Modeling in Cutting
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Modeling in Cutting P. J. Arrazola Faculty of Engineering, Manufacturing Department, Mondragon Unibertsitatea, ArrasateMondragon, Gipuzkoa, Spain
Synonyms Simulation of Machining Processes
Definition Modeling of machining processes is the competence of predicting the influence of input cutting parameters on output variables such as (i) fundamental variables and (ii) industrial relevant outcomes. Fundamental variables are forces, temperatures, strains, strain rates, stresses, and pressures. Industrial relevant outcomes include tool life, surface roughness, surface integrity, distortion, stability, and burrs. In order to predict the abovementioned outputs, different modeling approaches can be employed. For years, analytical and empirical models were the most commonly used. Recently, numerical and artificial intelligence (AI)-based methods are gaining relevance with the increase in computing power. The reason for this is the capability of computers to deal with complex
problems such as tool–chip contact and material nonlinearities.
Theory and Application Modeling Overview During machining, very complex mechanical, thermal, and chemical phenomena occur. Due to this, and although several significant advances have been made on the knowledge of cutting processes, there are still many issues that remain not well understood. That is, tool-life, surface finish, subsurface integrity, chip-form/chip breakability, burr formation, part accuracy, etc. In recent years it has been shown that modeling can provide a more comprehensive and, in some cases, complementary approach to experimental methods (Arrazola et al. 2013). Modeling offers the capability to predict what could happen during the material removal process. This enables the design and modification of process input parameters beforehand in order to reduce or eliminate problems that may arise during machining operations. These predictive models could be (i) integrated into process planning systems to improve productivity and enhance product quality and (ii) used also in adaptive control for machining processes, reducing, and/or eliminating trialand-error approaches. Figure 1 summarizes the basic modeling structure, where three main parts can be observed:
# CIRP 2014 The International Academy for Production Engineering et al. (eds.), CIRP Encyclopedia of Production Engineering, DOI 10.1007/978-3-642-35950-7_16800-1
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Modeling in Cutting
Modeling in Cutting, Fig. 1 Basic scheme for modeling of machining processes
(i) input parameters, (ii) models, and (iii) output parameters. Scales in Modeling Depending on the problem to be studied, modeling of machining processes can be focused on different scales (Fig. 2): • Macroscale: Models that take into account machine tool, workpiece, and tool including their fixture system and toolholder (Urresti et al. 2009). In this scale prediction of distortions is the main goal. • Mesoscale: Models which consider the area where the chip is formed. With this scale it is possible to predict cutting forces, tool temperatures, burr formation, t
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