Topological model for machining of parts with complex shapes

Complex shapes are widely used to design products in several industries such as aeronautics, automotive and domestic appliances. Several variations of their curvatures and orientations generate difficulties during their manufacturing or the machining of dies used in moulding, injection and forging. Analysis of several parts highlights two levels of difficulties between three types of shapes: prismatic parts with simple geometrical shapes, aeronautic structure parts composed of several shallow pockets and forging dies composed of several deep cavities which often contain protrusions. This paper mainly concerns High Speed Machining (HSM) of these dies which represent the highest complexity level because of the shapes' geometry and their topology. Five axes HSM is generally required for such complex shaped parts but 3 axes machining can be sufficient for dies. Evolutions in HSM CAM software and machine tools lead to an important increase in time for machining preparation. Analysis stages of the CAD model particularly induce this time increase which is required for a wise choice of cutting tools and machining strategies. Assistance modules for prismatic parts machining features identification in CAD models are widely implemented in CAM software. In spite of the last CAM evolutions, these kinds of CAM modules are undeveloped for aeronautical structure parts and forging dies. Development of new CAM modules for the extraction of relevant machining areas as well as the definition of the topological relations between these areas must make it possible for the machining assistant to reduce the machining preparation time. In this paper, a model developed for the description of complex shape parts topology is presented. It is based on machining areas extracted for the construction of geometrical features starting from CAD models of the parts. As topology is described in order to assist machining assistant during machining process generation, the difficulties associated with tasks he carried out are analyzed at first. The topological model presented after is based on the basic geometrical features extracted. Topological relations which represent the framework of the model are defined between the basic geometrical features which are gathered afterwards in macro-features. Approach used for the identification of these macro-features is also presented in this paper. Detailed application on the construction of the topological model of forging dies is presented in the last part of the paper

Biomimetic Design and Fabrication of Interior Architecture of Tissue Scaffolds Using Solid Freeform Fabrication

Modeling, design and fabrication of tissue scaffolds with intricate architecture, porosity and pore size for desired tissue properties presents a challenge in tissue engineering. This paper will present the details of our development in designing and fabrication of the interior architecture of scaffolds using a novel design approach. The Interior Architecture Design (IAD) approach seeks to generate scaffold layered freeform fabrication tool path without forming complicated 3D CAD scaffold models. This involves: applying the principle of layered manufacturing to determine the scaffold individual layered process planes and layered contour; defining the 2D characteristic patterns of the scaffold building blocks (unit cells) to form the Interior Scaffold Pattern; and the generation of process tool path for freeform fabrication of these scaffolds with the specified interior architecture. Feasibility studies applying the IAD algorithm to example models and the generation of fabrication planning instructions will be presented.Mechanical Engineerin

Development Of Generative Computer-Aided Process Planning For Cnc Milling Parts_Pramodkumar S Kataraki

The important aspect of computer-aided process planning (CAPP) is to recognize part’s surfaces and features to aid downstream intelligent manufacturing. The automatic recognition of surfaces and features will lead to successful attainment of generative CAPP. Feature recognition works performed so far do not recognize all regular form and freeform volumetric features, and do not generate delta volume (DV) for the recognized features. The works do not address the classification of freeform volumetric features. So there is a need for novel classification of features and approach to auto-recognize features so as to auto-generate DV for each recognized feature for the attainment of generative CAPP. An effort has been made to novel classify the features into regular form and freeform features which are further sub-classified into surface features and volumetric features. The overall delta volume (ODV) is classified into SDVF, SDVT, SDVF filled region, SDV-VF, and SDVR. Algorithm is developed to auto-recognize surfaces of a milling part and auto-generate ODV. The algorithm auto-generates exploded view of ODV, auto-labels the sub-delta volumes (SDVs) and determines the level of complexity to manufacture a part. The generated ODV is validated by percentage error (%) and machining of parts. The algorithm selects the type of machining operation to be performed and auto-allocates each SDV-VF to the face it belongs to. The surface and volumetric features of a part are successfully auto-recognized and estimated DV, results table are auto-generated. The SDVT developed contiguous to SDVF for freeform faces, overcomes the complex DV for roughing process. The DV discontinuity and overlap limitation that occurred in few studies are eliminated. The designation of feature faces and colour coding of faces of SDV-VF expresses the type of feature present in a part. The validation of developed algorithm by percentage error (%) shows error less than 0.1% and the machine selection criteria suggests user the type of milling machine needed to manufacture a part based on level of complexity

