Experimental Study on Application of Tuned Mass Dampers for Chatter in Turning of a Thin-Walled Cylinder

Chatter is more likely to occur during the turning process of a thin-walled cylindrical workpiece owing to the low rigidity of such workpieces. Chatter causes intensive vibration, deterioration of the surface finish accuracy, tool damage, and tool wear. Tuned mass dampers (TMD) are usually applied as a passive damping technique to induce a large damping effect using a small mass. This study experimentally investigated the effect of the mounting arrangement and tuning parameters of the TMDs on the production of chatter during the turning process of a thin-walled cylinder, wherein multiple TMDs with extremely small mass ratios were attached to the rotating workpiece. The results of the cutting tests performed by varying the circumferential and axial mounting positions of the TMDs exhibited different characteristics of the chatter suppression effect. Conclusively, the TMDs could suppress the chatter generated by the vibration mode with circumferential nodes if they were mounted on the workpiece to avoid the coincidence of the circumferential arrangement with the pitch of the vibration nodes, regardless of the extremely small mass of the TMDs.

Vibrodiagnostics Faults Classification for the Safety Enhancement of Industrial Machinery

The current digitization of industrial processes is leading to the development of smart machines and smart applications in the field of engineering technologies. The basis is an advanced sensor system that monitors selected characteristic values of the machine. The obtained data need to be further analysed, correctly interpreted, and visualized by the machine operator. Thus the machine operator can gain a sixth sense for keeping the machine and the production process in a suitable condition. This has a positive effect on reducing the stress load on the operator in the production of expensive components and in monitoring the safe condition of the machine. The key element here is the use of a suitable classification model for data evaluation of the monitored machine parameters. The article deals with the comparison of the success rate of classification models from the MATLAB Classification Learner App. Classification models will compare data from the frequency and time domain, the data source is the same. Both data samples are from real measurements on the CNC vertical machining center (CNC-Computer Numerical Control). Three basic states representing machine tool damage are recognized. The data are then processed and reduced for the use of the MATLAB Classification Learner app, which creates a model for recognizing faults. The article aims to compare the success rate of classification models when the data source is a dataset in time or frequency domain and combination.

On Coolant Flow Rate-Cutting Speed Trade-Off for Sustainability in Cryogenic Milling of Ti–6Al–4V

Application of cryogenic fluids for efficient heat dissipation is gradually becoming part and parcel of titanium machining. Not much research is done to establish the minimum quantity of a cryogenic fluid required to sustain a machining process with respect to a given material removal rate. This article presents an experimental investigation for quantifying the sustainability of milling a commonly used titanium alloy (Ti–6Al–4V) by varying mass flow rates of two kinds of cryogenic coolants at various levels of cutting speed. The three cooling options tested are dry (no coolant), evaporative cryogenic coolant (liquid nitrogen), and throttle cryogenic coolant (compressed carbon dioxide gas). The milling sustainability is quantified in terms of the following metrics: tool damage, fluid cost, specific cutting energy, work surface roughness, and productivity. Dry milling carried out the at the highest level of cutting speed yielded the worst results regarding tool damage and surface roughness. Likewise, the evaporative coolant applied with the highest flow rate and at the lowest cutting speed was the worst performer with respect to energy consumption. From a holistic perspective, the throttle cryogenic coolant applied at the highest levels of mass flow rate and cutting speed stood out to be the most sustainable option.

Research on Breakage Characteristics in Side Milling of Titanium Alloy with C emented Carbide End Mill

Aiming at the breakage of tool and low precision of the machined surface in the high-speed milling process of titanium alloy, damage mechanics is used to reveal the formation mechanism of tool fatigue breakage during the milling and determine the critical condition of tool breakage. Cutting edge chipping caused by random impact fracture during the evolution of tool damage is the main failure form of tool fatigue breakage. Based on continuous damage mechanics, fatigue crack growth theory and sliding crack energy balance equation, the crack growth law of tool material is studied under different cutting impact, and the initial damage value and critical damage value of tool material fracture based on the interval method are obtained. And the impact fracture limit conditions of the end mill edge are established including cutting parameters, material hardness, tool damage, tool wear, and cutting impact, which provide a theoretical basis for determining the cutting parameters. A titanium alloy milling experiment is carried out to define the impact damage morphology of the tool in different states after the tool is damaged. The obtained tool safety area range is verified, and the research results provide parameter optimization for the high-speed and high-efficiency milling titanium alloy process.

The Frictional Force between Slug and Die in Shear Cutting after Material Separation

Frictional forces in sheet metal blanking are central in different aspects, e.g. in wear prediction, validation of simulation models or in so called slug pulling. The latter is a phenomenon where the slug is pulled out of the die by the punch after the sheet metal is separated. This leads to process disturbances reaching from a blocked belt feeder up to severe tool damage caused by the simultaneous cutting of the slug and the sheet metal strip. A sufficiently high frictional force between the slug and the die prevents this effect. Despite its importance, this force and its causes have not yet been investigated in detail. A method was developed in this paper to measure the frictional force between slug and die. A shear cutting tool with an integrated piezoelectric load cell and an inductive position sensor was used on a stamping press to cut sheet metal made of CuSn6 (R350, thickness 1 mm). The die clearance, the punch edge radii and the lubrication conditions were varied. A larger die clearance resulted in a lower frictional force while a larger punch edge radius increased it significantly. Lubrication reduced the frictional force, especially for small die clearances. Finally, the cause of the frictional force was investigated by identifying the relevant springback modes of the slugs. This was carried out by correlating the slugs' deflection, oversize, and clean cut height with the frictional force. Especially the slug oversize, i.e. the difference between the slug's diameter and the die's inner diameter, revealed a strong correlation. Calculations showed that the deformation in radial direction is the main cause of the frictional force between slug and die. It suggests that the slug oversize is a good measure for the magnitude of the frictional force.

Data mining–based disturbances prediction for job shop scheduling

In real production manufacturing process, there are many disturbances (e.g. machine fault, shortage of materials, tool damage) which can greatly interfere the original scheduling. These interventions will cost production managers extra time to schedule orders, which increase much workload and cost of maintenance. On account of this phenomenon, a novel system of data mining–based disturbances prediction for job shop scheduling is proposed. It consists of three modules: data mining module, disturbances prediction module, and manufacturing process module. First, in data mining module, historical data and new data are acquired by radio frequency identification or cable from database, and a hybrid algorithm is used to build a disturbance tree which is utilized as a classifier of disturbances happened before manufacturing. Then, in the disturbances prediction module, a disturbances pattern is built and a decision making will be determined according to the similarity between testing data attributes and mined pattern. Finally, in the manufacturing process module, scheduling will be arranged in advance to avoid the disturbances according to the results of decision making. Besides, an experiment is conducted at the end of this article to show the prediction process and demonstrate the feasibility of the proposed method.

Milling Process Monitoring Based on Vibration Analysis Using Hilbert-Huang Transform

Vibration analysis is one method of machining process monitoring. The vibration obtained in machining is often nonlinear and of a nonstationary nature. Therefore, an appropriate signal analysis is needed for signal processing and feature extraction. In this research, vibrations obtained in the milling of thin-walled workpieces were analyzed using the Hilbert-Huang transform (HHT). The features obtained by the HHT served as machining-state indicators for machining process monitoring. Experimental results showed the effectiveness of the HHT method for detecting chatter and tool damage.