Numerical Investigation of Heat Partition in the Primary Shear Zone in Metal Cutting

The fraction of heat generated in the primary shear zone that is conducted into the workpiece is a key factor in the calculation of the shear plane temperature and in calculating the cutting forces based on material flow stress. Accurate analytical, numerical, or experimental determination of this heat partition coefficient is not available to date. This study utilizes a new approach to obtain the heat partition coefficient for the primary shear zone using results for strain, strain rate, and temperature distribution obtained from a coupled thermo-mechanical finite element analysis of machining. Different approaches, using strain rate and equivalent strain, are used for calculating the total plastic power in the primary shear zone and the heat generated by plastic deformation below the plane of the machined surface. The heat carried away by the workpiece is obtained by calculating the heat flow by convection in regions where the conduction is expected to be small. We have used an elastic perfectly plastic material model and constant thermal properties to mimic the assumptions used in analytical models. The fraction of the total heat generated in the primary shear zone that is conducted into the machined workpiece is found and compared to the prediction of different analytical models. It is found that for most of the cutting conditions, the values of heat partition coefficient are closest to those provided by Weiner’s model.

Particle Dampers for Workpiece Chatter Mitigation

It is well known that the chatter stability of a machining process can be improved by increasing the structural damping of the system. To date this approach has been effectively used on various components of the machining system, for example boring bars, milling tools, and the machine structure itself. Various damping treatments have been proposed, including tuned vibration absorbers, active methods, and impact dampers. However, to date there has been little or no work to investigate the issue of particle dampers for this application. This special class of damper comprises a container of thousands of small granular particles which dissipate energy by friction and impact when the container vibrates. The resulting behaviour is highly nonlinear but can provide very high levels of damping across a wide frequency range. In the present study, particle dampers were applied to a workpiece to mitigate chatter during milling, and the limiting critical depth of cut was increased by an order of magnitude. This article gives an overview of the particle damper’s behaviour and key design parameters. Cutting trials employing the device are then described.

Computer-Integrated Design and Manufacturing of Packaging Machines

Automated packaging machines must be constantly redesigned to accommodate ever changing packing. There is little time to make these changes and no room for error. In this work, computer-integrated design and manufacture of a packaging machine has been conducted. A knowledge base system has been developed, which checks for errors in user input, updates all assemblies per the user input, checks for part interferences in the assembly, holds the new design to accepted design standards, and sends warning messages to the user’s computer screen in the event of a problem. The knowledge base then creates new intelligent part numbers. These part numbers provide the informational link from Engineering to Production as they contain all the new part information needed to make the parts. These part numbers are entered into a program that automatically creates the new tool paths for the CNC mill. The entered part number is automatically milled into the part to insure the correct part was entered. The cost of design and manufacture is then reduced substantially. This knowledge base also extends into sales for quoting and for new job creation which expedites the entire process.

Retrieving Assembly Part Design Using Case-Based Reasoning and Genetic Algorithms

Artificial intelligence (AI) approaches have been successfully applied to many fields. Among the numerous AI approaches, Case-Based Reasoning (CBR) is an approach that mainly focuses on the reuse of knowledge and experience. However, little work is done on applications of CBR to improve assembly part design. Similarity measures and the weight of different features are crucial in determining the accuracy of retrieving cases from the case base. To develop the weight of part features and retrieve a similar part design, the research proposes using Genetic Algorithms (GAs) to learn the optimum feature weight and employing nearest-neighbor technique to measure the similarity of assembly part design. Early experimental results indicate that the similar part design is effectively retrieved by these similarity measures.

Manufacture of Microcantilever Sensors

Mechanical micro machining is an emerging technology with many potential benefits and equally great challenges. The push to develop processes and tools capable of micro scale fabrication is a result of the widespread drive to reduce part and feature size. One important factor that contributes to the ability to machine at the microscale level is the overall size of the machine tool due to the effects of thermal, static, and dynamic stabilities. This paper explores the technical feasibility of miniaturized machine tools capable of fabricating features and parts on the micro scale in terms of depth of cut and part form accuracy. It develops a machine tool and examines its capabilities through benchmarking tests and the making of precision dies for the injection molding of microcantilever parts. The design and configuration of a miniaturized vertical machining center of overall dimension less than 300 mm on a side is presented and the component specifications discussed. The six axis machine has linear positioning resolution of 4 nm by 10 nm by 10 nm, with accuracy on the order of 0.3 μm, in the height, feed, and cross feed directions. The work volume as defined by the ranges of axes travel are 4 mm by 25 mm by 25 mm in the height, feed, and cross feed and 20 degrees in the rotational space. To quantify the performance capability of the miniaturized machine tool as a system, a series of evaluation tests were implemented based on linear and arch trajectories over a range of feed speed and depth of cut conditions. Test results suggest that micro level form accuracy and sub-micron level finish are generally achievable for parts with moderate curvature and gradient in the geometry under selected machining parameters and conditions. An injection mold was made of steel with this machine and plastic microcantilevers fabricated. Plastic microcantilevers are appropriate for sensing applications such as surface probe microscopy. The microcantilevers, made from polystyrene, were 464 to 755 μm long, 130 μm wide and only 6–9 μm thick. They showed very good uniformity, reproducibility, and appropriate mechanical response for use as sensors in surface force microscopy.

