Unit process energy consumption models for material removal processes
Introduction
In the last decade, economical, environmental and legislative drivers have raised the awareness of energy consumption and the associated environmental impact of manufacturing processes [1]. The energy cost of manufacturers is increasing considerably due to both soaring energy price and growing production demands. The industrial energy usage is highly related to the greenhouse gas emissions, which contribute to the global climate change. The preliminary environmental studies for machine tools in material removal processes (e.g. turning, milling) indicate that more than 99% of the environmental impacts are due to the consumption of electrical energy [2]. Therefore, reducing electrical energy consumption of manufacturing processes not only benefits the manufacturers economically but also improves their environmental performance.
Achieving this energy reduction requires knowledge about energy consumption as a function of machine tool and process parameters. However, the previous studies were primarily based on rough estimates considering averaged demands. Neither the machine tool documentations nor the existing methods could provide a reliable estimation of energy consumption under various machining conditions. Hence, developing machine specific models of unit process energy consumption is essential to improve the accuracy and the reliability of the estimation.
This paper presents an empirical approach to characterize the relationship between unit energy consumption and process variables. Initially, material removal processes are targeted as the starting point of developing the methodology. Eight different CNC turning and milling machines were selected for investigation. The derived machine specific models provide high level of accuracy for predicting energy consumption, which will enable industry to develop potential energy saving strategies during product design and process planning stages.
Section snippets
Literature review
Theoretically, energy consumption or power demand can be calculated based on either force or thermal equilibrium.
Cutting forces of turning and milling processes have been studied for decades. Different methods were applied to predict cutting forces, for instance, Oxley's model uses orthogonal machining theory [3], Armarego force prediction is an empirical approach [4]. However, power estimation based on cutting force only captures the power demand at the tool tip which is the minimal energy for
Methodology
In general, the unit process energy consumption models are developed by means of observing and monitoring energy consumption related to process variables, namely empirical modelling [8].
There were four stages of developing the empirical models. Firstly, a design of experiments (DOE) defined the tested process variables and their variance. Secondly, series of experiments were conducted according to the DOE, while the energy behaviour of the machine tool was monitored and transferred as input
Modelling and validation
For each tested machine tool, there were hundreds observed data for model development with SPSS software. Initial curve estimation indicates that an inverse model provides the best fitness about the relationship between SEC and MRR, as shown in Eq. (1) [7].where C0 and C1 are the machine specific coefficients.
An example of 5-axis milling machine tool, DMU 60P, is shown in Fig. 2. The large F value (184,086.052) in the ANOVA table indicates the strong correlation between MRR and SEC.
Wet cut
Although there is a trend towards minimum coolant or lubricant, wet cut is still widely used in industry. From an energetic point of view, applying coolant requires additional power to activate the coolant pump which is generally at a constant level. Different machines provide different pressure of the output coolant. For some complex models, such as DMU 60P, an integrated coolant filter system consumes extra energy once the coolant pump is enabled. All the experiments have been repeated on 3
Discussion and conclusions
This paper presents an empirical approach to develop unit process energy consumption models for material removal processes. For the selected machine tools, the derived models could provide a reliable prediction of energy consumption for removing material at certain material removal rate. Within this information, the energy requirement of machining a product with turning or milling processes can be easily calculated. Thus, a more accurate assessment of environmental impact of manufacturing
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