From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

The aim of this paper is to provide an introduction and overview of recent advances in the key technologies and the supporting computerized systems, and to indicate the trend of research and development in the area of computational numerical control machining. Three main themes of recent research in CNC machining are simulation, optimization and automation, which form the key aspects of intelligent manufacturing in the digital and knowledge based manufacturing era. As the information and knowledge carrier, feature is the efficacious way to achieve intelligent manufacturing. From the regular shaped feature to freeform surface feature, the feature technology has been used in manufacturing of complex parts, such as aircraft structural parts. The authors’ latest research in intelligent machining is presented through a new concept of multi-perspective dynamic feature (MpDF), for future discussion and communication with readers of this special issue. The MpDF concept has been implemented and tested in real examples from the aerospace industry, and has the potential to make promising impact on the future research in the new paradigm of intelligent machining. The authors of this paper are the guest editors of this special issue on computational numerical control machining. The guest editors have extensive and complementary experiences in both academia and industry, gained in China, USA and UK

Modeling and Verification of Error Propagation in Integrated Additive/Subtractive Multi-Directional Direct Manufacturing

Integrated additive-subtractive manufacturing, when applied in the framework of SolidFreeform-Fabrication (SFF) allows the fabrication of functional parts on single platform, directly from its computer model. Reduction in process complexity and total processing steps is ensured by multi-directional material deposition and machining. However, due to shift in the datum location in reorientation steps and sequential addition of material in the form of layers, the CAD process intent is not exactly replicated. This leads to inclusion of dimensional errors. Machining in order to eliminate the errors as frequent as layer deposition is highly expensive and can be avoided by estimation of errors and varying process parameters, and/or performing machining after a set of layers are deposited. This paper proposes a state space model for modeling the error propagation due to linear as well as angular variation in the datum. The model is based on identification of possible sources of error, mechanism of error inclusion and influence of process parameters. An experiment performed to determine parameters of error modeling has been reported.Mechanical Engineerin

Process planning for an Additive/Subtractive Rapid Pattern Manufacturing system

This dissertation presents a rapid manufacturing process for sand casting patterns using a hybrid additive/subtractive approach. This includes three major areas of research that will enable highly automated process planning; a critical need for a rapid methodology. The first research area yields a model for automatically determining the locations of layers, given the slab height, material types and part geometry. Layers are chosen such that it will avoid catastrophic failures and poor machining conditions in general. First, features that are possible thin material machining positions are defined, and methods for detecting these feature positions from an STL model are studied. Next, a layer thickness calculation model is presented according to positions of these features. The second area focuses on tools and parameters for the subtractive side of processing each layer. A tool size and machining parameter selection model is presented that can automatically select tool sizes and machining parameters, given layer thickness, part geometry, and material types. Machining strategies and related machining parameters are studied first. Then the method for Stepdown parameter calculation is presented. Finally, an algorithm based on both accessibility and machining efficiency is proposed for the selection of tool sizes for the rough cutting operation, finish cutting operation and optional semi-rough cutting operation. The final research area focuses on a cutting force analysis for thin material machining with additional layer thickness & tool size interaction. Popular cutting force models are reviewed, and a suitable model for cutting force calculation in this process is evaluated. Then, a cantilever beam model is used to analyze the thin material machining failure problem, and a minimum layer thickness model is presented. Third, a combined layer thickness & tool size model is constructed based on the machining tool deflection under cutting forces. This rapid pattern manufacturing process and related software has been implemented, and experimental data is presented to illustrate the efficacy of this system and its process planning methods

Integrated process planning for a hybrid manufacturing system

A hybrid manufacturing system integrated CNC machining and laser-aided layered deposition and achieves the benefits of both processes. In this dissertation, an integrated process planning framework which aims to automate the hybrid manufacturing process is investigated. Critical components of the process planning, including 3D spatial decomposition of the CAD model, improvement of the toolpath generation pattern, repairing strategies using a hybrid manufacturing system, etc., are discussed --Abstract, page iv