Steven Y. Liang

Machining Process Monitoring and Control: The State-Of-The-Art

Research in automating the process level of machining operations has been conducted, in both academia and industry, over the past few decades. This work is motivated by a strong belief that research in this area will provide increased productivity, improved part quality, reduced costs, and relaxed machine design constraints. The basis for this belief is twofold. First, machining process automation can be applied to both large batch production environments and small batch jobs. Second, process automation can autonomously tune machine parameters (feed, speed, depth of cut, etc.) on-line and off-line to substantially increase the machine tools performance in terms of part tolerances and surface finish, operation cycle time, etc. Process automation holds the promise of bridging the gap between product design and process planning, while reaching beyond the capability of a human operator. The success of manufacturing process automation hinges primarily on the effectiveness of the process monitoring and control systems. This paper discusses the evolution of machining process monitoring and control technologies and conducts an in-depth review of the state-of-the-art of these technologies over the past decade. The research in each area is highlighted with experimental and simulation examples. Open architecture software platforms that provide the means to implement process monitoring and control systems are also reviewed. The impact, industrial realization, and future trends of machining process monitoring and control technologies are also discussed.

Predictive modeling of surface roughness in grinding

Abstract The surface roughness is a variable often used to describe the quality of ground surfaces as well as to evaluate the competitiveness of the overall grinding system. This paper presents the prediction of the arithmetic mean surface roughness based on a probabilistic undeformed chip thickness model. The model expresses the ground finish as a function of the wheel microstructure, the process kinematic conditions, and the material properties. The analysis includes a geometrical analysis of the grooves left on the surface by ideal conic grains. The material properties and the wheel microstructure are considered in the surface roughness prediction through the chip thickness model. A simple expression that relates the surface roughness with the chip thickness was found, which was verified using experimental data from cylindrical grinding.

Cutting forces modeling considering the effect of tool thermal property—application to CBN hard turning

Abstract Force modeling in metal cutting is important for a multitude of purposes, including thermal analysis, tool life estimation, chatter prediction, and tool condition monitoring. Numerous approaches have been proposed to model metal cutting forces with various degrees of success. In addition to the effect of workpiece materials, cutting parameters, and process configurations, cutting tool thermal properties can also contribute to the level of cutting forces. For example, a difference has been observed for cutting forces between the use of high and low CBN content tools under identical cutting conditions. Unfortunately, among documented approaches, the effect of tool thermal property on cutting forces has not been addressed systemically and analytically. To model the effect of tool thermal property on cutting forces, this study modifies Oxley’s predictive machining theory by analytically modeling the thermal behaviors of the primary and the secondary heat sources. Furthermore, to generalize the modeling approach, a modified Johnson–Cook equation is applied in the modified Oxley’s approach to represent the workpiece material property as a function of strain, strain rate, and temperature. The model prediction is compared to the published experimental process data of hard turning AISI H13 steel (52 HRc) using either low CBN content or high CBN content tools. The proposed model and finite element method (FEM) both predict lower thrust and tangential cutting forces and higher tool–chip interface temperature when the lower CBN content tool is used, but the model predicts a temperature higher than that of the FEM.

Chatter stability of a slender cutting tool in turning with tool wear effect

An analysis of the chatter behavior for a slender cutting tool in turning in the presence of wear flat on the tool flank is presented in this research. The mechanism of a self-excited vibration development process with tool wear effect is studied. The components contributing to the forcing function in the turning vibration dynamics are analyzed in the context of cutting force and contact force. A comparison of the chatter stability for a fresh cutting tool and a worn cutting tool is provided. Stability plots are presented to relate width of cut to cutting velocity in the determination of chatter stability. Machining experiments at various conditions were conducted to identify the characteristic parameters involved in the vibration system and to identify the analytical stability limits. The theoretical result of chatter stability agrees qualitatively with the experimental result concerning the development of chatter stability model with tool wear effect.

Modeling of CBN tool flank wear progression in finish hard turning

Cubic Boron Nitride (CBN) cutters are widely used in finish turning of hardened parts. Their wear mechanisms and associated wear rates are important issues to be understood in view of the high cost of CBN cutters and because of the tool change down-time cost which impacts the economic justification of CBN precision hard turning. The objective of this study is to present a methodology to analytically model the CBN tool flank wear rate as a function of tool/workpiece material properties, cutting parameters and process arrangement in three-dimensional finish hard turning. The proposed model is calibrated with experimental data of finish turning of hardened 52100 bearing steel with a CBN insert, and further validated over practical hard turning conditions. It is shown that adhesion is the main wear mechanism over common cutting conditions, which agrees with documented observations, however, chemical diffusion can gain dominance over extended periods of machining time under aggressive cutting conditions.

