5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th–14th, 2014, IIT
Guwahati, Assam, India
AUTOMATIC FEATURE RECOGNITION OF CYLINDER AND KNUCKLE
THREAD FROM NEUTRAL FILES
M.M.M.Sarcar1, P.Madar Valli 2,V.Naga Malleswari3*
1
Department of Mechanical Engineering, GIET,Odisha- 765022,
India,[email protected]
2
Department of Industrial Engineering, GITAM University, Visakhapatnam-530045,
India,[email protected]
3*
Department of Industrial Engineering, GITAM University, Visakhapatnam-530045,
India, [email protected]
Abstract
The computerization of the design and manufacturing in the mechanical industry results in the Computer Aided
Design (CAD) and Computer Aided Manufacturing (CAM). One of the main integration efforts of the recent
computer integrated manufacturing (CIM) research has been the integration of CAD and CAM through computer
aided process planning (CAPP). Automatic feature recognition is the main input for CAPP. This paper presents
STEP AP203 based feature recognition methodology to identify the manufacturing features. Methodology utilizes
the neutral file which contains the information about the faces, edge curves, surfaces, edge loops, vertices,
coordinate points, location planes and location axes of the features. A rule based search is employed to recognize
manufacturing features and to interpret the characteristic attributes of dimension sets that denote length and radius
dimensions, type of feature (cylinder, thread) of the designed part is extracted. The proposed methodology is
developed for 3D rotational parts that are created by using solid modeling software, CATIA. A generalized Java
code has been written to extract the data from STEP file and to recognize the features. Theproposed software is
implemented and tested for many complex 3D models.
Keywords: STEP file; Feature recognition; Thread; Rotational parts
1 Introduction
The generative CAPP systems generate process
plans based on the feature concept and the expert
system technology generally. The features represent the
work pieces to be planned, and the expert system
includes the various process planning knowledge and
plans using the process planning rule bases. So, feature
recognition is an important aspect for CAPP.Analyzing
the solid model which is drawn by using CAD software
is a major task for feature recognition process. Features
can be divided as design features and manufacturing
features. Design features are specific geometric portions
that have certain functions from a usage viewpoint
whereas manufacturing features are the removal
volumes from the initial stock to generate the part
model.
There are two types of approaches to CAD feature
recognition: platform dependent and platform
independent. In the platform independent approach, the
part’s geometrical data are extracted from neutral files.
In contrast, the platform dependent approach extracts
the information of the design features directly from a
design by feature solid model through the object
oriented model of the part.There are different neutral
files like Data Exchange Format (DXF), Initial Graphic
Exchange specification (IGES), STandard for Exchange
of Product (STEP) etc. Different application protocols
(AP) are available in STEP like AP202,AP203, AP214,
AP224 etc. In which AP203 is Configuration controlled
3D designs of mechanical parts and assemblies. ISO10303-21 is the beginning keyword of STEP file and
END-ISO-10303-21 is the ending key word of the STEP
file. It is based on the B-Rep.
In this paper, STEP neutral file and AP 203 is
considered. In the proposed feature recognizer Figure 1,
the details of the part are extracted from STEP data
[AP203] neutral formats after modeling in the CATIA
software package. The part details from the STEP
AP203 formats extracted by the extractor are inputted to
the feature recognizer, which adopts the rule based
technique to recognize the features present in the part.
623-1
AUTOMATIC FEATURE RECOGNITION OF CYLINDER AND KNUCKLE THREAD FROM NEUTRAL FILES
Developed feature recognizer is capable of identifying
features like cylindrical, conical, spherical, toroidal,
CATIA solid
model
Process
planning Input
Convert into STEP File
Feature Recognizer
Feature
type,
dimensions
elliptical and knuckle thread. But, the present paper
presents cylinder and knuckle thread features.
