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In the present analysis, a new experimental pilot plant system for exploring resin-impregnated paper (RIP) bushing technology was conducted. Experimental and numerical studies were carried out on the resin infusion and impregnation processes in the paper condenser core of a RIP bushing. An innovative approach for the molding process (named molding method B) of a commercial RIP bushing was implemented. For this method, the homogeneity of the paper winding process was controlled precisely. The filling process was conducted by gravity due to the difference of heights between two vacuumed chambers and from bottom to top in the mold. The flow front position and infusion time were measured experimentally and used to obtain the axial permeability of the paper condenser core analytically and numerically. The results indicate that the molding methods have a significant effect on the RIP bushing quality, homogeneous filling, and impregnating process time. Also, it was found that homogeneity of the paper winding process and, consequently, uniform axial velocity of resin flow in the radial direction is the most effective factor to eject the air. Finally, it was recognized that the determination of axial permeability in the case of transient flow is novel in comparison with conventional procedures such as Darcy relation of steady flows. By decreasing the paper thickness from 0.3 to 0.2 mm, the permeability decreased from 8.84 × 10−10 to 4.52 × 10−10 m2. The microstructure of the core illustrates that the axial permeability of the crepe paper condenser core is considerably affected by the variation of the paper thickness.

The contact angle (CA) of a water droplet on the polished aluminum surfaces is usually between 60° and 90°. This paper discusses a tuned bulk micro-manufacturing approach for transforming the surface topology of aluminum simultaneously at the micro- and nano-length scales, thereby significantly influencing its wetting characteristics. The approach is cheap, easy to implement, and scalable. The treated aluminum surfaces appeared like roughly polished surfaces at the macroscale and were found to be robust and non-toxic. They exhibited a paper towel effect by showing extreme surface wettability (CA of zero) to many industrial liquids, i.e., wetting on these surfaces is only a function of the surface roughness but not the fluid type. This extreme wetting ability to multiple liquids (or ultra-omniphilicity) was generated by sequentially creating a sub-surface micro- and nano-cavity architecture with nano-cavities within the embryos of micro-cavities interconnected by a network of micro-grooves.

Freehand sketch is a natural and intuitive communication channel for idea expression. Lines are drawn one after another to create the outline before additional lines are often drawn over the existing ones to make a sketch clearer. Typically, the sketch is transformed to be a 3D CAD model by a designer for use in subsequent operations. Sketch-based modeling has been researched to support this transformation but mainly for an online sketch on a digital device. For an offline sketch on a paper, commonly found used in practice, sketch-based modeling remains a challenge because a scanned image conceals enriched information on the sketch in a batch of data points. This paper proposes an approach for reconstructing a 3D model from a paper-based overtraced freehand sketch. Two main modules in this approach are single-line drawing identification and 3D reconstruction. The first module where image processing technique is applied is for transforming a paper-based overtraced freehand sketch to be a single-line drawing in order to generate more information about the sketch (i.e., the number of lines and their starting points and endpoints). The second module where progressive reconstruction approach with cubic corner is applied is for reconstructing a 3D model from the obtained single-line drawing. Steps to be taken in both modules have been formalized. The approach has been successfully implemented on LabVIEW, and tested with several samples.

Freehand sketching on a paper is commonly found to be used as it is a natural and intuitive communication channel for portraying ideas. Additional strokes are often drawn over the existing ones to make the sketch clearer. For its usefulness in subsequent steps, a sketch is transformed to be a 3D CAD model that is typically performed manually by a designer due to a lack of technology support. Geometrical reconstruction from an offline scanning of a sketch has been a challenge because enriched information obtained during sketching is reduced to a batch of data points. This paper presents an algorithm for identifying a single-line drawing from a paper-based overtraced sketch as it is the first important step towards geometrical reconstruction. Key activities in this approach are thick-line sketch creation, contour boundary extraction, segments identification, and line drawing creation. The algorithm has been successfully implemented on LabVIEW and tested with several samples.

