The derivation and implementation of an algorithm that calculates exit order sequence (EOS) as a planar milling burr prediction tool is presented. EOS expresses the orientation of a cutter relative to the workpiece in terms of the exit order of three points describing the major and minor cutting edges. EOS calculations along the contours of a CAD model are based upon an instantaneous, Cartesian frame of reference centered on the tool spindle axis and oriented in the feed direction. The scheme provides accurate and robust EOS calculations and introduces a “worst-case” approach to select a unique EOS from overlapping tool exit conditions.
It has been recognized that on ductile materials, high radial tool engagement conditions produce the largest burrs in face milling operations. Ideally, high radial engagement is avoided by configuring the tool path such that the mill is kept within the feasible offset region –a region that satisfies user requirements– of a given workpiece geometry and material. Fulfillment of this condition, however, is often difficult due to geometrical complexity of the manufactured components and cycle time constraints. For this reason there is great motivation to minimize burr formation at high tool engagement. In this paper, the mechanisms of burr formation and the effect of cutting parameters under high radial engagement are investigated, and possible burr minimization strategies are discussed. To this end, face milling tests results conducted by CODEF members and other researchers on different materials were examined. The proposed minimization strategies focus on the optimization of the following parameters: depth of cut, insert nose sharpness, lead angle, and axial rake angle, to promote a transition from primary to secondary burr formation.
High speed face milling test were performed on two aluminum silicon alloys currently used in automotive engine production to study the effect of cutting parameters and tool geometry in edge quality. Axial Rake and Radial Rake angles were varied to assess their effect in burr formation, as well as cutting speed, feedrate and depth of cut. Significant improvements in edge quality were obtained by optimizing these geometrical and kinematical parameters.
Control of surface contamination in the form of small particles is becoming a major priority in conventional manufacturing processes, due to the higher sensitivity of mechanical assemblies to contamination-related failures. At the same time, the complexity of workpieces is increasing, making the removal of contaminants more difficult. Thus there is a critical need to facilitate cleaning in order to reduce the high costs and expenditure of natural resources required for cleaning operations. The objective of this paper is to present strategies to reduce or prevent solid particle contamination by manufacturing by-products throughout the product development and manufacturing chain, via cleaning-conscious design feedback to product developers in the context of Design for Cleanability (DFC) and improved process planning for manufacturing. We also show preliminary results on the effect of cutting parameters on chip size and morphology when machining cast aluminium silicon alloy, in an attempt to control chips for easier removal.
Removal of burrs at cross-drilled hole intersections is often tedious and expensive due to limited accessibility. Automated edge finishing of crossholes has been practiced successfully using robot-assisted, flexible abrasive brush deburring, and non-traditional, mass finishing methods such as electrochemical deburring (ECD), abrasive slurry, and thermal deburring. These methods are very efficient but most require specialized equipment and dedicated cleaning operations to remove chemicals or trapped brush bristles. The Orbitool is an on-line, localized deburring alternative to brushes recently developed by JWDone Company. The Orbitool is a mechanized cutting tool with carbide edges specifically designed for crosshole deburring. Mechanized cutting provides greater selectivity and control of dimensional specifications compared to brushing and mass finishing methods. Furthermore, it can be implemented using existing machine tool equipment and cleaning procedures. As with any deburring tool, its desired capability is burr removal in the shortest time possible while meeting dimensional and surface quality requirements. To this end, process maps of chamfer width and surface roughness of the deburred edges, plotted against process parameters, were developed in this study. Workpieces consisted of Al 6061 T6 bars with zero-offset, perpendicular cross-holes with a diameter of 7.94 mm (5/16 in.). The experiments were conducted using Orbitools with a diameter of 6.35 mm (1/4 in.) and 36 cutting edges. The effect of the process inputs and their mutual interaction was assessed using Taguchi methods. The results show that proper selection of process parameters yield consistent and effective removal of burrs at cross-drilled intersections while achieving surface roughness values that range from 15 to 65 ?m at the chamfers.
We developed computer-aided planning tools for waterjet cleaning processes incorporating experimental results. We designed experiments to determine the influence of key waterjet parameters on cleaning effect and devised a computer-aided visualization and optimization scheme incorporating these parameters. In addition, we developed a particle dynamics model to simulate local waterjet interaction with target surfaces. Finally, we developed a model to predict water traps inside the workpieces based on layered volume segmentation. Our tools will aid designers and process planners in achieving efficient cleaning of geometrically complex workpieces in a high volume manufacturing environment.
The quality of machined components in the aerospace and automotive industries has become increasingly critical in the past years because of greater complexity of the workpieces, miniaturization, usage of new composite materials, and tighter tolerances. This trend has put continual pressure not only on improvements in machining operations, but also on the optimization of the cleanability of parts. The paper reviews recent work done in these areas at the University of California-Berkeley. This includes: Finite element modeling of burr formation in stacked drilling; development of drill geometries for burr minimization in curved-surface drilling; development of a enhanced drilling burr control chart; study of tool path planning in face-milling; and cleanability of components and cleanliness metrics.
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