Variation Simulation of Fixtured Assembly Processes for Compliant Structures Using Piecewise-Linear Analysis

While variation analysis methods for compliant assemblies are becoming established, there is still much to be done to model the effects of multi-step, fixtured assembly processes statistically. A new method is introduced for statistically analyzing compliant part assembly processes using fixtures. This method yields both a mean and a variant solution, which can characterize an entire population of assemblies. The method, called Piecewise-Linear Elastic Analysis, or PLEA, is developed for predicting the residual stress, deformation and springback variation resulting from fixtured assembly processes. A comprehensive, step-by-step analysis map is presented for introducing dimensional and surface variations into a finite element model, simulating assembly operations, and calculating the error in the final assembly. PLEA is validated on a simple, laboratory assembly and a more complex, production assembly. Significant modeling issues are resolved as well as the comparison of the analytical to physical results.

A Numerical Study of Uncertainty in Stability and Surface Location Error in High-Speed Milling

High-speed milling offers an efficient tool for developing cost effective manufacturing processes with acceptable dimensional accuracy. Realization of these benefits depends on an appropriate selection of preferred operating conditions. In a previous study, optimization was used to find these conditions for two objectives: material removal rate (MRR) and surface location error (SLE), with a Pareto front or tradeoff curve found for the two competing objectives. However, confidence in the optimization results depends on the uncertainty in the input parameters to the milling model (time finite element analysis was applied here for simultaneous prediction of stability and surface location error). In this paper the uncertainty of these input parameters such as cutting force coefficients, tool modal parameters, and cutting parameters is evaluated. The sensitivity of the maximum stable axial depth, blim, to each input parameter at each spindle speed is determined. This enables identification of parameters with high contribution to stability lobe uncertainty. Two methods are used to calculate uncertainty: 1) Monte Carlo simulation; and 2) numerical derivatives of the system eigenvalues. Once the uncertainty in axial depth is calculated, its effect is observed in the MRR and SLE uncertainties. This allows robust optimization that takes into consideration both performance and uncertainty.

Evaluation of Tool Wear Suppressive Ability of Lubricants Usein in Minimum Quantity Lubrication Application in High Speed Machining of Cast Aluminum Alloys

The disadvantages of conventional metalworking fluids such as disposal problems, health problems and economic factors have led to the development of strategies to reduce their amount in metalworking. Recently, Minimum Quantity Lubrication (MQL) technology was developed and it seems to be a suitable alternative for economically and environmentally compatible production. It combines the functionality of lubrication with an extremely low consumption of lubricant and has a potential to replace metalworking fluids application in machining operations. The MQL lubricants are formulated with two major groups of additives; anti-wear (AW) additives and extreme pressure (EP) additives. When such lubricants are applied to the cutting zone, protective layers are formed on the interacting surfaces of the workpiece and the cutting tool. These layers prevent direct contact between the tool and chip surfaces, and, therefore reduce friction forces and tool wear. In order to utilize MQL to its full potential, it is essential to select appropriate lubricant composition for particular work material and machining parameters. The experimental study of different compositions of MQL lubricants is reported. The effectiveness of the lubricants are determined in terms of their ability to protect the cutting tool in high speed machining of cast aluminum alloys, which are widely used in automotive industry. The main objective of this research is to quantitatively evaluate the ability of lubricant’s additive composition to reduce the tool wear. This is reached through the comparison between the tool wear rate measured during the machining of aluminum cast alloy with the application of MQL, and the tool wear rate obtained in dry machining of the same alloy. Two kinds of the lubricants are evaluated; vegetable and synthetic. The content of AW and EP additives in each kind of lubricant was varied on three levels in order to capture the effect of the lubricant’s composition on tool wear. The result of the MQL lubricants evaluation is discussed and the recommendations for optimal lubricant composition are made.

Research of the Relationship Between the Clearance and Wear of Precise Micro Punch and Die

The punch and die operation is widely used for forming and processing of both metal and non-metal sheets due to its ease-of-operation. Moreover, this method is characterized by a higher degree of cost-effectiveness and accuracy as compared to other processing modes, such as casting, forging and metal processing. The typical field of application covers parts manufacturing for timekeepers, vehicles, sheet metals or motors and various thin plates. With the development of IC (Integrated circuit) processing technology, passive components are being increasingly miniaturized, ranging from 0603 (0.06″ × 0.03″) chips to existing 0402 (0.04″ × 0.02″) and 0201 chips. Because of increasing miniaturization of passive components, the smaller aperture of composite paper bags for various IC will be required. The IC chips need to be packaged for sale. The packaging bag has many small apertures to store the chips. Micro punches and dies are use to punch this aperture. The accuracy of aperture for packaging bags, however, depends on the clearance between the punch and die. This study utilizes an Image Vision System to measure the clearance of micro dies and the burr size of processed composite materials in order to estimate which condition is better for micro dies. The relational expression was established between input parameters and outputs via a Neural Network. This can help to anticipate the burr size under any clearance, and contributes to the design and application of smaller punches in the future.

Eliminating Redundant Operations While Improving Part Quality by Modeling Machining Errors

A methodology to predict part quality was applied to the perpendicularity quality of the bell face and main axis of a transmission case. By modeling the quality of different processing sequences, we were able to show that the quality of the part - perpendicularity of critical features - does not improve significantly by performing two-pass machining process instead of a single-pass. This application of our quality methodology required the modeling of additional system errors which were not developed in the earlier version and which were needed to predict certain types of form errors. In addition to improved part quality, changing the existing line to a single-pass process eliminated a bothersome job-setting procedure and tooling costs at the second-pass and increased productivity of a rebalanced line.