Feature-Based Machining Precedence Reasoning and Sequence Planning

1998 ◽  
Author(s):  
Yong Se Kim ◽  
Eric Wang ◽  
Choong Soo Lee ◽  
Hyung Min Rho
Keyword(s):  
Feature Recognition ◽  
Search Space ◽  
Machining Process ◽  
Planning System ◽  
Process Information ◽  
Computer Aided Process Planning ◽  
Sequence Planning ◽  
Precedence Relations ◽  
Feature Based ◽  
Form Features

Abstract This paper presents a feature-based method to support machining sequence planning. Precedence relations among machining operations are systematically generated based on geometric information, tolerance specifications, and machining expertise. The feature recognition method using Alternating Sum of Volumes With Partitioning (ASVP) Decomposition is applied to obtain a Form Feature Decomposition (FFD) of a part model. Form features are classified into a taxonomy of atomic machining features, to which machining process information has been associated. Geometry-based precedence relations between features are systematically generated using the face dependency information obtained by ASVP Decomposition and the features’ associated machining process information. Multiple sets of precedence relations are generated as alternative precedence trees, based on the feature types and machining process considerations. These precedence trees are further enhanced with precedence relations from tolerance specifications and machining expertise. Machining sequence planning is performed for each of these precedence trees, applying a matrix-based method to reduce the search space while minimizing the number of tool changes. The precedence trees may then be evaluated based on machining cost and other criteria. The precedence reasoning module and operation sequence planning module are currently being implemented within a comprehensive Computer-Aided Process Planning system.

Unified Feature Definition for Feature Based Design and Feature Based Manufacturing

1995 ◽  
Author(s):  
Reinholt Geelink ◽  
Otto W. Salomons ◽  
Fjodor van Slooten ◽  
Fred J. A. M. van Houten ◽  
Huub J. J. Kals
Keyword(s):  
Feature Recognition ◽  
Design Feature ◽  
Geometric Constraints ◽  
Planning System ◽  
Conceptual Graphs ◽  
Computer Aided Process Planning ◽  
Feature Based ◽  
Definition Of ◽  
Feature Based Design ◽  
Interactive Feature

Abstract In this paper, interactive “constraint based feature definition” is used to drive both feature based design and feature recognition. At present, hardly any feature based CAD or CAPP system does offer adequate facilities to easily define application specific features. Feature definition by means of programming is an error prone and difficult task. The definition of new features has to be performed by domain experts in the fields of design and manufacturing. In general they will not be programming experts. This paper elaborates on interactive feature definition, aiming at facilitating the definition of features by non-programming experts. The interactive feature definition functionality is implemented in a re-design support system called FROOM. It supports feature based design. Feature definition is also used in a Computer Aided Process Planning system, called PART, for the definition of features to be recognized. Conceptual graphs are used as an aid in the definition of features and for the representation of the features. The conceptual graphs are automatically transformed into feature recognition algorithms. Degrees of freedom (DOF) analysis is used for support during feature definition and for solving geometric constraints related to the feature to be defined.

A Graphical Symbol for Machining Process Information Description Using Model-Based Definition Technology

2014 ◽  
Vol 1061-1062 ◽  
pp. 681-686 ◽  
Author(s):  
Fu Jun Tian ◽  
Hong Qi Zhang ◽  
Xing Yu Chen ◽  
Hong Qiao Zhou ◽  
Di Jiang Chen
Keyword(s):  
Cutting Tools ◽  
Three Dimensional ◽  
Machining Process ◽  
Planning System ◽  
Symbolic Language ◽  
Process Information ◽  
Technical Parameters ◽  
Machining Process Planning ◽  
Graphical Symbol ◽  
Language Description

To realize the process information sharing and three-dimensional annotation, a standardization description model for machining process information was proposed, which including three layers, natural language description layer, object oriented language description layer and symbolic language description layer. By extension the graphical symbol of surface texture, integrated with machining allowance, surface lay and direction, surface roughness, machining method and technical parameters, equipment, fixture, cutting tools, test information, and sequence number, a graphical symbol for three-dimensional machining process information was proposed. Then formulated the annotation specification of the graphical symbol, including annotation plane, position and orientation, associativity, indication of two or more machining step, restricted area and color using. Finally, a three-dimensional machining process planning system was developed, and a part machining process annotation was taken to illustrate the validity of the graphical symbol.

