Marek A. Galewski

An effective method of minimizing vibrations during milling of small flexible workpieces is presented, using a new modified approach to the problem of vibration reduction, based on a workpiece holder with adjustable clamping stiffness. A completely new formulation of a mechanistic model of...

This paper presents an algorithm for 3D path-following using an articulated 6-Degree-of-Freedom (DoF) robot as well as experimental verification of the proposed approach. This research extends the classic line-following concept, typically applied in 2D spaces, into a 3D space. This is achieved by equipping a standard industrial robot with a path detection tool featuring six low-cost Time-of-Flight (ToF) sensors. The primary objective is to enable the robot to follow a physically existing path defined in 3D space. The developed algorithm allows for step-by-step detection of the path’s orientation and calculation of consecutive positions and orientations of the detection tool that are necessary for the robot arm to follow the path. Experimental tests conducted using a Nachi MZ04D robot demonstrated the reliability and effectiveness of the proposed solution.

Vibrations occurring during milling operations are one of the main issues disturbing the pursuit of better efficiency of milling operations and product quality. Even in the case of a stable cutting process, vibration reduction is still an important goal. One of the possible solutions to obtain it is selection of the favorable conditions for clamping the workpiece to the machine table. In this paper, a method for predicting and selecting the clamping condition of a large-size workpiece for the reduction in vibrations during milling is presented. A modal test of the workpiece is performed first for a selected set of tightening screw settings. Next, one milling pass is performed to obtain reference data which are then used to tune the hybrid computational model. In the subsequent step, milling simulations are performed for a set of tightening variants, and the best one is selected, providing the lowest vibrations, assessed as the root mean square (RMS) of vibration displacements. In this paper, the description of the clamping selection procedure, key elements of the simulation model, and simulation and experimental results obtained for the milling of the test workpiece performed for a set of different clamping conditions are provided. The proposed method accurately predicts not only the best but also the worst clamping conditions.

The article introduces a method for selecting the best clamping conditions to obtain vibration reduction during the milling of large-size workpieces. It is based on experimental modal analysis performed for a set of assumed, fixing conditions of a considered workpiece to identify frequency response functions (FRFs) for each tightening torque of the mounting screws. Simulated plots of periodically changing nominal cutting forces are then calculated. Subsequently, by multiplying FRF and spectra of cutting forces, a clamping selection function (CSF) is determined, and, thanks to this function, vibration root mean square (RMS) is calculated resulting in the clamping selection indicator (CSI) that indicates the best clamping of the workpiece. The effectiveness of the method was evidenced by assessing the RMS value of the vibration level observed in the time domain during the real-time face milling process of a large-sized exemplary item. The proposed approach may be useful for seeking the best conditions for fixing the workpiece on the table.

This paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system, i.e., object and its supports, which is essential from the point of view of the relative tool–workpiece vibrations. To reduce the vibration level during milling, it is necessary to appropriately set the support stiffness coefficients, which are obtained from numerous milling process simulations. The simulations utilize the model of the workpiece with adjustable supports in the convention of a Finite Element Model (FEM) and a dynamic model of the milling process. The FEM parameters are tuned based on modal tests of the actual workpiece. For assessing simulation results, the proper indicator of vibration level must be selected, which is also discussed in the paper. However, simulating the milling process is time consuming and the total number of simulations needed to search the entire available range of support stiffness coefficients is large. To overcome this issue, the artificial intelligence salp swarm algorithm is used. Finally, for the best combination of stiffness coefficients, the vibration reduction is obtained and a significant reduction in search time for determining the support settings makes the approach proposed in the paper attractive from the point of view of practical applications.

The paper presents an original method concerning the problem of vibration reduction in the general case while milling large-size and geometrically complex details with the use of an innovative approach to the selection of spindle speed. A computational model is obtained by applying the so-called operational approach to identify the parameters of the workpiece modal model. Thanks to the experimental modal analysis results, modal subsystem identification was performed and reliable process data for simulation studies were obtained. Next, simulations of the milling process, for successive values of the spindle speed, are repeated until the best vibration state of the workpiece is obtained. For this purpose, the root mean square values of the time plots of vibration displacements are examined. The effectiveness of the approach proposed for reducing vibrations in the process of face milling is verified on the basis of the results of appropriate experimental investigations. The economic profitability of the implementation of the operational technique in the production practice of enterprises dealing with mechanical processing is demonstrated as well.

The paper presents a thoroughly modified method of solving the problem of vibration suppression when boring large-diameter holes in large-size workpieces. A new approach of adjusting the rotational speed of a boring tool is proposed which concerns the selection of the spindle speed in accordance with the results of the simulation of the cutting process. This streamlined method focuses on phenomenological aspects and involves the identification of a Finite Element Model (FEM) of a rotating boring tool only and validating it with a real object, while dispensing with discrete modelling of a completely rigid workpiece. In addition, vibrations in the boring process in all directions were observed, which implies a geometric nonlinearity of the process model. During the simulation, the values of the Root Mean Square (RMS) of the time plots and the dominant values of the “peaks” in the displacement amplitude spectra were obtained. The effectiveness of the method was demonstrated using a selected mechatronic design technique called Experiment-Aided Virtual Prototyping (E-AVP). It was successfully verified by measuring the roughness of the indicated zone of the workpiece surface. The economic profitability of implementing the method in the production practice of enterprises dealing with mechanical processing is also demonstrated.

There is abundant worldwide research conducted on the subject of the methods of human respiration process examination. However, many of these studies describe methods and present the results while often lacking insight into the hardware and software aspects of the devices used during the research. This paper’s goal is to present new equipment for assessing the parameters of human respiration, which can be easily adopted for daily diagnosis. This work deals with the issue of developing the correct method of obtaining measurement data. The requirements of the acquisition parameters are clearly pointed out and examples of the medical applications of the described device are shown. Statistical analysis of acquired signals proving its usability is also presented. In the examples of selected diseases of the Upper Respiratory Tract (URT), the advantages of the developed apparatus for supporting the diagnosis of URT patency have been proven.

The paper presents the theoretical background and four applications examples of the new method for the estimation of support stiffness coefficients of complex structures modelled discretely (e.g. with the use of the Finite Element Model (FEM) method based on the modified Particle Swarm Optimization (PSO) algorithm. In real-life cases, exact values of the supports’ stiffness coefficients may change for various reasons (e.g. order of fastening, state of the contact surfaces, environment changes, etc.). Because of the unknown coefficients, reliable simulations of fixed structure (i.e. mounted, assembled, not in a free-free state) are difficult to perform. The method serves as a tool to obtain good correlation between the FEM of a structure and the experimental data. Simple modal tests are required to estimate the first few modes of the fixed system. The FEM of the structure is considered in a free-free state and the support stiffness coefficients of the FEM are estimated by the proposed method. Further simulations with test-tuned and correlated complete FEM could be performed in time or frequency domain.