manufacturing network reconfiguration use cases. To close identified gaps in literature the focus is put on the migration process. The elaborated framework is based on a rolling planning and control approach, with decision support tools (i.e. simulation & optimization) taking the leading role due to the operational, complex and dynamic nature of migration processes.
Original language | English |
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Pages (from-to) | 857-862 |
Number of pages | 6 |
Journal | Procedia CIRP |
Volume | 107 |
DOIs | |
Publication status | Published - 2022 |
Event | 55th CIRP Conference on Manufacturing Systems: CIRP CMS 2022 - Lugano, Switzerland Duration: 29 Jun 2022 → 1 Jul 2022 |
Keywords
- Decision support
- Discrete Event Simulation
- Manufacturing network configuration
- Migration planning
- Operations management
ASJC Scopus subject areas
- Control and Systems Engineering
- Industrial and Manufacturing Engineering