# Estimation and Adjustment of Interface Stiffnesses for Machine-Tool
## 1 Introduction
The contact stiffness coefficient is then established by placing the model into the data from the observation. The difference in surface topography is observed by comparing two types of floor texture using the proposed mechanism. The contact stiffness of the floor covered with glass coating is 455% higher in contrast to the floor covered with polymer ([PERSON] et al., 2015). [PERSON] et al. (2015) combined the support stiffness model into finite element analysis in order to obtain the rocking vibration mode simulation. The support stiffness model acts as a base in calculating the support stiffness of a prototype from a machining center. The support placement in the simulation is decided based on the stiffness tuning technique. In the simulation to obtain the rocking vibration, the support stiffness is modelled as three-dimensional springs, based on the previous calculation. As verification, a comparison is made between the simulation with the developed model, the simulation without support stiffness, and an experiment. Results show that the natural frequency of the simulation without support stiffness differs above 19%, in contrast to the one with support stiffness, which is under 10%. The rocking vibration modes obtained from the simulation are in parallel with the one obtained from the experiment, showing a higher accuracy obtained when the support stiffness model is involved in FEA ([PERSON] et al., 2003). [PERSON] et al. (2003) enhanced the joint parameter identification procedure by combining the substructure synthesis procedure and the frequency response function (FRF), suggesting a matrix form for the joint model. This procedure is applied in the finite element method on a beam with one end constrained, proving that the joint parameters could be identified using only two measurement points. Results show that FEM is capable of modellingand simulating a properly identified joint parameter on a constrained beam, which also has been verified with an experiment, giving an accurate result that highly influences the parameters. The screw joint rotational stiffness has been found in a sensitive region, while the translational stiffness result is not as accurate, but not so influential towards the simulation result. This method is able to improve the FRF simulation accuracy in the high frequency region due to the cross-coupled term found between the translational and rotational stiffness of the suggested matrix form model [5]. [PERSON] et al. (2019) investigated the effect of a pretightening sequence of anchor bolts on the pretightening state based on the influence of elastic interaction. The anchor bolt pretightening force calculation model is developed analytically, and it is applicable to the three-bolt joint and the n-bolt joint. The structural deformation of a machine bed is expressed in various pretightening sequences by developing an analytical-deformation model. The discrete strain values are designated as the boundary conditions of the model. The particle swarm optimization method is applied to define any unclear correlation parameters. This enables various machine bed configurations to be measured analytically. Finally, two conventional pretightening sequences of anchor bolts are applied for large lathe bed installation as the verification method. After comparison with the result calculated with an autocollimator, the anticipated deformation of the guideway in various pretightening steps showed good consistency. A uniform deformation of the machine bed could be assured from the pretightening sequence from the middle to the sides. In short, the procedure of pretightening for anchor bolts heavily affects the quality of machine bed installation [6]. [PERSON] et al. (2020) combined MSTMM (transfer matrix method for multibody systems) and fractal theory, while developing an advanced model, to calculate joint interfacial contact stiffness. In order to facilitate plastic interaction issue, the Strange contact model is applied, improving the translational model.