Influence of the stress,strain, and temperature on the surface roughness of an AlSl 52100 steel due to an orthogonal cut

In recent years, the finite element method (FEM) has become the main tool for simulating the metal cutting process because research based on trial and error is time consuming and requires high investment. Early studies were done by different investigators. In this research AISI 52100, hardened steel (62 HRC) was selected for an orthogonal machining process as well as metal cutting simulation using the software DEFORM-2D. This software is based on a forging process and has been adapted to an orthogonal machining process. The results of simulated cutting forces were compared with experimental cutting force data to validate the orthogonal cut simulation. Also, the surface roughness was measured, and the influence of the stress, strain, and temperature on the surface roughness was studied.     

Prediction of part orientation error tolerance of a robotic gripper

This paper presents a model which predicts the part orientation error tolerance of a three-fingered robotic gripper. The concept of “self-alignment” is introduced, where the gripper uses the grasping process to bring the workpiece into its final state of orientation. The gripper and part are represented mathematically, and initial contact locations upon grasp closure determined. This information is used to solve for the contact forces present, and criteria are developed to determine if beneficial part motion resulting in self-alignment is expected. The results are visualized via a boundary projected on a reference plane below the part. The model is validated experimentally with a number of part configurations with favorable results. This method presents a useful tool by which the mechanical designer can quantitatively predict the performance of an intuitively designed gripping system.     

A statistical approach to the optimization of a laser-assisted micromachining process

The objective of this study is to optimize a laser-assisted micro-grooving process designed for micromachining of difficult-to-machine materials such as hard mold/die steels and ceramics. The process uses a relatively low power continuous wave laser beam focused directly in front of a micro-grooving tool to thermally soften the material thereby lowering the cutting forces and associated machine and tool deflections. However, the use of laser heating can produce a detrimental heat-affected zone (HAZ) in the workpiece surface layers. Consequently, the laser and micro-grooving parameters need to be optimized in order to achieve the desired thermal softening effect while minimizing the formation of a HAZ in the material. Although thermal and force models for the hybrid process have been developed for possible use in process optimization, they are computationally intensive and are not accurate enough to produce reliable results. We overcome these deficiencies using a statistical approach. First, easy-to-evaluate metamodels are developed to approximate the complex engineering models. Then, the metamodels are statistically adjusted using real data from the process to make more accurate predictions. The optimization is then carried out on this statistically adjusted metamodels. The optimization strategy is experimentally verified and shown to yield good results.     

Laser assisted micro-milling of hard-to-machine materials

There is a need for developing hybrid micro-manufacturing processes capable of generating three-dimensional micro-scale features in hard-to-machine materials. This paper deals with the development of the laser assisted micro-milling process for which a novel 4-axis machine has been designed and built. This paper presents the results of experiments on laser assisted micro-milling of hardened A2 tool steel (62 HRc). The dimensional accuracy of the micro-milled feature and surface finish obtained with and without laser heating are compared and discussed. Scientific explanations for the different observations are given.     

Mechanistic models of thrust force and torque in step-drilling of Al7075-T651

In the aerospace industry, burr removal is an important and expensive part of the manufacturing process. One approach to minimizing burrs is to lower the thrust force in drilling through suitable modification of the drill geometry such as the use of step drills. This paper focuses on the modeling of thrust force and torque for step drills. A mechanistic model capturing the various material removal mechanisms, i.e. oblique cutting, orthogonal cutting, and indentation, active on different sections of the step drill is developed. Subsequently, a series of experiments is conducted to calibrate and validate the model. The validation results show that the predicted thrust and torque values are in good agreement with measured values, although the torque is slightly underestimated. The validated model was further used to investigate the effects of step drill geometry parameters on the thrust force and torque. The model predictions suggest that the thrust force increases and the torque decreases for larger secondary point angles and inner diameters.     

Effect of plastic side flow on surface roughness in micro-turning process

Kinematic roughness-based surface finish prediction is known to often under-predict the measured surface roughness in turning process, especially at small (micron level) feed rates. It has also been observed that the surface roughness in micro-turning decreases with feed, reaches a minimum, and then increases with further reduction in feed. This paper presents a model for predicting the surface roughness in micro-turning of Al5083-H116 alloy that takes into account the effects of plastic side flow, tool geometry, and process parameters. The model combines these effects with more accurate estimation of the average flow stress of Al5083-H116 at micron scale of deformation with the help of a previously reported strain gradient-based finite element model. The surface roughness model is evaluated through a series of micro-turning experiments. The results show that the model can predict the surface roughness in micro-turning quite well. It is shown that the commonly observed discrepancy between the theoretical and measured surface roughness in micro-turning is mainly due to surface roughening caused by plastic side flow. Further, it is shown that the increase in roughness at low feed can be attributed to the increased side flow caused by strain gradient-induced strengthening of the material directly ahead of the tool.     

Determination of minimum clamping forces for dynamically stable fixturing

This paper presents a model-based framework for determining the minimum required clamping forces that ensure the dynamic stability of a fixtured workpiece during machining. The framework consists of a dynamic model for simulating the vibratory behavior of the fixtured workpiece subjected to time- and space-varying machining loads, a geometric model for capturing the continuously changing geometry and inertia of the fixture–workpiece system during machining, a static model for determining the localized fixture–workpiece contact deformations due to clamping, a model for checking the dynamic stability of the fixtured workpiece, and a model for determining the optimal set of clamping forces that satisfies the stability criteria for a given machining operation. The clamping force optimization problem is formulated as a bilevel nonlinear programming problem and solved using the Particle Swarm Optimization (PSO) technique featuring computational intelligence. A simulation example solved using the developed approach reveals that the minimum required clamping forces for dynamically stable fixturing are significantly affected by the fixture–workpiece system dynamics and its continuous change during machining due to the material removal effect.     

Fixture Clamping Force Optimisation and its Impact on Workpiece Location Accuracy

Workpiece motion arising from localised elastic deformation at fixture-workpiece contacts owing to clamping and machining forces is known to affect significantly the workpiece location accuracy and, hence, the final part quality. This effect can be minimised through fixture design optimisation. The clamping force is a critical design variable that can be optimised to reduce the workpiece motion. This paper presents a new method for determining the optimun clamping forces for a multiple clamp fixture subjected to quasu-static machining forces. The method uses elastic contact mechanics models to represent the fixture-workpiece contact and involves the formulation and solution of a multi-objective constrained oprimisation model. The impact of clamping force optimisation on workpiece location accuracy is analysed through examples involving a 3-2-1 type milling fixture.     

Analysis of Reactions and Minimum Clamping Force for Machining Fixtures with Large Contact Areas

This paper presents a model for analysing the reaction forces and moments for machining fixtures with large contact areas, e.g. a mechanical vice. Such fixtures transmit torsional loads in addition to normal and tangential loads and thus differ from fixtures using point or line contacts. The model is developed using a contact mechanics approach where the workpiece is assumed to be elastic in the contact region and the fixture element is treated as rigid. Closed-form contact compliance solutions for normal, tangential, and torsional loads are used to derive the elastic deformation model for each contact. A minimum energy principle is used to solve the multiple contact problem yielding unique predictions of the fixture–workpiece contact forces and moments due to clamping and machining forces. This model is then used to determine the minimum clamping force necessary to keep the workpiece in static equilibrium during machining. An example is given to demonstrate its effectiveness in analysing the clamping performance of a mechanical vice during machining.