Infrared Thermography for Investigation of Surface Quality in Dry Finish Turning of Ti6Al4V

The machining of titanium alloys always raises issues because of their peculiar chemical and physical characteristics as compared to traditional steel or aluminum alloys. A proper selection of parameters and their monitoring during the cutting operation makes it possible to minimize the surface roughness and cutting force. In this experimental study, infrared thermography was used as a control parameter of the surface roughness of Ti6A4V in dry finish turning. An analysis of variance was carried out to determine the effect of the main cutting parameters (cutting speed and feed rate) on the surface roughness and cutting temperature. In the examined range of the machining parameters, cutting speed and feed were found to have a primary effect on the surface roughness of the machined parts. Cutting speed also significantly affected the temperature of the cutting region, while feed was of second order. Higher cutting speeds and intermediate feed values gave the best surface roughness. A regression analysis defined some models to relate the cutting temperature and surface roughness to the machining parameters. Infrared thermography demonstrated that the cutting temperature could be related to roughness.

METHODOLOGICAL FOUNDATIONS OF DIAGNOSTICS OF METALWORKING TECHNOLOGICAL SYSTEMS ACCORDING TO PARAMETRIC RELIABILITY OF ENSURING A GIVEN QUALITY OF THE TREATED SURFACES

The paper presents the results of research justifying the need for diagnostics of metalworking technological systems on the reliability of ensuring the quality parameters of the surfaces of machine parts during machining. The fundamentals of the methodology of its implementation have been developed. Theoretical models of forming the quality parameters of parts surfaces during machining are considered and refined. This characterizes the scientific novelty of the results obtained. Circuitries for the construction of experimental control systems when conducting bench tests of machined surfaces of parts in conditions close to operational are of practical value. Circuitries are developed and computerized systems based on them for measuring the quality parameters of machined parts surfaces, including the working area of the technological system, are implemented. Recommendations on the rational choice of technological systems and the use of simulation methods in the study of parametric reliability of technological systems are presented. Mathematical and software analysis and processing of experimental results are developed and tested. These results will serve as a foundation for further development of research in the field of parametric reliability of technological systems, improving the quality of domestic engineering products and increasing their competitiveness at the world market.

Modelling dimensional change of machined parts and optimizing replacement time and initial position of cutting tool

In a manufacturing process, a key quality characteristic such as a certain dimension of machined parts can have a systematic shift toward the upper or lower specification limit due to the cutting tool wear. That is, the quality characteristic is a stochastic process with trend. As a result, the process capability and quality loss vary with time and depend on the initial position of the cutting tool. In this setting, decision problems that need to be solved are optimization of replacement time and initial position of the cutting tool. This paper proposes a non-homogenous Wiener process to model the dimensional change of machined parts; and the above-mentioned decision problems are solved through combining this model with a cost model that involves Taguchi quality loss. A real-world example is included to illustrate the appropriateness of the proposed models. The results are useful for both reliability researchers and manufacturing engineers.

A Data-Driven Method for Predicting Deformation of Machined Parts Using Sparse Monitored Deformation Data

In the aircraft industry, where high precision geometric control is vital, unexpected component deformation, due to the release of internal residual stress, can limit geometric accuracy and presents process control challenges. Prediction of component deformation is necessary so that corrective control strategy can be defined. However, existing prediction methods, that are mainly based on the prediction or measurement of residual stress, are limited and accurate deformation prediction is still a research challenge. To address this issue, this paper presents a data-driven method for deformation prediction based on the use of in-process monitored deformation data. Deformation, which is caused by an unbalanced internal residual stress field, can be accurately monitored during the machining process via an instrumented fixture device. The state of the internal stress field within the part is first estimated by the using the part deformation data collected during machining process, and then, the deformation caused by a subsequent machining process is predicted. Deep learning is used to establish the estimating module and predicting module. The estimating module is used to infer the unobservable residual stress field as vectors by using sparse deformation data. The inferred vector is then used to predict the deformation in the predicting module. The proposed method provides an effective way to predict deformation during the machining of monolithic components, which is demonstrated experimentally.

Surface Integrity and Tool Wear Analysis on Turning of Copper-Nickel 70/30 ASTM B122 Alloy under Low Initial Lubrication

Traditional flood lubrication in machining processes is considered an unsustainable technique. In this paper, the low initial lubrication (LIL) technique is analysed during turning of cupronickel 70/30 alloy, in terms of surface roughness. A tribological analysis has been developed on a pin-on-disk tribometer comparing different lubrication systems, obtaining comparative results of friction and tool wear. It has been found that the tool wear is 73% lower in comparison to flood lubrication. LIL technique shows the ability to reduce the friction coefficient compared to dry machining and leads to improve tool wear in comparison with flood lubrication. The surface integrity evaluation of machined parts finds that the LIL technique can improve the surface roughness under specific machining conditions.

