Comparison of minimum quantity lubrication and wet milling based on energy consumption modeling

M Bayat, MM Abootorabi - Proceedings of the Institution of …, 2021 - journals.sagepub.com
M Bayat, MM Abootorabi
Proceedings of the Institution of Mechanical Engineers, Part E …, 2021journals.sagepub.com
Estimating the energy consumed by machining process is substantial because it has a large
share of environmental effects in the manufacturing industry. In this paper, a generic energy
consumption model was developed for milling processes that is able to be applied in all
milling machine tools. Energy consumption of each segment was estimated according to
power characteristics and parameters extracted from numerical control (NC) codes, then the
total energy consumption was estimated by adding energy consumption of the machine …
Estimating the energy consumed by machining process is substantial because it has a large share of environmental effects in the manufacturing industry. In this paper, a generic energy consumption model was developed for milling processes that is able to be applied in all milling machine tools. Energy consumption of each segment was estimated according to power characteristics and parameters extracted from numerical control (NC) codes, then the total energy consumption was estimated by adding energy consumption of the machine components. Energy consumption of milling process was measured and compared in conventional (wet) and minimum quantity lubrication (MQL) conditions. The developed method was verified by comparing the estimated values of energy consumption with experimental results. Various studies have suggested different types of energy consumption modeling with machining, however; only a few studies have focused on the use of these modeling techniques. Thus, the MQL method has been rarely compared with the wet milling in terms of energy consumption. In the proposed model, energy consumption for workpiece adjustment, accounting for a major part of the costs in machining economics was considered for the first time. The results showed that the proposed method is efficient and practical for predicting energy consumption, with the possibility of occurring 5% error. Analysis of the results revealed that using the MQL method in milling process leads to 33% lower power consumption than wet milling and therefore, the MQL method can reduce the cost of production.
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