Abstract
The energy demand of body shop manufacturing lines is primarily determined by decisions that are made in the early planning phase. However, energy related data which is needed in order to make well founded decisions is mostly unavailable in that phase. The lack of information leads to overdimensioned equipment and inefficient processes. Therefore, in this paper energy related data is acquired and analyzed from existing manufacturing lines. With an established energy and equipment database, the prediction of the future manufacturing lines energy demand is possible. In combination with a rule-based decision support, improvements are already possible in the early planning process. In comparison with existing approaches, the developed holistic methodology addresses all levels in the planning process and is exemplified by a use case in the automotive industry.
Original language | English |
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Article number | 125269 |
Journal | Journal of cleaner production |
Volume | 284 |
Early online date | 8 Dec 2020 |
DOIs | |
Publication status | Published - 15 Feb 2021 |
Externally published | Yes |
Keywords
- UT-Hybrid-D
- Decision support
- Energy database
- Energy efficiency
- Planning phase
- Body shop