An Evaluation of the Tribological Behavior of Cutting Fluid Additives on Aluminum-Manganese Alloys

The introduction of additives enhances the friction and wear reduction properties of cutting fluids (CFs) as well as aids in improving the surface quality of the machined parts. This study examines the tribological behavior of polymer-based and phosphorus-based additives introduced into cutting fluids for the machining of Al-Mn alloys. Ball-on-disc tests were used to evaluate the coefficient of friction (COF) and lubrication failure temperature to study the performance of the additives in the cutting fluids. Surface characterization was performed on the sliding tracks induced on the Al-Mn disc surfaces and used to propose the wear and friction reduction mechanisms. The polymer-based additive possessed a higher temperature at which lubrication failure occurred, displayed comparable COF at a lower temperature under certain conditions, and possessed a steadier tribological behavior. However, the phosphorus-based additive was observed to display lower COF and wear damage from 200 °C till failure. The lower COF values for the phosphorus-based additive at 200 °C corresponded with lower surface damage on the Al-Mn surface. The phosphorus-based additive’s performance at 200 °C could be attributed to the forming of a phosphorus-rich boundary layer within the sliding wear track, resulting in less surface damage on the Al-Mn surface and lower material transfer to the counterface steel ball surface.

Reconfigurable Machine Tool Design for Box-Type Part Families

The reconfigurable manufacturing system (RMS) is a new manufacturing technology and paradigm that resolves the contradictions regarding high efficiency, low cost and flexible production in the mass production of part families. Reconfigurable machine tools (RMTs) are the core components of RMSs. A new approach is proposed for the design of RMTs, which is closely related to the process planning of a given box-type part family. The concepts of the processing unit and the processing segment are presented; they are not only the basic elements of the processing plans of machined parts, but also closely related to the structural design of RMTs. Processing units created by processing features can be combined into various processing segments. All the processing units of one processing segment correspond to the machining operations performed by one RMT. By arranging the processing segments according to the processing sequence, a variety of feasible processing plans for a part can be obtained. Through analysis of the established similarity calculation model for processing plans, the most similar processing plans for the parts in a given part family can be determined and used for the structural design of RMTs. Therefore, the designed RMTs can achieve rapid conversion of processing functions with the least module replacement or adjustment to realize the production of the parts in the part family. Taking the production of a gearbox part family as an example, the validity of the presented method is verified.

Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades

To simulate and analyse the real machined parts in virtual environments, virtual machining systems are applied to the production processes. Due to friction, chip forming, and the heat produced in the cutting zone, parts produced using machining operation have residual stress effects. The machining force and machining temperature can cause the deflection error in the machined turbine blades, which should be minimized to increase the accuracy of machined blades. To minimize the residual stress and deflection error of machined parts, optimized machining parameters can be obtained. In the present research work, the application of a virtual machining system is presented to predict and minimize the residual stress and deflection error in a five-axis milling operations of turbine blades. In order to predict the residual stress and deflection error in machined turbine blades, finite element analysis is implemented. Moreover, to minimize the residual stress and deflection error in machined turbine blades, optimized parameters of machining operations are obtained by using a genetic algorithm. To validate the research work, experimentally determining residual stress by using a X-ray diffraction method from the machined turbine blades is compared with the finite element results obtained from the virtual machining system. Also, in order to obtain the deflection error, the machined blades are measured by using the CMM machines. Thus, the accuracy and reliability of machined turbine blades can be increased by analysing and minimizing the residual stress and deflection error in virtual environments.

Investigation of the effect of residual stresses in the subsurface on process forces for consecutive orthogonal cuts

The quality and surface integrity of machined parts is influenced by residual stresses in the subsurface resulting from cutting operations. These stress characteristics can not only affect functional properties such as fatigue life, but also the process forces during machining. Especially for orthogonal cutting as an appropriate experimental analogy setup for machining operations like milling, different undeformed chip thicknesses cause specific residual stress formations in the subsurface area. In this work, the process-related depth profile of the residual stress in AISI 4140 was investigated and correlated to the resulting cutting forces. Furthermore, an analysis of the microstructure of the cut material was performed, using additional characterization techniques such as electron backscatter diffraction and nanoindentation to account for subsurface alterations. On this basis, the influence of process-related stress profiles on the process forces for consecutive orthogonal cutting strategies is evaluated and compared to the results of a numerical model. The insights obtained provide a basis for future investigations on, e. g., empirical modeling of process forces including the influence of process-specific characteristics such as residual stress.