Input to Feature
Recognition Program
Finding radii and
coordinates
No.of Cylindrical
Conical/Toroidal/Spheri
cal surfaces/Elliptical
Surfaces
EXTRACTOR
Figure 1 Different stages of feature recognition in the present methodology
2Methodology
Recognizing machining features from a CAD
model is the first and foremost task in a CAPP system to
plan further activities. This section presents the various
methodologies developed to identify manufacturing
features by using different feature recognition
approaches and neutral formats. Out of those most of
the techniques is used by authors are Heuristic based,
Syntactic pattern recognition, rule based, hint based,
combination of hint and rule based, graph based and
Neural Network.
It is observed that many of the authors concentrated
on recognizing features in prismatic parts. It is also
observed that features for rotational parts from STEP
format is given less attention. So, this paper has focused
on recognizing features for rotational parts from STEP
file. It is also observed that B-Spline curve features are
given less attention. So, in this work it is given
importance. The details of the data extraction from
STEP files and feature recognition methodology
developed are presented in further sections.
In this work, the STEP file is given as input for the
developed program. Output of the program is data
extraction from STEP file and various attributes of the
features. This paper mainly focused on feature
recognition of a cylinder and knuckle thread from STEP
file.
2.1 Extraction of data from STEP file
A STEP data file is a text file that contains
geometric data of a component including boundary
representation data such as shells, faces, vertices;
surface geometric data such as planes, cylinders, cones,
torus; curve geometric data such as lines, circles,
ellipses, b-spline curves. Searching STEP file starts with
a string CLOSED_SHELL and ends with the Cartesian
point which indicates coordinates of the geometry.
Extraction of various strings like closed_shell,
face_outer bound, face_bound etc. and entities (#
number) from STEP file is done according to the
hierarchy shown in Figure 2. Partial lines from STEP
file that is required to explain methodology to recognize
cylindrical feature is shown in Figure 3. From these
lines extraction of data for cylindrical feature according
to the hierarchy is shown in Figure 4. JAVA language is
used to search various strings and entities in the STEP
file.
After extracting geometric information from STEP
file, next step is feature recognition. The recognition of
a feature is based on certain rules. In this research, the
methodology of recognizing cylinder and knuckle
thread features is dealt.
623-2
5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th–14th, 2014, IIT
Guwahati, Assam, India
Figure 2 Hierarchy of geometrical strings
Line 571: #35=CLOSED_SHELL('Closed Shell',(#75,#92,#132,#149,#177,#217,#234,#274,………………..#586));
Line 596: #75=ADVANCED_FACE('PartBody',(#74),#40,.T.);
Line 6: #40=CYLINDRICAL_SURFACE('generated cylinder',#39,50.);
Line 775: #74=FACE_OUTER_BOUND('',#69,.T.) ;
Line 732: #69=EDGE_LOOP('',(#70,#71,#72,#73)) ;
Line 70: #70=ORIENTED_EDGE('',*,*,#49,.F.) ;
Line 71: #71=ORIENTED_EDGE('',*,*,#56,.T.) ;
Line 72: #72=ORIENTED_EDGE('',*,*,#63,.T.) ;
Line 73: #73=ORIENTED_EDGE('',*,*,#68,.F.) ;
Line 363: #49=EDGE_CURVE('',#46,#48,#44,.T.) ;
Line 364: #56=EDGE_CURVE('',#46,#55,#53,.F.) ;
Line 365: #63=EDGE_CURVE('',#55,#62,#60,.T.) ;
Line 366: #68=EDGE_CURVE('',#48,#62,#67,.F.) ;
Line 630: #44=CIRCLE('generated circle',#43,50.) ;
Line 53: #53=LINE('Line',#50,#52) ;
Line 631: #60=CIRCLE('generated circle',#59,50.) ;
Line 67: #67=LINE('Line',#64,#66) ;
Line 285: #43=AXIS2_PLACEMENT_3D('Circle Axis2P3D',#41,#42,$) ;
Line 286: #59=AXIS2_PLACEMENT_3D('Circle Axis2P3D',#57,#58,$) ;
Line 153: #41=CARTESIAN_POINT('Axis2P3D Location',(0.,0.,0.)) ;
Line 155: #57=CARTESIAN_POINT('Axis2P3D Location',(0.,20.,0.)) ;
Line 284: #39=AXIS2_PLACEMENT_3D('Cylinder Axis2P3D',#93,#94,#95) ;
Line 156: #93=CARTESIAN_POINT('Axis2P3D Location',(0.,30.,0.)) ;
Figure 3 Partial lines from STEP file for cylindrical feature recognition
623-3
AUTOMATIC FEATURE RECOGNITION OF CYLINDER AND KNUCKLE THREAD FROM NEUTRAL FILES
Figure 4 Data extraction hierarchy from STEP file for cylindrical feature
2.2 Recognition of a cylinder
2.3 Recognition of a knuckle thread
After extracting data from STEP file features are
recognized. Geometry for a cylinder is shown in
Figure 5.