In this paper, a non-supervised technique for on-line paper characterisation is presented. The method uses self-organising maps (SOM) and texture analysis for clustering different kinds of paper according to their properties. A light-through technique is used to get pictures of paper. Then, effective texture features are extracted from greyscale images and the dimensionality of the feature data is reduced with SOM allowing visual analysis of measurements. The method makes it possible to implicitly extract important information about paper formation. The approach provides excellent results. A classification error below 1% was achieved for four quality classes when local binary pattern (LBP) texture features were used. The improvement to the previously used texture features in paper inspection is huge: the classification error was reduced by over 40 times. In addition to the excellent classification accuracy, the method also offers a self-intuitive user interface and a synthetic view of the inspected data.

This paper discusses the health hazards faced in a company which produces printed paper packaging. The analysis is based on three main production processes, namely, printing, plate-making and washing. The components in the emissions of these processes are broken down into their chemical compositions and given a hazard rating. The analytic hierarchy process in the health hazard scoring system is introduced to evaluate the level of hazard of each process to the environment. When the hazard level encountered in each process is known, the necessary precautions and measures can be taken.

The production and optimization of biodiesel from a novel feedstock (parsley seed oil) using catalytic potassium hydroxide were investigated in this work with respect to the influence of the parametric reaction: temperature of reaction, time, and the ratio of alcohol-to-oil on the biodiesel yield. The best optimized conditions to generate parsley biodiesel were investigated with the aid of response surface methodology design tool while the analysis of variance showed that the reaction parameters employed had a significant influence on the yield of biodiesel from parsley. The biodiesel percentage yield of 98% was the optimum yield achieved from the experiment conducted with reaction conditions of 60°C, 30 min, and 6:1 for the temperature of the reaction, time of reaction, and the ratio of alcohol-to-oil respectively while the biodiesel percentage yield of 98.18% was predicted from the data analysis as the optimal biodiesel yield. This study developed an optimal temperature of reaction, time of reaction, and the ratio of alcohol-to-oil parametric conditions for producing biodiesel from parsley seed oil and also identified the fatty acid methyl esters (FAME) present in the biodiesel. The biodiesel’s fuel properties were within the requirements of D6751 of the American Society for Testing and Materials (ASTM)

The conventional flood cooling is neither economically viable nor eco-friendly in the cutting process. The vegetable oil is biodegradable and environmentally friendly used as base oil for the minimum quantity lubricant (MQL) cutting, but the temperature field in the milling zone with different vegetable oils as lubricants remains unclear. The temperature of the MQL milling of the 45 steel was studied with cottonseed, palm, castor, soybean, and peanut oils as base oils. The effects of the fatty acid composition, carbon chain length, thermal conductivity, and viscosity on the milling temperature were also considered. The temperature distribution of the milling of the 45 steel with five different vegetable oils was simulated, showing that the cottonseed and the palm oils had good cooling effect. Experimental results were consistent with the findings obtained using the temperature simulation analysis. Compared with that of the flood milling, the temperature of the MQL milling with different vegetable oils decreased, and the temperature was reduced by 67.4% when the cottonseed oil was used. The surface quality of the workpiece was improved during the MQL milling. When the cottonseed oil was used as lubricant, the surface roughness (Ra) values decreased by 41.5%, 53%, and 50.2% when the cottonseed, palm, and castor oils, respectively, were used as lubricating fluids, which indicated that the advantages of biolubricants as base oils especially cottonseed, palm, and castor oils could be used as base oils for the MQL milling.

A new method of cutting stacked workpieces with the help of abrasive water jet was proposed in this paper based on the powerful cutting ability of abrasive water jet. This method can greatly improve the cutting efficiency of abrasive water jet. Firstly, the effect of workpiece thickness on cutting characteristic was studied. Then the cutting quality of the workpieces stacked with the same material and different materials was studied respectively. The characteristics of the cutting of stacked workpieces were analyzed, and on this basis, the optimal stacking strategy for the cutting was put forward. Finally, a prediction model for the total cutting depth of stacked workpieces was built.

