Automated Digital Machining for Parallel Processors

When a process engineer creates a tool path a number of fixed decisions are made that inevitably produce sub-optimal results. This is because it is impossible to process all of the tradeoffs before generating the tool path. The research presents a methodology to support a process engineers attempt to generate optimal tool paths by performing automated digital machining and analysis. This methodology automatically generates and evaluates tool paths based on parallel processing of digital part models and generalized cutting geometry. Digital part models are created by voxelizing STL files and the resulting digital part surfaces are obtained based on casting rays into the part model. Tool paths are generated based on a general path template and updated based on generalized tool geometry and part surface information. The material removed by the generalized cutter as it follows the path is used to obtain path metrics. The paths are evaluated based on the path metrics of material removal rate, machining time, and amount of scallop. This methodology is a parallel processing accelerated framework suitable for generating tool paths in parallel enabling the process engineer to rank and select the best tool path for the job

Tool selection and path planning in 3-axis rough machining

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1999.Includes bibliographical references (p. 72-77).by Mahadevan Balasubramaniam.S.M

Automatic tool path generation for multi-axis machining

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.Includes bibliographical references (leaves 67-72).We present a novel approach to CAD/CAM integration for multi-axis machining. Instead of redefining the workpiece in terms of machining features, we generate tool paths directly by analyzing the accessibility of the surface of the part. This eliminates the problem of feature extraction. We envision this as the core strategy of a new direct and seamless CAD/ CAM system. We perform the accessibility analysis in two stages. First, we triangulate the surface of the workpiece and perform a visibility analysis from a discrete set of orientations arranged on the Gaussian Sphere. This analysis is performed in object space to ensure reliability. For each triangle, a discrete set approximation of the accessibility cone is then constructed. Next, a minimum set cover algorithm like the Quine-McCluskey Algorithm is used to select the minimum set of orientations from which the entire workpiece can be accessed. These set of orientations correspond to the setups in the machining plan, and also dictate the orientation in which the designed part will be embedded in the stock. In particular, we bias the search for setups in favor of directions from which most of the part can be accessed i.e, the parallel and perpendicular directions of the faces in the workpiece. For each setup, we select a set of tools for optimal removal of material. Our tool-path generation strategy is based on two general steps: global roughing and facebased finishing. In global roughing, we represent the workpiece and stock in a voxelized format. We perform a waterline analysis and slice the stock into material removal slabs. In each slab, we generate zig-zag tool paths for removing bulk of the material. After gross material removal in global roughing, we finish the faces of the component in face-based finishing. Here, instead of assembling faces into features, we generate tool paths directly and independently for each face. The accessibility cones are used to help ensure interference- free cuts. After the tool paths have been generated, we optimize the plan to ensure that commonalities between adjacent faces are exploited.by Laxmiprasad Putta.S.M

Optimization of Three-Axis Vertical Milling of Sculptured Surfaces

A tool path generation method for sculptured surfaces defined by triangular meshes is presented in this thesis along with an algorithm that helps determine the best type of cutter geometry to machine a specific surface. Existing tool path planning methods for sculptured surfaces defined by triangular meshes require extensive computer processing power and result in long processing times mainly since surface topology for triangular meshes is not provided. The method presented in this thesis avoids this problem by offsetting each triangular facet individually. The combination of all the individual offsets make up a cutter location surface. A single triangle offsetting results in many more triangles; many of these are redundant, increasing the time required for data handling in subsequent steps. To avoid the large number of triangles, the proposed method creates a bounding space to which the offset surface is limited. The original surface mesh describes the bounding surface of a solid, thus it is continuous with no gaps. Therefore, the resulting bounding spaces are also continuous and without gaps. Applying the boundary space limits the size of the offset surface resulting in a reduction in the number of triangular surfaces generated. The offset surface generation may result in unwanted intersecting triangles. The tool path planning strategy addresses this issue by applying hidden-surface removal algorithms. The cutter locations from the offset surface are obtained using the depth buffer. The simulation and machining results show that the tool paths generated by this process are correct. Furthermore, the time required to generate tool paths is less than the time required by other methods. The second part of this thesis presents a method for selecting an optimal cutter type. Extensive research has been carried out to determine the best cutter size for a given machining operation. However, cutter type selection has not been studied in-depth. This work presents a method for selecting the best cutter type based on the amount of material removed. By comparing the amount of material removed by two cutters at a given cutter location the best cutter can be selected. The results show that the optimal cutter is highly dependent on the surface geometry. For most complex surfaces it was found that a combination of cutters provides the best results

Emergent Structure Detection for Multi-Axis Machining

This paper examines the phenomenon of emergent structures that occur in the transient stock material during multi-axis rough machining from a plurality of fixed orientations. Taking the form of thin webs and strings, emergent structures are stock material conditions that can lead to catastrophic failure during machining, even when tool path verification is successful. We begin by discussing the motivation for use of fixed orientations in multi-axis machining using multiple automated setups via rotary axes, which enables fast processing and ‘first part correct’ machining. Next, we demonstrate how unintended emergent structures occur in this paradigm of machining and can lead to catastrophic failure of the tool or work piece. Our original work focuses on the problem of geometric detection of these structures during process planning and prior to tool path planning, to the end of altogether avoiding emergent structure formation. To quickly simulate the machining process, we present an object-space method for determining the transient state of stock material based on the inverse tool offset. To identify emergent structures within this transient stock state, we propose a metric based on the medial axis transformation. Finally, we present our implementation of these methods and demonstrate realtime computation appropriate for an optimization scheme to eliminate emergent structures. Our methods provide consistent and logical results, as demonstrated with several freeform component examples. This work enables the development of robust algorithms for autonomous tool path planning and machining in multi-axis environments

Manufacturability analysis for non-feature-based objects

This dissertation presents a general methodology for evaluating key manufacturability indicators using an approach that does not require feature recognition, or feature-based design input. The contributions involve methods for computing three manufacturability indicators that can be applied in a hierarchical manner. The analysis begins with the computation of visibility, which determines the potential manufacturability of a part using material removal processes such as CNC machining. This manufacturability indicator is purely based on accessibility, without considering the actual machine setup and tooling. Then, the analysis becomes more specific by analyzing the complexity in setup planning for the part; i.e. how the part geometry can be oriented to a cutting tool in an accessible manner. This indicator establishes if the part geometry is accessible about an axis of rotation, namely, whether it can be manufactured on a 4th-axis indexed machining system. The third indicator is geometric machinability, which is computed for each machining operation to indicate the actual manufacturability when employing a cutting tool with specific shape and size. The three manufacturability indicators presented in this dissertation are usable as steps in a process; however they can be executed alone or hierarchically in order to render manufacturability information. At the end of this dissertation, a Multi-Layered Visibility Map is proposed, which would serve as a re-design mechanism that can guide a part design toward increased manufacturability