Modelling of cutting forces is important for understanding and simulation of the machining processes. This paper presents cutting force modelling of data obtained from machining of C45 carbon steel with a coated carbide tool. The model is based on a rather extensive measurement of 270 combinations of cutting tool geometry parameters (rake angle, clearance angle and helix angle), tool wear (flank wear average value), chip thickness and cutting velocity. The model with the friction and cutting component of the cutting force is presented and discussed. We conducted an analysis of the identified model and found a relationship between the increase in tangential and radial cutting forces and tool wear. We concluded that flank wear influences the cutting force acting on the worn tool more significantly than cutting tool geometry. This is caused by changes in cutting edge geometry and the resultant significant increase in the friction component of the cutting force as is shown using the identified model.

Quick calculation of machine tool dynamic response represents one of the major requirements for machine tool virtual modelling and virtual machining, aiming at simulating the machining process performance, quality, and precision of a workpiece. Enhanced time effectiveness in machine tool dynamic simulations may be achieved by employing model order reduction (MOR) techniques of the full finite element (FE) models. The paper provides a case study aimed at comparison of Krylov subspace base and mode truncation technique. Application of both of the reduction techniques for creating a machine tool multibody model is evaluated. The Krylov subspace reduction technique shows high quality in terms of both dynamic properties of the reduced multibody model and very low time demands at the same time.

The aim of this paper is to introduce a novel methodology, based on a finite element (FE) computation engine for simulation of process machine interaction occurring in machining systems. FE modelling of the milling process has the purpose of being accountable for a thorough validation of the parametric identification approach, and of providing a good physical insight into the phenomena investigated. The system considered here has a lower number of degree-of-freedoms which permits a thorough analysis. However, when taking into account the system's nonlinear and time-varying nature, it is apparent that the results are far from being trivial. Therefore, the analysis of the milling process, taking into account nonlinearities restricting the growth of response amplitudes in the case of chatter-type instability, provides some intrinsic information of the basic features on the system that might be of both fundamental interest and practical use.

The scale of large finite element (FE) models may nowadays easily exceed 10 7 or even 10 8 degrees of freedom (DOF), leading to excessive calculation times when performing transient simulations. Such long simulation times hinder effective structural or thermal design and optimization and make any engineering insight into a problem difficult. The Krylov subspace-based model order reduction (MOR) is a reduction method based on projection of a discretized model onto a lower dimension subspace. The paper presents a methodology based on this method in the context of thermal transient simulation of a large scale subsea equipment FE model. The finite element model mesh size exceeds 30 × 10 6 DOFs. The problem has nonzero initial conditions (ICs) and has to be transformed into a problem with zero ICs in order to apply the Krylov based MOR. Coupling the Krylov based MOR models employs a novel technique involving coupling through their surface interfaces. The approach is compared with the solution obtained using a full FE simulation which takes about 7 days to solve with a fine time step. The results are compared using an error norm which computes maximum absolute difference of temperature fields over time taking the full FE simulation with the fine time step as a reference. The study shows that applying the proposed method using Krylov MOR for performing thermal transient simulations is valid and leads to substantial reduction of the computational time.

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