Increased rise of industries and car usage in Nigeria and urban development is exponentially on the increase giving rise to multiple waste generation. Evaluation of the different recycling processes showed that acid-clay process has the highest environmental risk as well as the lowest cost; hence, this work added a treatment method for the slurry produced after treatment with acid-clay method, thereby reducing the environmental concern caused by acid and acid sludge formed in the process. The acid ratio was varied between 0 and 20% and adsorbent ratio between 15 and 25%. Automotive-used lubricating oil and industrial-used lubricating oil were treated using two different samples, acid and adsorbent. An increase in acid concentration showed a significant difference over the properties of oil such as density, viscosity, flash point, and other physiochemical properties nevertheless increasing the amount of acid over the optimum point made on significant change. Varying of adsorbent ratio showed little significant effect to density and flash point, while yield and viscosity were unaffected. Optimum point being at 10% acid and 25% adsorbent gave optimal result. All metal contaminants are substantially removed; total base number was improved, while increase in flash point suggested the method effectiveness. Treatment of used industrial oil was found to be easier to re-refine due to less contamination.

With the increased prerequisites for ecological protection, the vegetable oil and nano-fluid-based minimum quantity lubrication (MQL) technology have become a modern research trend. For instance, the palm oil exhibits superior lubricity owing to fatty acid and film-developing characteristics of the carboxyl group. Conversely, due to unique physiochemical properties of Al2O3 nano-particles, they exhibit superior lubricity during machining operations. Thus, here, it was attempted to discover the benefits of Al2O3 and palm oil–mixed nano-fluid in MQL-assisted milling of Inconel 690 for eco-benign and cleaner manufacturing. During the experiment, different concentrations (0.5–5%) of Al2O3 nano-particles were mixed with palm oil. Afterward, the performances were evaluated with respect to the surface roughness, specific cutting energy, tool wear, and cutting temperature. From an economic perspective, the determination of ideal concentration (%) of the Al2O3 nano-particle is a crucial concern. Thus, a fuzzy interference system (FIS)–based model has been developed to obtain the optimum concentration (%) of Al2O3 nano-particle. The multi-performance characteristics index (MPCI) values confirmed that 2.5% was the optimum concentration for Al2O3 in MQL milling environment. Afterward, the machining performances obtained from 2.5% Al2O3 particle concentration have been compared with dry, flood, and pure palm oil condition. It is clearly found from the comparison that MQL milling with 2.5% Al2O3 nano-particle concentration demonstrated much better machining behavior than another lubricating medium.

Friction plays a major role in all bulk metal forming processes, except in a few isolated cases such as die-less wire drawings, etc. In upset cold forging, the existence of frictional constraints between the dies and the work-piece directly affect the plastic deformation of the latter. When a solid cylinder is compressed axially between the top and bottom platen, the work piece material in contact with their surfaces undergoes heterogeneous deformation resulting in “barrelling” of the cylinder. The friction at the faces of contact retards the plastic flow of metal on the surface and in its vicinity. A conical wedge of a relatively undeformed metal is formed which suffers high strain hardening and bulges out in the form of a barrel. This experimental work has been undertaken to study the bulging effect of aluminium solid cylinders, varying the frictional conditions at the flat die surfaces. Flat dies of different surface finish were produced by different machining processes like grinding, milling, electro-spark machining, and lathe turning and finishing with ‘0’ grade emery paper. Experiments were conducted for two aspect ratios. The radius of curvature of bulge was measured and found to conform to the calculated bulge using experimental data. The calculations are made with the assumption that the curvature of the bulge followed the form of a circular arc. A relationship was established between the various bulge parameters including new hoop strain, hydrostatic stress, geometrical shape factor, and stress ratio factor, considering the dissimilar frictional conditions.

