Energy consumption characterization in feature based milling and reduction strategies

The rapid increase in human population and industrialization has led to a constant increase in energy consumption. Today, electricity production is mostly obtained by burning fossil fuels. The need of reduction in energy demand and the need to use energy more efficiently have arisen due to environmental impacts and the increase in resource availability problems. The industry sector is the leading energy consuming sector. The energy used for manufacturing processes constitutes a significant portion of the energy consumption in industry sector. Machining operations are widely used in manufacturing operations and these operations are carried out by machine tools. These machine tools that are used in machining operations such as milling and turning have a wide application area due to their transaction capabilities. The energy consumption of machine tools should be measured and modeled for a more efficient use. Within the scope of this thesis, a feature (ISO 10303-STEP AP 224) based energy assumption model applicable for milling machine tools is presented. The energy consuming components of the CNC vertical machining center placed in Mechanical Engineering Department Advanced Manufacturing Technology Laboratory are determined and constant values are obtained for modeling the energy consumption of these components. The calculations that are carried out using these obtained values and energy prediction model are compared to the data obtained from experimental cutting, the consistency of the model is measured and consistent results are obtained for milled parts. The total energy consumption proportion of the auxiliary components of the machine tool and how much energy they provide are determined and data are collected to derive energy reduction strategies. In addition to this, the effect of different tool paths that are produced by CAM packaged software on energy consumption is investigated by experimental cuttings for milling operations of a feature. It is found that as the time which depends on tool path length increases, the total energy consumption also increases.