Modeling of Cutting Forces Under Hard Turning Conditions Considering Tool Wear Effect

Quantitative understanding of cutting forces under hard turning conditions is important for thermal modeling, tool life estimation, chatter prediction, and tool condition monitoring purposes. Although significant research has been documented on the modeling of forces in the turning operation in general, turning of hardened materials involves several distinctive process conditions, including negative tool rake angle, large tool nose radius, and rapid tool wear. These process conditions warrant specific treatment in the analysis of cutting forces. This paper first addresses these issues by formulating an oblique chip formation force model through the extension of a two-dimensional (2D) mechanistic force model while considering the effect of tool geometry complexities. The coefficients of the mechanistic force model are estimated by applying a genetic algorithm in overcoming the lack of explicit normal equations. Then the forces occurring due to flank wear are modeled by extending a 2D worn tool force modeling approach into a three-dimensional analysis to accommodate the effect of low feed rate, small depth of cut, and relatively large tool nose radius in hard turning. The total cutting forces are the linear summation of forces due to chip formation and forces due to flank wear. The model-predicted forces match well with experimental results in the turning of hardened 52100 bearing steel under practical cutting conditions (low feed rate, small depth of cut, and gentle cutting speed) using cubic boron nitride (CBN) tools under the progressive tool flank wear conditions.

Dynamic Prognostic Prediction of Defect Propagation on Rolling Element Bearings

Rolling element bearing failure is a major factor in the failure of rotating machinery. Current methods of bearing condition monitoring focus on determining any existing fault presence on a bearing as early as possible. Although a defect can be detected when it is well below the industry standard of a fatal size of 6.25 mm2 (0.01 in2), the remaining life of a bearing (the time it takes to reach the final failure size) from the point where a defect can be detected can vary substantially. As a fatal defect is detected, it is common to shut down machinery as soon as possible to avoid catastrophic consequences. Performing such an action, which usually occurs at inconvenient times, typically results in substantial time and economics losses. It is, therefore, important that the bearings remaining life be more precisely forecasted, in a prognostic rather than diagnostic manner, so that maintenance can be optimally scheduled. Unfortunately, current bearing remaining life prediction methods have not been well dev...

Analysis of acoustic emission in chatter vibration with tool wear effect in turning

Abstract The progressive wear of cutting tools and occurrence of chatter vibration often pose limiting factors on the achievable productivity in machining processes. An effective in-process monitoring system for tool wear and chatter therefore offers the unique advantage of relaxing the process parameter constraints and optimizing the machining production rate. This research presents a dynamic model of the cutting RMS acoustic emission (AE) signal when chatter occurs in turning, and it determines how this motion is related to the RMS AE signal in the presence of tool flank wear. The tool wear effect on acoustic emission generated in turning is expressed as an explicit function of the cutting parameters and tool/workpiece geometry. The AE generated from the sliding contact on the flank wear flat during chatter is investigated based on the energy dissipation principle. This model offers an explanation of the phenomenon of chatter vibration in the neighborhood of the chatter frequency of the tool. It also sheds light on the variation of the RMS AE signal power in close correlation to the characteristic of the state of wear. Cutting tests were conducted to determine the amplitude relationship between RMS AE and cutting parameters. It is shown that RMS AE is quite sensitive to the dynamic incremental changes in the friction and the wear flat mechanism active in machining processes.

Analysis of tool wear effect on chatter stability in turning

Abstract This study establishes an analytical basis for the prediction of chatter stability in the turning process in the presence of wear flat on the tool flank. The components contributing to the forcing function in the machine vibration dynamics are analyzed in the context of cutting force, contact force and Coriolis force. In this way, the effects of the displaced workpiece volume at the wear flat as well as the workpiece rotation in conjunction with its radial compliance can be incorporated in describing the motion of the vibration system. Laplace domain analysis provides the analytical solution for the limits of stability in terms of the machine characteristics, structural stiffness, cutting stiffness, specific contact force, cutting conditions and cutter geometry. Stability plots are presented to relate stiffness ratio to cutting velocity in the determination of chatter stability. Machining experiments at various cutting conditions were conducted to identify the characteristic parameters involved in the vibration system and to verify the analytical stability limits. The extent of tool wear effect and Coriolis effect on the stability of machining is discussed.

Milling force convolution modeling for identification of cutter axis offset

Abstract This paper discusses the application of a convolution integral force model to the identification of the geometry of cutter axis offset in milling operations. This analysis builds upon the basis of linear decomposition of elemental local cutting forces into a nominal component and an offset-induced component. The convolution of each elemental local cutting force component with the chip width density in the context of cutter angular position provides an integral expression for the total cutting forces. By virtue of the convolution integration property, the total cutting forces in the frequency domain can be derived as closed-form functions of the cutting pressure constants, various cutting conditions, as well as the cutter offset geometry. Subsequently, the magnitude and phase angle of cutter axis offset are shown to be algebraic and explicit functions of the Fourier series coefficients of cutting forces at the spindle frequency. Following the theoretical analysis, experimental study is discussed to illustrate the implementation procedure for offset identification, and frequency domain data are presented to verify the analytical results. Potential industrial applications of this work include the real-time monitoring of dynamic cutter runout and the in-process compensation for the loss of tolerance or finish using automatic controls based on the feedback information of offset magnitude and phase angle.