The application of ultrasound to leather processing has a significant role for more efficient and advanced manufacturing techniques for leather production. The effect of important process parameters for scale-up such as mechanical agitation, float, and concentration of dye bath has been experimentally examined. The results indicate that float level and dye bath concentration has significant effect on exhaustion of dye. There is no appreciable improvement due to mechanical agitation over the effect of ultrasound in leather dyeing. Dyeing of chrome-tanned wet-blue leather has been carried out directly in the ultrasonic tank with larger area of sample for scale-up possibility. The results indicate notable improvement (1.6-fold) in dye exhaustion as compared to dyeing in process vessel immersed in the ultrasound tank. This is also equivalent to 4.3-fold increase due to ultrasound as compared to control process without ultrasound at static condition. Ultrasound-aided dyeing of vegetable-tanned (EI) leather shows sixfold improvement as compared to control process. Acoustic cavitation energy in the ultrasonic tank, another important parameter for the scale-up, has been measured and the results indicate that ~60% acoustic energy is absorbed by leather in the process. Influence of ultrasound on dye aggregate size, an important parameter for diffusion, was also studied and found to be beneficial. Different ultrasonic equipments such as ultrasonic tank or ultrasonic probe have been tested and compared for their efficacy. Mass balance for ultrasonic leather dyeing process was performed and compared with control processes. Preliminary techno economic cost benefit analysis indicates positive trend for ultrasonic dyeing as compared to conventional drumming process. Savings in dye due to the use of ultrasound yield significant profit taking into account of ultrasonic energy cost, with a payback period for ultrasonic equipment cost. Therefore, the use of ultrasound in leather processing is a potential viable option for tanners in near future as advanced technology.

Thin-Walled Parts (TWP) are widely used in aerospace, whose service performance is significantly affected by the machining accuracy. Considering the poor stiffness of TWP, multi-pass machining is used to machine TWP for better surface accuracy. However, it is difficult to accurately predict the final machining accuracy due to the surface topography error’s propagation and accumulation in multi-pass machining. Therefore, this paper proposes a multi-pass machining accuracy prediction method for TWP based on dynamic factors (cutting force and stiffness). Firstly, a flexible cutting force prediction model, which considers the axial errors determined by the initial surface topography and part deflection, is proposed. Secondly, a Position-Pass-Dependent Stiffness (PPDS) model is established considering position-dependent of stiffness and multi-pass machining material removal. Finally, combining the two models above, a multi-pass machining accuracy prediction method based on Genetic Algorithm - Back Propagation (GA-BP) neural network is proposed. The experiments under various conditions have been carried out to validate the proposed method. The machining accuracy (flatness as an example) is as high as 90.8% using the method in this paper, while it is only 73.9% when the accumulative error is neglected. The proposed method can significantly improve the performance of machining accuracy prediction by analyzing the error propagation mechanism and the effect of dynamic factors between multi-pass machining. Furthermore, this also provides a theoretical basis for process parameters optimization and machining accuracy improvement in TWP machining.

In order to realize real-time and precise monitoring of the tool wear in the milling process, this paper presents a tool wear predictive model based on the Stacked Multilayer Denoising AutoEncoders (SMDAE) technique, the particle swarm optimization with an adaptive learning strategy (PSO-ALS) and the Least Squares Support Vector Machine (LSSVM). Cutting force and vibration information are adopted as the monitoring signals. The unique feature extraction and fusion method consists of three steps: multi-domain features extraction, dimension-reduction by principal component analysis (PCA) and dimension-increment by SMDAE. As a novel feature representation learning approach, the SMDAE technique is utilized to fuse the PCA-based fusion features to enrich the effective information by realizing dimension-increment, thus helping polish up the predictive performance of the proposed model. PSO-ALS is used to obtain the optimal parameters for LSSVM, simplifying the problem and increasing the population diversity. Twelve sets of cutting experiments are conducted to verify the effectiveness of the proposed model. The experimental results show that the presented model is superior to models such as PSO-LSSVM in predictive performance, and the SMDAE technique effectively improves the prediction accuracy of the constructed model. The findings of this paper provide theoretical guidance for monitoring milling tool wear in real industrial situations.