Automatic feature recognition using artificial neural networks to integrate design and manufacturing: Review of automatic feature recognition systems

2010 ◽  
Vol 25 (3) ◽  
pp. 289-304 ◽  
Author(s):  
Bojan R. Babić ◽  
Nenad Nešić ◽  
Zoran Miljković
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Feature Recognition ◽  
System Development ◽  
Planning System ◽  
Computer Aided Process Planning ◽  
Design And Manufacturing ◽  
Automatic Feature Recognition ◽  
Feature Technology ◽  
Artificial Neural

AbstractFeature technology is considered an essential tool for integrating design and manufacturing. Automatic feature recognition (AFR) has provided the greatest contribution to fully automated computer-aided process planning system development. The objective of this paper is to review approaches based on application of artificial neural networks for solving major AFR problems. The analysis presented in this paper shows which approaches are suitable for different individual applications and how far away we are from the formation of a general AFR algorithm.

Machining Feature Modeling and Process Intermediate Model Generation in Process Planning

2013 ◽  
Author(s):  
Xu Zhang ◽  
Chao Liang ◽  
Tiedong Si ◽  
Ding Ding
Keyword(s):  
Process Planning ◽  
Feature Recognition ◽  
3D Models ◽  
Machining Process ◽  
Model Generation ◽  
Machining Features ◽  
Intermediate Model ◽  
Machining Feature ◽  
Feature Based ◽  
Solid Modeler

In process planning of machined part, machining feature recognition and representation, feature-based generative process planning, and the process intermediate model generation are the key issues. While many research results have been achieved in recent years, the complete modeling of machining features, process operations, and the 3D models in process planning are still need further research to make the techniques to be applied in practical CAPP systems. In this paper, a machining feature definition and classification method is proposed for the purpose of process planning based on 3D model. Machining features are defined as the surfaces formed by a serious of machining operation. The classification scheme of machining features is proposed for the purpose of feature recognition, feature-based machining operations reasoning, and knowledge representation. Recognized from B-Rep representation of design model, machining features are represented by adjacent graph and organized by feature relations. The machining process plan is modeled as operations and steps, which is the combination and sequencing of machining feature’s process steps. The process intermediate models (PIM) are important for process documentation, analysis and NC programming. An automatic PIM generation approach is proposed using local operations directly on B-Rep model. The proposed data structure and algorithm is adopted in the development of CAPP tool on solid modeler ACIS/HOOPS.

Feature Extraction and Operation Sequencing for Machining on Mill-Turns

1997 ◽  
Author(s):  
Debaslsh Dutta ◽  
Yong Se Kim ◽  
Youngjin Kim ◽  
Eric Wang ◽  
Derek Yip-Hoi
Keyword(s):  
Process Planning ◽  
Product Information ◽  
Integrated System ◽  
Machining Process ◽  
Planning System ◽  
Operation Sequencing ◽  
Computer Aided Process Planning ◽  
Convex Decomposition ◽  
Reasoning System ◽  
The University

Abstract An integrated system to support both product and manufacturing process design should be such that (1) the part design can be evaluated and redesigned based on manufacturability analysis and (2) the manufacturing processes can be selected efficiently and flexibly exploiting product information provided by part design representations. In this paper, we describe the collaborative research of the University of Illinois at Urbana-Champaign (UIUC) and the University of Michigan (UM) in computer-aided process planning for mill-turn machining. The UIUC geometric reasoning system based on convex decomposition identifies the machining features and maps the negative feature volumes to machining process methods, and generates geometry-based machining precedence relations. The UM process planning system based on genetic algorithm determines machining process sequences and assignment to multiple spindles and turrets.

