The trends of machining difficult-to-machine materials and of dry machining or MQL lead to high temperatures in the cutting zone and increase the importance of thermal factors in the machining process. Besides amplified thermal tool loading and wear, the thermal fluxes affect the machining accuracy due to thermo-elastic deformations. Thus it is extremely important to know the magnitudes of these heat flows in order to assess the machining process heat and the tool wear and to develop compensation strategies against thermal tool center point (TCP) displacements. Based on the FE modeling of the cutting processes, the paper describes methods of determining the generated thermal energy and heat fluxes. Furthermore, new methods are presented how and in which partitions this heat flows into the workpiece, the tool and the chips. In order to validate the methods, 2D FE models are compared with temperature and force measurements carried out on a broaching test bed. The methods are applied on cutting examples which are investigated in the papers of Komanduri and Hou using analytical models. Thus, the simulation allows an assessment of the heat fluxes in real cutting processes in comparison with analytical and simplified numerical models.
The main goal of energy-efficient manufacturing is to generate products with maximum value-added at minimum energy consumption. To this end, in metal cutting processes, it is necessary to reduce the specific cutting energy while, at the same time, precision requirements have to be ensured. Precision is critical in metal cutting processes because they often constitute the final stages of metalworking chains. This paper presents a method for the planning of energy-efficient machining processes based on numerical simulations. It encompasses two levels of planning flexibility: process adjustment and process design. At the process adjustment level, within the constraints of existing machines and tools, numerical simulations of orthogonal cutting are used to determine cutting parameters for increased energy efficiency. In this case, the model encompasses specific cutting energy, tool wear, chip geometry, and burr shape. These factors determine the energy and resources required for the chip formation itself, tool replacements, cleaning and deburring and with that the overall energy efficiency and precision. In the context of process design, with the ability to select machines, machine configurations, tools, and cooling systems, numerical simulations of cutting processes that incorporate machine and tool conditions are applied in the planning of energy-efficient machining. The method is demonstrated for the case of drilling processes and supported by experimental investigations that identify the main influences on energy efficiency in drilling.
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