A hot stamping process of quenchable steel tubes using a mandrel reinforced with eco-friendly fibers was developed to produce ultra-high strength steel hollow parts having enhanced lightweighting and crashworthiness. High internal pressure was generated to improve the die quenchability and shape accuracy of the formed parts by the fiber reinforcement. Wood sawdust, shredded copy paper, and plant fiber made of recycled toilet paper were chosen as the fibers, and not only the strength was evaluated from a uniaxial compression test but also the melting behavior of the mandrel was examined. The influence of the fiber reinforcement on the shape accuracy and die quenchability of hot-stamped parts was investigated. The generated internal pressure with the fiber-reinforced ice mandrel was higher than that with the pure ice mandrel without the reinforcement, and thus, the shape accuracy and die quenchability of hot-stamped parts were significantly improved even for a comparatively small change in internal volume of tubes.

In precision machining, the milling tool’ geometry has a great influence on the milled surface quality. The research on milling tool state monitoring was mainly based on one-dimensional signals and two-dimensional images, which could indirectly obtain the tool state and wear area, but it could not provide the volume of milling tool wear and breakage area, thereby making it difficult to achieve quantitative analysis tool wear. This paper proposed a three-dimensional (3D) reconstruction method of the milling tool tip, it could build a 3D model of the milling tool tip, and then the volume of the wear and breakage region of the milling tool tip was extracted by the 3D model. Firstly, the focusing degree of image sequence’s pixels was calculated based on the non-subsampled discrete shearlet transform (NSST) and Laplace algorithm, and the 3D reconstruction of the milling tool tip was completed according to the shape-from-focus (SFF) principle; secondly, the depth values were optimized by fitting the focusing degree curve of pixels in the image sequence with Gaussian function; finally, the volume of the 3D point cloud of the milling tool tip was calculated by the Simpson double numerical integration method, and the material loss in the damaged region could be obtained. In the 3D reconstruction experiment of the milling tool tip, comparing the different focus degree evalution operators of SFF, the 3D point cloud obtained by this paper's proposed 3D reconstruction method has the least noise and the best performance in the root-mean-square error, correlation, and smoothness indexes. In addition, compared with Genmagic software, the 3D point cloud volume calculation method adopted in this paper could accurately calculate the 3D point cloud volume of the milling tool tip, and the percentage error was less than 1%.

This paper aims to design a novel pulse generator for electrical discharge machining (EDM) which can generate discharge current pulse with high discharge frequency more efficiently. Recent research has revealed that the LC pulse generator is able to generate higher rising speed discharge current pulses and high open voltage for EDM by utilizing electromotive force induced by an inductor. Conventional LC generators use inductors to store energy and switches to control the open gap voltage and discharge current flowing through the gap by varying the charging time of inductance, thereby realizing higher peak discharge power even with a low voltage DC power supply, as well as large removal volume per discharge due to high rising speed waveforms. However, the discharge probability of LC generators is lower than 20% if the discharge frequency divided by the switching frequency of the LC generator is defined as the discharge probability of the LC generator. This is because the duration of the open voltage pulse is significantly short in the order of several microseconds, although it usually takes several microseconds or longer for discharge to be ignited. This discharge delay time is an important parameter in EDM because longer delay time results in lower material removal rate, and an excessively short delay time indicates that the gap will be short circuited, resulting in decrease machining stability. Hence, this paper proposes a modified version of the LC generator in which a high impedance transistor pulse generator is used to control the discharge ignition in EDM to produce discharge frequency 2 to 3 times higher than the conventional LC pulse generator.

