ACV Comparativa entre Processos de Fresamento de Engrenagens Automotivas com Lubrificação Convencional e MQL
Soares, Luiz Arthur Paluch
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Life Cycle Inventory (LCI) data are fundamental for the Life Cycle Analysis (LCA) of products and processes. Nevertheless, there is a lack of inventory data for manufacturing processes, which this research work intends to exploit by means of carrying out a comparative LCA between automotive gear hobbing processes assisted by conventional and Minimum Quantity Lubrication (MQL). Prior to the LCA, bibliographic and bibliometric researches resulted in the identification of 12 methodologies for LCI of manufacturing processes, notably the methodology Unit Process Life Cycle Inventory (UPLCI). Such methodology was employed to conduct one case study for collecting LCI data on automotive gear hobbing process. The LCI results showed that, 76,5% of the energy consumed over the hobbing cycle of one gear, took place under the machine-tool state “Processing”, and the remaining consumed energy was associated to non-productive machine-tool states. The introduction of MQL reduced the cutting fluid consumption by 98,4%. Afterwards, a LCA was carried out for 4 gear hobbing operation scenarios, ranging the consumption parameters of cutting fluid and electric energy. The results of the LCIA pointed out four among eleven normalized environmental impact categories totalized more than 80% of the accumulated impacts: fossil depletion (43%), climate changes (19%), terrestrial acidification (11%) and freshwater consumption (8%). The identified hotspot in the case study was the input flow of raw material for the system “Hobbing Machine”, which is linked to more than 75% of the total amount of normalized potential environmental impacts. Once, any change on the raw material input flow depends on the automotive gear design, the sensitivity analysis was aimed at the environmental aspects of energy and cutting fluid consumption, whose setup depended directly on the parameters of the hobbing process. The introduction of MQL provided reduction of 70.77% on the total amount of normalized potential environmental impacts, while the strategies to reduce electric energy consumption by the machine tool accounted only for 3.74%. This research contributed to setting up new LCI of machining processes, and, revealed by means of a LCA of automotive gear hobbing process, the contribution of raw material, electric energy and lubricant flows to the generation of potential environmental impacts.
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