An Experimental Investigation of the Crack Growth Phenomenon for Drilling of Fiber-Reinforced Composite Materials

An experimental study has been conducted to study the crack growth phenomenon that occurs while drilling fiber-reinforced composite materials (FRCM), specifically unidirectional (UD) carbon fiber/epoxy resin. It uses an experimental setup that exploits the technology of video to understand the complete crack growth phenomenon as the drill emerges from the exit side of the workpiece. Significant damage mechanisms are observed and defined, and correlations between the average exit drill forces and the crack tip position are shown. Instantaneous forces as they vary along the orientation of the cutting edges are identified in terms of their contribution to the crack propagation.

A Dual-Mechanism Approach to the Prediction of Machining Forces, Part 2: Calibration and Validation

The Dual-Mechanism Machining Force Model (DMMFM) developed in Part 1 of this paper is calibrated through a specially developed algorithm, then validated. The calibration results are used to study the total machining force predictive capabilities of both the traditional lumped shearing model and the DMMFM. It is shown that the Dual-Mechanism Approach contributes greatly to our ability to both physically explain the trends in the machining force data and to understand their implications. This is achieved through an interpretation of the individual rake face and clearance face forces that are predicted using the DMMFM. The interpretation is based on the relations of these rake face and clearance face forces to the process inputs resulting from their effects on the DMMFM coefficients through thermal energy generation and temperature, shear-strain level and shear-strain rate. Some implications of the knowledge of the individual rake face and clearance face forces, as predicted by the DMMFM, are also discussed.

A Mechanistic Approach to Predicting the Cutting Forces in Drilling: With Application to Fiber-Reinforced Composite Materials

In this paper models are developed to predict the thrust and torque forces at the different regions of cutting on a drill. The mechanistic approach adopted to develop these models exploits the geometry of the process, which is independent of the workpiece material. The models are calibrated to a particular material using the well-established relationships between chip load and cutting forces, modified to take advantage of the characteristics of the drill point geometry. The models are validated independently for the cutting lips and the chisel edge for drilling both metals and fiber-reinforced composite materials for a wide range of machining conditions and drill geometry. While the cutting-lips model predictions agree well with the experimental data for both materials, only the chisel-edge model proposed for metals agrees well with the experimental data.

A Dual-Mechanism Approach to the Prediction of Machining Forces, Part 1: Model Development

A cutting-process model addressing the chip removal and edge ploughing mechanisms separately yet simultaneously is presented. The model is developed such that it is readily applicable in an industrial setting, its coefficients have physical meaning, and it can be calibrated with a concise quantity of orthogonal cutting data. The total cutting and thrust forces are each the summation of its individual components acting on the rake face and clearance face. These components are calculated using the rake and effective clearance angles from the normal and friction forces acting on each of these tool surfaces. These normal and friction forces are calculated by the chip removal and edge ploughing portions of the model, respectively, using four empirical coefficients. To calculate the clearance face forces, the interference volume is required, the calculation of which is based on a geometrical representation of the clearance face interference region. This representation is characterized in part by the depth of tool penetration, which is influenced by thermal energy generation and is therefore determined using a fifth empirical model.

A Model for the Prediction of Bore Cylindricity During Machining

In this paper, a model is developed for computation of bore cylindricity of machined cylinder bores. The model takes into account the effect of cutting process variables and the bore design on bore cylindricity. Surface error, which is a measure of the lack of bore cylindricity, is caused by both the elastic deflection of the bore wall due to cutting forces and the thermal expansion of the bore during machining. The effect of both the cutting forces and the bore temperature is included in the model. Experiments have been conducted to measure the bore cylindricity using an Incometer device. Comparisons between the shape and magnitude of predicted and measured surface error show a good agreement.

Temperature Distribution in a Hollow Cylindrical Workpiece During Machining: Theoretical Model and Experimental Results

In this paper, an analytical model is developed for computation of the temperature distribution in a hollow cylindrical workpiece during machining with a single point tool. Such a model is useful for prediction of machined surface error arising from thermal expansion of the workpiece during machining. The model considers the interface between the tool and the workpiece to be a helically moving volumetric heat source. The governing equation satisfied by the temperature field, along with the appropriate boundary and initial conditions, is solved using the method of integral transforms. The experimental test facility used for the conduct of experiments for measurement of the temperature response in a cylindrical workpiece, namely a cylinder bore, during machining is discussed. The results from tests conducted using a laser as a heat source to verify the analytical model for temperature field are then presented. Several cylinder boring tests have been conducted, and the results from these tests along with the analysis performed with the temperature data to calibrate the temperature model are then discussed. Comparisons between predicted and measured temperature response in a cylinder bore during machining show good agreement.

The Effects of Variable Speed Cutting on Vibration Control in Face Milling

This paper discusses the use of variable speed cutting for vibration control in the face milling process. Both simulation and experimental results show that the self-excited vibrations that can occur during constant speed cutting, and hence put limitation on the possible size of cut, can be suppressed by continuously varying the spindle speed. Through both analytical and experimental studies, the shape of variable speed trajectory has been examined, in terms of both the trackability by the spindle servo system and performance in terms of vibration suppression. It was found that a sinusoidal wave because of its acceleration and jerk characteristics can be tracked more precisely than some other periodic waves. The dynamic face milling force model was used to study the effects of speed trajectory parameters, namely, the frequency and amplitude. The results, in general, show the method to be fairly robust to the specific nature of the machining situation in terms of both processing conditions and system dynamics. Speed trajectory design was, however, shown to be somewhat dependent upon the nominal cutting speed and dominant frequencies of the system.