Classification and Automatic Feature-Based Extraction Approach for Cylindrical and Milling Parts

2021 ◽  
Vol 11 (3) ◽  
pp. 55-73
Author(s):  
Sathish Kumar Adapa ◽  
Dowluru Sreeramulu ◽  
Jagadish
Keyword(s):  
Case Studies ◽  
Process Planning ◽  
Feature Recognition ◽  
Recognition Algorithm ◽  
Machining Process ◽  
Automatic Extraction ◽  
Java Program ◽  
Feature Based ◽  
Logical Rules ◽  
Conventional Machining

This paper reports classification and automatic extraction of various cylindrical and milling features in conventional machining process parts. In this work, various algorithms like hole recognition algorithm (HRA) and milling feature recognition algorithm (MFRA) have been used for identification of different cylindrical and milling features. A cylindrical feature is identified based on specific logical rules, and milling feature is identified based on the concept of concave decomposition of edges. In-house developed JAVA program is used to write algorithm, and then validation of the algorithm is done through two case studies. The HRA and MFRA algorithms extract the cylindrical features (through holes, blind holes, taper holes, and bosses) and milling features (slot, blind slot, step, blind step, pockets) precisely. The current work is well suitable to extract the features in conventional machining parts and thereby improve the downstream applications likes process planning, CAPP, CAM, etc.

Machining Process Evaluation Indices for Developing a Computer Aided Process Planning System

2017 ◽  
Vol 11 (2) ◽  
pp. 242-250 ◽  
Author(s):  
Kenta Koremura ◽  
◽  
Yuki Inoue ◽  
Keiichi Nakamoto
Keyword(s):  
Process Evaluation ◽  
Process Planning ◽  
Manufacturing Industry ◽  
High Efficiency ◽  
Machining Process ◽  
Planning System ◽  
Machining Features ◽  
Computer Aided Process Planning ◽  
Study Results ◽  
Computer Aided

In the manufacturing industry, there is an urgent need to shorten the manufacturing lead time of products. Therefore, optimizing process planning is essential to realize high efficiency machining. In this study, in order to develop a computer aided process planning (CAPP) system using previously proposed machining features, a prediction method for some process evaluation indices is proposed. Many candidates for the machining process exist, depending on the recognized machining features in a previous study. Therefore, by using these indices, operators can select a suitable process from among these candidates according to their ideas. Case studies of process planning are conducted to confirm that the operator’s strategy affects the selection of the machining process candidates. From the case study results, it is found that the proposed process evaluation indices have potential use in determining the machining process utilized, and are suitable for a flexible CAPP system of multi-tasking machine tools.

Review of Computer-Aided Process Planning Systems for Machining Operation – Future Development of a Computer-Aided Process Planning System –

2014 ◽  
Vol 8 (3) ◽  
pp. 317-332 ◽  
Author(s):  
Mohammad Mi’radj Isnaini ◽  
◽  
Keiichi Shirase
Keyword(s):  
Process Planning ◽  
Future Development ◽  
Metal Removal ◽  
Machining Process ◽  
Planning System ◽  
Computer Aided Process Planning ◽  
Removal Process ◽  
Manufacturing Information ◽  
Computer Aided ◽  
Six Elements

The need to integrate the design and machining stages has become an important issue since the introduction of the Computer-Integrated Manufacturing (CIM) concept. The development of the Computer-Aided Process Planning (CAPP) system has been recognized to have made a significant contribution toward fulfilling the requirement for an integrated planning system. This paper reviews the development of the CAPP system, particularly for the metal removal process. Previous reviews on CAPP are gathered and discussed to show the evolution stage of CAPP in general. Main research topics that contribute to the CAPP system development are shown. Six elements of the CAPP system are identified as the most important tasks in generating a process plan. These elements consist of: (1) model convention, (2) manufacturing operation selection, (3) manufacturing resource selection, (4) cutting condition selection, (5) tool path selection, and (6) setup selection. Six elements for the development of CAPP that contribute to process planning for metal removal process are discussed. The evolution stages of each element easily show the involvement of several tools in order to support the corresponding element. For further guidance, the methods of comprehending the involvement of manufacturing information in CAPP are discussed. Knowledge structuring and logic reasoning are the main organizational steps that can be used to describe the CAPP data architecture of manufacturing information. Further, the examples of full-scale CAPP in actualizing machining process planning are presented. Finally, key technologies for future development of CAPP are discussed.

Sign in / Sign up

Export Citation Format

Share Document