For the problem of difficulty in measuring the surface roughness of large-pitch internal threads, predictions are used instead of measurements, whereas the common predictions are not highly accurate and narrow in scope of use. In this paper, the homologous isomerism data of vibration signal were utilized to establish a predictive model, which predicted the surface roughness of large-pitch internal threads. The corresponding homologous isomerism data were acquired by turning the large-pitch internal thread, and the data were processed using Relief-F algorithm to obtain the weights, which are the effects of different features on surface roughness. Additionally, influenced by the structural characteristics of the workpiece with a large pitch and a small number of teeth, support vector machine (SVM) and RBF neural network, which are suitable for researches with small sample sizes, from the machine learning algorithm were used to establish the predictive model with the homologous isomerism data of vibration signal as the input parameters. Eventually, the SVM model with higher accuracy of prediction and better ability of generalization was more appropriate for the research of this paper through comparison and analysis. The SVM model was verified to have absolute errors within 0.05μm and relative errors within 4% for turning both left and right threaded surface, demonstrating that the predictive model could take the place of measuring the surface roughness in the mass production of large-pitch internal threads. The method proposed in this paper can also be extended to other parts for the prediction of surface roughness, especially those whose surface roughness are difficult to measure due to structural characteristics.

This paper investigates the thermal-pseudo mechanical (TPM) model’s residual stress prediction capability for its utility in developing friction stir processing (FSP). Specifically, two FSP tests under different processing conditions were conducted, and the corresponding simulations were carried out to verify if the TPM model can predict residual stresses for various tool radii and workpiece materials. The model was successful in predicting residual stresses for one of the tests but failed to work for the other test. Further simulations under different FSP conditions prove that the TPM model works for cast aluminum alloys in addition to wrought aluminum alloys. However, there is only a range of tool radii for which the TPM model is applicable, and the large FSP tool used is the reason for the model’s failure on one of the tests. As a solution, this paper suggests modifications to the TPM model based on calibration to the FSP test temperatures. The calibrated TPM model still cannot predict the effect of the tool radii on the residual stresses; however, the effect on residual stresses due to changes in the process parameters, such as the tool traverse & rotation speeds and the clamping conditions, can be predicted.

Linear tool path with the inherent shortcoming of tangential and curvature discontinuities which lead to poor machining efficiency and surface finish. A lot of local corner smoothing methods which inset a tiny spline curve at the corners have been proposed in literature. However, there exists potential overlap of the two adjacent spline curves while smoothing, and still no optimal solution for eliminating the overlaps. To optimally eliminate the overlaps and smooth the transition curve curvature in real-time, a symmetrical Non-uniform rational B-spline (NURBS) curve transition based on look ahead optimal method is proposed in this paper, by scanning a set of unconstrained pre-cornering transition curve information, analysing the overlap type and backward determining the optimal transition length, thus fully use the linear segment length of each corner, Thus fully increasing the feedrate at the corners. continuity, analytical expression of the curvature extreme, approximation error constraint and real-time performance are considered simultaneously in this paper. Simulation and real machining experiments are made to compare with the existing symmetrical rounding algorithms, the results show that the proposed method has a significant curvature decrease of 17.64% and 4.44% improvement of efficiency, and the curvature distribution of the adjacent curves are balanced, thus improved the machining velocity smoothness. In addition, the real machining experiment results validate the proposed method can work well in 125us real-time control period CNC system.