A Methodology for Integrated Quality Systems

This paper proposes a methodology for the design of a system for planning and controlling the quality of products and processes. The system considers the relationships of quality-related parameters along the stages of a product life cycle. Parameters include material properties, process parameters, product quality characteristics, and product performance in use. The methodology is based on modeling the transformation taking place at every stage and on the design of quality control windows which perform all the functions of a control cycle. Several applications of the methodology are described.

An Integrated Quality Systems Approach to Quality and Productivity Improvement in Continuous Manufacturing Processes

An integrated quality systems methodology is presented as a framework within which the concepts of process control can be used to improve quality and productivity. The process is mathematically described by stochastic time series models which statistically describe how inputs and outputs interact. Several different methods for fault identification, including autocorrelation checks of the model residuals, forecasting prediction intervals, and the cusum chart are compared in terms of relative performance. A helix cable manufacturing process is simulated and analyzed by the methodology and faults are identified and suggestions are made for process improvement. Through the simulation these time series control chart methods are shown to be much more effective than conventional methods such as Shewhart control charts.

An Improved Method for Cutting Force and Surface Error Prediction in Flexible End Milling Systems

As more emphasis is placed on quality and productivity in manufacturing, it becomes necessary to develop models that more accurately describe the performance of machining processes. An improved model for the prediction of the cutting force system and surface error in end milling has been developed and has been implemented on the computer. This enhanced model takes into account the effect of system deflections on the chip load, and solves for the chip load that balances the cutting forces and the resulting system deflections. Such a model allows for the evaluation of cuts in which deflections significantly effect the chip load. The flexible system model predictions of forces and surface error are compared against both measured and rigid system model-predicted values associated with the machining conditions for experiments performed on the 390 casting aluminum alloy. It is shown that the enhanced chip load model gives predictions of both cutting force signatures and surface error profiles that are significantly better than the rigid system chip load model developed previously. The fact that system deflections temper the effects of runout, and reduce both peak cutting force and maximum surface error is demonstrated and discussed.

A Mechanistic Model for the Prediction of the Force System in Face Milling Operations

A mechanistic force system model for the face milling process has been developed and implemented on the computer. The model predicts the force system in face milling over a range of cutting conditions, cutter geometries, workpiece, and process geometries including relative positions of cutter to workpiece, spindle tilt, and runout. Machining tests have been conducted for both fly cuting and multitooth cutting with polycrystalline diamond tools on plain surfaces. The 390 casting aluminum alloy has been used as the workpiece material. Force data from these tests were used to estimate the empirical constants of the mechanistic model and to verify its prediction capabilities. Data bases from flycutting tests have been used to predict forces under multitooth face milling and the results indicate good agreement with observed data from multitooth tests.

The Prediction of Surface Accuracy in End Milling

In the end milling process, the cutting forces during machining produce deflection of the cutter and workpiece which result in dimensional inaccuracies or surface error on the finished component. A previously developed mathematical model for the cutting force system in end milling is combined with models for cutter deflection and workpiece deflection so that the surface error profile may be predicted from the machining conditions and geometry and material properties of the cutter and workpiece. Machining experiments are performed on rigid and flexible workpieces of 7075 aluminum to verify the ability of the models to predict surface error. The model predicted surface error profiles are accurate both in magnitude and shape with the difference between measured and predicted surface errors ranging from 5 to 15 percent. This approach for the prediction of surface errors provides a useful aid for the analysis of a variety of end milling process design and optimization problems.

Tool Life Variation and Its Influence on the Development of Tool Life Models

An investigation into the nature of the inherent variation of tool life over a range of cutting conditions for a finish turning process is presented. In this study, tool life is based upon a fixed amount of wear on the clearance face of the tool. The nature of tool life variation as a function of the prespecified wear level is also examined. It was found that the inherent variation of tool life increased as the wear level increased, to the point where an optimum wear level should be definable through an economic optimization of the process. Statistical tests showed that the variance of logarithmically transformed tool life data is not homogeneous over the range of cutting conditions examined. To account for this behavior, the method of weighted least squares is employed in developing tool-life-predicting equations. A comparison between the weighted least-squares method and the ordinary (unweighted) least-squares method is presented. More realistic predicting capabilities resulted by using the weighted method given the inherent behavior of the tool life variation.

Surface Profile Characterization by Autoregressive-Moving Average Models

The surface texture of a machined part is in general composed of three topographical components: waviness, roughness, and errors of form. A new technique for surface profile characterization is introduced which employs parametric stochastic models of the autoregressive-moving average (ARMA) class. The method for obtaining these models for surface profiles is shown by an example. The ARMA modeling technique for profile description is evaluated in three parts to determine its validity, workability, and descriptive power. This analysis is developed through the criteria of ergodicity, sensitivity, and describability. The ergodicity criterion tests the ability of models for physically identical profiles to convey equivalent information. The sensitivity criterion measures the level of detection of topographical differences among profiles by the ARMA model parameters. The descriptive ability of the models is examined by interpreting their parameters in light of the physical components of the profile. To implement this evaluation, ARMA models for eight different milled surfaces are determined and used.