Design criteria for grinding machine dynamic stability

Abstract Surface grinding is one of the oldest and most widely used machining process: to date, there are still few alternatives available for producing smooth and flat surfaces, satisfying both technical and economic constraints. The quality of a workpiece resulting from a grinding process is strongly influenced by the static and dynamic behavior of the mechanical system, composed by machine tool, wheel, fixture and workpiece. In particular, the dynamic compliance of the machine at wheel-workpiece interface may cause vibrations leading to poor surface quality. Starting from the analysis of process-machine interaction according to self-excited vibrations theories (the most relevant), this paper outlines a path for surface grinding machines design, focused on the identification of the most critical dynamic eigenmodes both in terms of dynamical parameters and geometry (vibration direction). The methodology is based on the application of Nyquist stability criterion for MIMO systems. Firstly, the methodology distinguishes between a limitation mainly ascribable to regenerative chatter and one ascribable to closed-loop eigenmodes properties. In this latter case, it will be shown that stability properties are strongly influenced by the shape and orientation of the elliptical movement of the wheel entailed by the limiting eigenmode (that, in general, is complex). Such an analysis can be also exploited to provide some indications guiding machine structural modifications. Finally, the approach is demonstrated on a couple of grinding machine variants via FE modeling

Potential for smart spindles adoption as edge computing nodes in Industry 4.0

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Optimal feature rescaling in machine learning based on neural networks

This paper proposes a novel approach to improve the training efficiency and the generalization performance of Feed Forward Neural Networks (FFNNs) resorting to an optimal rescaling of input features (OFR) carried out by a Genetic Algorithm (GA). The OFR reshapes the input space improving the conditioning of the gradient-based algorithm used for the training. Moreover, the scale factors exploration entailed by GA trials and selection corresponds to different initialization of the first layer weights at each training attempt, thus realizing a multi-start global search algorithm (even though restrained to few weights only) which fosters the achievement of a global minimum. The approach has been tested on a FFNN modeling the outcome of a real industrial process (centerless grinding).Comment: 6 page

Energy Driven Process Planning and Machine Tool Dynamic Behavior Assessment

AbstractThe current work outlines an approach to close the loop between process planning and machine tool dynamic modeling by addressing the problem of energy efficiency across the process design and realization chains, from the process settings and pallet configuration to the machine tool design and usage phases. The proposed closed loop approach consists of an off-line and on-line component enabling the process and equipment dynamic and energy assessment over time. The benefits of the approach have been evaluated against an industrial case study related to the automotive industry

Fascinating Characteristics and Applications of the Fibonacci Sequence

This thesis offers a brief background on the life of Fibonacci as well as his discovery of the famous Fibonacci sequence. Next, the limit of the ratio of consecutive Fibonacci terms is established and discussed. The Fibonacci sequence is then defined as a recursive function, a linear homogeneous recurrence relation with constant coefficients, and a generating function. Proofs for those particular properties are introduced and proven. Several theorems and identities from the field of number theory concerning the properties of the Fibonacci numbers are also introduced and proven. Finally, the famous Fibonacci puzzle is introduced and critiqued. These fascinating characteristics and applications demonstrate not only the universal nature of the Fibonacci sequence but also the aesthetic nature of God

A meta-model framework for grinding simulation

When considering the mechanics of grinding, several physical phenomena have to be modeled, each one having effect on the resulting grinding forces, wheel and workpiece geometry. Depending on the analyzed problem, some dependencies can be neglected to privilege some aspects instead of others. Nevertheless, all models essentially start considering wheel-workpiece engagement and the corresponding material removal (both wheel and workpiece side), deriving the forces by means of energy balances and/or shear mechanics. The meta-model proposed in this paper represents a general framework conceived for providing a time-domain simulation engine based on a dexel representation of wheel and workpiece, capable to “host” all the semi-empirical models existing in literature, where the overall grinding force is the result of the integration of the force contributions associated to the local removal along wheel-workpiece engagement arc. A cascade approach is adopted to solve for forces and displacements the DAEs set describing the dynamic interactions between wheel and workpiece, whereas all the algebraic relationships pertaining to the various specific models are solved in a pre-processing phase, yielding a set of response surfaces that are queried during time integration. Finally, the meta-model framework is instantiated for a model of traverse roll grinding with force-dependent wheel wear