Empirical power-consumption model for material removal in three-axis milling
Introduction
The energy crisis, caused by an imbalance between energy supply and demand, has been a reality for some time. In an effort to maintain or increase productivity, the industrial sector has become one of the major energy consumers (U.S. Energy Information Administration (EIA), 2013a). Moreover, energy-price policies have facilitated energy-consumption activities in the interest of economic development (Allcott, 2011). In July 2013, the average retail price for industrial electricity use was 7.32 cents per kWh, whereas residential and commercial electricity prices were 12.62 and 10.81 cents per kWh (U.S. EIA, 2013b).
A greater awareness of potentially harmful environmental practices has prompted various ecodirectives and legislation requiring energy-efficient manufacturing (Chiarini, 2012). In particular, cutting machine tools used in manufacturing processes consume significantly more energy compared with other types of machine tools, such as lasers or welding machines (Fraunhofer, 2012).
The basic energy-saving approach is to measure and assess the energy-consumption characteristics of the process being considered. The energy consumption of machine tools has been decomposed and modeled in accordance with the process parameters. In the study by Balogun and Mativenga (2013), the process states of the machine tool were classified into basic, ready, and cutting states; the total energy consumption was modeled in terms of the respective power elements and time. Salonitis and Ball (2013) divided the energy consumption into a background element, process element, and additional load element. Similarly, Yoon et al. (2013) decomposed energy consumption into basic energy (EBASIC), momentum energy (ESTAGE+ESPINDLE), and material removal energy (EMACHINING).
The proportion of each energy element varies with respect to the type of machine tool and various process parameters. Because the basic energy consumption of a machine tool is constant, the total energy consumption is most affected by the process time. Therefore, many studies have revealed that the specific energy consumption (SEC) can be modeled as the reciprocal of the material-removal rate (Li and Kara, 2011).
Among the decomposed energy elements, the material removal energy (EMACHINING) originates from the additional cutting load during the process. Many researchers have tried to model this cutting force or spindle torque component. According to Li and Kara (2011), this component consists of a specific tool-tip energy (STE) and specific unproductive energy (SUE). In practice, information on the energy consumption related to the cutting force is difficult to obtain. Typically, energy monitoring at the machine level uses basic sensing techniques (O’Driscoll and O’Donnell, 2013); however, machine tools are equipped with numerous auxiliary devices, which affect the total energy consumption.
Hence, the purpose of this research was to devise a means of monitoring the machine tool conditions in terms of the process parameters in an effort to model the energy-consumption components of the manufacturing process. A tool-condition monitoring (TCM) system can provide condition information for effective tool replacement, avoiding potential damage caused by severe tool wear or breakage (Cuppini et al., 1990). Among various sensor systems for TCM systems, power measurement has been considered as an economical monitoring solution. Power or current usually does not require complex measurement systems, and does not disturb the process, unlike a dynamometer (Teti et al., 2010).
Modern computer numerical control (CNC) systems offer information on spindle or motor power in terms of rated current values (Oliveira et al., 2008). Thus, the cutting power can be derived from this information. However, these current values are very sensitive and fluctuate with respect to the tool tooth movement (Shao et al., 2004); hence, appropriate mean power values must be used. Additionally, from the perspective of energy management, energy assessment is one of the tools available in computer-aided design/manufacturing (CAD/CAM) systems (Christoffersen et al., 2006). CAD/CAM provides an estimate of the overall energy-consumption values (Avram and Xirouchakis, 2011) with integrated consideration of the manufacturing cost (Yoon et al., 2012).
In this research, the energy consumption of a milling machine was decomposed into a basic element, momentum element, and material-removal element. The material-removal element was analyzed with respect to the tool wear. An increase in the material-removal energy consumption was observed following an increase in the tool wear. An empirical model was constructed in terms of the process parameters using the measured data. A set of experiments was performed with various process parameters. Because the variation of the material-removal elements originated from the cutting load and tool wear, the constructed model is applicable to estimations of tool-wear conditions and energy consumption/minimization practices.
Section snippets
Theoretical background and material-removal power model
The energy consumption of machine tools is usually decomposed into machine component consumption and process consumption. Neugebauer et al. (2011) decomposed the process energy from the overall machine energy, and calculated this value using the measured torque and feed-force values. Process energy is the power consumed for material removal, and originates from the cutting load. Process power, or material-removal power, PMACHINING, can be calculated usingwhere T is the feed
Experimental details
The purpose of this investigation was to decompose the energy consumption of a machine tool, and to confirm the agreement between the proposed material-removal power model and experiments. The energy consumption of a CNC milling machine (F400, Hyundai WIA Corp. Ltd., Korea) was measured using a power meter (PAC3200, Siemens, Germany). Data were collected using data acquisition equipment (PXI-1042Q, National Instruments Corp., USA) with a sampling frequency of 4 Hz. The current values from a
Energy model of machine tool
The energy consumption of the machine tool was decomposed into separate components. When the machine tool was turned on, it consumed ∼1530 W continuously (the light consumed 16.5 W). A fluid pump used for the cutting fluid consumed ∼602 W. Thus, PBASIC was estimated to be ∼2132 W. The spindle and stage consumed different amounts of energy with respect to their speeds. Fig. 4 below shows the power distribution of the machine tool with respect to the reference machining conditions under cutting.
Conclusion
Monitoring and assessing machine-tool energy consumption is an essential practice for energy conservation research. Because the input power reflects, to some extent, the state of the process, many studies have attempted to diagnose the process using the measured power as an indicator. In this study, the energy consumption of a milling machine used for cutting was decomposed into individual components, and the material-removal power was empirically modeled with respect to the process parameters
Acknowledgment
This work was supported by the Brain Korea 21 plus project at Soul National University, Korea Institute for Advancement of Technology (KIAT) funded by the Ministry of Knowledge Economy (No. 2010-TD-700203-01), the National Research Foundation of Korea (NRF) grants funded by the Ministry of Education, Science and Technology (No. 2013014138, NRF-2010-0029227), and SNU-Hyundai-NGV cooperative research projects funded by Hyundai WIA corporation.
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