Decision support for evaluating energy demand in vinification processes using fuzzy sets theory
The current trend associated with high energy demand, depletion of energy reserves and low potential of renewable energy sources linked with strong industrial growth, is increasingly becoming unsustainable. As a result, production costs have increased considerably in the process industries, mainly...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
ERC
2006
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| Online Access: | http://hdl.handle.net/20.500.11937/27007 |
| _version_ | 1848752144325279744 |
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| author | Musee, N. Lorenzen, L. Aldrich, Chris |
| author_facet | Musee, N. Lorenzen, L. Aldrich, Chris |
| author_sort | Musee, N. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The current trend associated with high energy demand, depletion of energy reserves and low potential of renewable energy sources linked with strong industrial growth, is increasingly becoming unsustainable. As a result, production costs have increased considerably in the process industries, mainly owing to skewed energy demand and supply realities. A feasible strategy for meeting these challenges is to reduce energy consumption per unit throughput. However, to obtain a workable solution, decision makers may have to deal with energy management variables that are ambiguous, which makes solving the energy minimization problem with conventional numerical approaches very difficult. In this paper, we consider an alternative approach based on fuzzy logic to qualitatively evaluate the energy demand associated with an industrial cooling process. The model was formulated based on Mamdani fuzzy logic inferencing and implemented in MATLAB 6.5 via the Fuzzy Logic toolbox. The energy demands pertaining to specific variables were independently estimated, followed by an estimate of the overall energy consumption. The procedure is demonstrated via a case study of cooling at the maceration stage of a vinification process in the wine industry. |
| first_indexed | 2025-11-14T08:03:57Z |
| format | Journal Article |
| id | curtin-20.500.11937-27007 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:03:57Z |
| publishDate | 2006 |
| publisher | ERC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-270072017-02-28T01:51:18Z Decision support for evaluating energy demand in vinification processes using fuzzy sets theory Musee, N. Lorenzen, L. Aldrich, Chris fuzzy logic vinification energy minimization wine industry maceration The current trend associated with high energy demand, depletion of energy reserves and low potential of renewable energy sources linked with strong industrial growth, is increasingly becoming unsustainable. As a result, production costs have increased considerably in the process industries, mainly owing to skewed energy demand and supply realities. A feasible strategy for meeting these challenges is to reduce energy consumption per unit throughput. However, to obtain a workable solution, decision makers may have to deal with energy management variables that are ambiguous, which makes solving the energy minimization problem with conventional numerical approaches very difficult. In this paper, we consider an alternative approach based on fuzzy logic to qualitatively evaluate the energy demand associated with an industrial cooling process. The model was formulated based on Mamdani fuzzy logic inferencing and implemented in MATLAB 6.5 via the Fuzzy Logic toolbox. The energy demands pertaining to specific variables were independently estimated, followed by an estimate of the overall energy consumption. The procedure is demonstrated via a case study of cooling at the maceration stage of a vinification process in the wine industry. 2006 Journal Article http://hdl.handle.net/20.500.11937/27007 ERC restricted |
| spellingShingle | fuzzy logic vinification energy minimization wine industry maceration Musee, N. Lorenzen, L. Aldrich, Chris Decision support for evaluating energy demand in vinification processes using fuzzy sets theory |
| title | Decision support for evaluating energy demand in vinification processes using fuzzy sets theory |
| title_full | Decision support for evaluating energy demand in vinification processes using fuzzy sets theory |
| title_fullStr | Decision support for evaluating energy demand in vinification processes using fuzzy sets theory |
| title_full_unstemmed | Decision support for evaluating energy demand in vinification processes using fuzzy sets theory |
| title_short | Decision support for evaluating energy demand in vinification processes using fuzzy sets theory |
| title_sort | decision support for evaluating energy demand in vinification processes using fuzzy sets theory |
| topic | fuzzy logic vinification energy minimization wine industry maceration |
| url | http://hdl.handle.net/20.500.11937/27007 |