The continuous short line segment processing method in CNC machining has the defect of frequent fluctuation of feedrate, which affects the quality and efficiency. For this problem, the local and global methods are common solutions. The local method is to insert transition curves at the corners to obtain a smooth toolpath, but this method does not essentially reduce the number of acceleration and deceleration, and it is difficult to insert transition curves between tiny straight sections. Although the global method can obtain smooth tool trajectories, the parametric interpolation method is not suitable for low- and mid-range CNC machines. The article proposes an adaptive tool path generation method with the original part contour as the research object and discrete the NURBS curves into smooth trajectories consisting of large segments of straight lines and circular arcs. The article mimics the crawling characteristics of snakes and designs a double-headed snake algorithm based on the least squares method to implement this process. First, given the start and end points of the curve, two snakeheads search for the maximum linear and circular segments that satisfy the error constraint in the curve direction. The winner will then be selected as the candidate track segment through a competition mechanism. Finally, all trajectory segments are connected to obtain a smooth tool path. Experiments show that the toolpath data of the method in this paper is reduced by 75.56% compared with commercial CAM software when the contour error threshold is the same, and the contour error is reduced by more than one order of magnitude when the number of toolpath segments is equal. In addition, the method in this paper can obtain a smoother machining surface and more stable cutting force, thus achieving a win-win situation of quality and efficiency.

B-spline curve approximation is widely used for fitting linear toolpaths to improve machining quality and efficiency in CNC machining. For a high-quality smoothing method, the control of both approximation error and curve curvature needs to be considered. To reduce the maximum curve curvature while meeting the precision requirements, a B-spline approximation scheme with tool tip position adjustment is proposed in this paper. Toolpaths are first divided into several subdivisions according to the discrete curvature of each tool tip point. For subdivisions that need adjustment, tool tip positions are adjusted to minimize the maximum discrete curvature. An existed approximation method named Energy-term-incorporated Progressive and Iterative Approximation for Least Square fitting (ELSPIA) is selected and improved to fit the adjusted toolpaths and lower the chord errors. For improving the numerical stability of ELSPIA method, the way of searching appropriate foot point parameters is discussed in this paper. Deviation expansion factors of tool tip points are also defined to make the ELSPIA method suitable for fitting the adjusted toolpaths. Both simulations and experimental studies are conducted to prove that the proposed method can significantly decrease the maximum curvature of fitted B-spline curves and improve the machining efficiency without exceeding the tolerance. For example, experimental results show that for the tested butterfly and rabbit toolpaths, the proposed method can improve the machining efficiency by 2.61% and 2.37%, compared with the ELSPIA method without tool tip position adjustment.

The paper provides a comprehensive and detailed description of design solutions of industrial rolling bearing vibration measurement systems used in quality control. The aim of the proposed article was to recognise what design solutions are used among such stands, to make a theoretical analysis of the advantages and disadvantages of each type of solution, as well as an attempt to identify such solutions, the application of which will allow high metrological properties to be achieved. The article is a starting point for the design of new equipment intended for the bearing industry. A theoretical analysis has been made of the most important components of the devices, such as the spindle assembly, drive assembly, clamp assembly, sensor assembly, and data transmission assembly. In the analysis, pictures showing the devices manufactured by various companies from all over the world were included. With the analysis carried out, further experimental work is possible. The analysis presented in the paper allows criteria to be established for the selection of test stands for comparative tests (tests of systems of different design, evaluation, and comparison of indications). It is also possible to relate the measurement result to the design of the device in use. The result of the analysis is the establishment of a design base, which will provide guidance for the construction of improved vibration measurement devices for the bearing industry.

This work presents a measurement for the identification of translational quasi-static stiffness of machine tool using Stiffness Workspace System (SWS). The novelty of this work is a significant modification of the SWS. The changes in measurement procedure and data analysis as well as new technical solutions are described in detail. A methodology for generalised translational static stiffness determination is presented. The major purpose of this paper is to provide the information about quasi-static stiffness values that characterise a typical machine tool. The measurement procedure is implemented in a case study on a 5-axis machining centre. Measurement results were used to determine the generalised translational stiffness indicators of points in the workspace. Then, the static stiffness distribution on the XY plane over machining space was estimated. The obtained results confirm the importance of analyses of static stiffness distribution as they point out areas where some possible changes occur. In the conclusion of the paper the utility value of the information of translational static stiffness is emphasised.