The recognition of a cylindrical feature is based on
four rules.
Rule 1: EDGE_CURVE construction must be circle,
line, circle, line
Rule 2: Radius of circles in EDGE_CURVE is equal
to cylinder radius.
Rule 3: X and Z coordinates of circle centers are
same and Y coordinate is different.
Rule4:Surface must be CYLINDRICAL_SURFACE.
The knuckle thread is drawn in CATIA by using
helix command. Pitch of a knuckle thread is
calculated by using formula 1. Geometry of knuckle
thread is shown in Figure 6. Starting and ending of a
thread are planes. When a thread is created on a
cylinder then, it is bounded by number of bounded
surfaces. From this information pitch of the thread
and radius of thread is calculated. By knowing the y
coordinates on plane 1 and on plane 2 length of the
thread can be calculated in formula 2. Plane 1 edge
curve construction is bspline, circle, circle and plane
2 edge curve construction is bcurve, line.
pitch
=
length/(number
of
bounded
surfaces/4)……………( 1 )
Length= Y co-ordiante of bspline in plane2 – y coordinate of bspline or bounded curve in
plane1……… ……(2)
Figure 5 Cylinder geometry
623-4
5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th–14th, 2014, IIT
Guwahati, Assam, India
based on the proposed methodology for
demonstration purposes. This case study is shown in
Figure7. It consists of two features one is cylinder
and another is knuckle thread on a cylinder. In
feature extractor extracted data is shown in MAIN
table and recognized features are shown in
FEATURE table.Results for case study that is MAIN
table and FEATURE table are shown in Figure8.
Figure 6 Geometry of knuckle thread
2.4 Case study
To illustrate the methodology described in the
previous sections of this paper, case study is analyzed
Figure 7 Case study
Figure 8 MAIN table and FEATURE table for case study
3Conclusions
In the present work, a feature recognizer was
developed to recognize features like cylinder and
knuckle thread. The proposed methodology operates
in 3D solid modeling environment which gives it a
powerful ability to be used by the current
manufacturing
technology.
The
developed
methodology is coded using the JAVA language.
These features were tested on an Intel Core duo
1.66 GHz PC for its capability of handling
combinations of more than one feature. The feature
recognizer took a minimum amount of time to
recognize the features and to generate the output. The
output contains extracted data from STEP file and
attribute of features(cylinder- length and radius ;
knuckle thread- pitch and length). From STEP file
623-5
AUTOMATIC FEATURE RECOGNITION OF CYLINDER AND KNUCKLE THREAD FROM NEUTRAL FILES
different surfaces like cylinder, cone, torus and
sphere with their radius can be recognized from the
developed Feature Extractor program. By developing
rules features like conical/spherical/toroidal can be
recognized. Further, the complex features like radial
holes, gears, keyways etc. can also be recognized.
References
AbouelNasr, E.S and Kamrani, A.K. (2006), A new
methodology
for
extractingmanufacturingfeaturesfrom CAD system.
Computers &Industrial Engineering, vol. 51, pp.389415.
Arivazhagan, A., Mehta, N. K. and Jain, P.K.
(2008), A STEP AP 203–214-based machinable
volume identifier for identifying the finishcutmachinable volumes from rough-machined parts,
International
Journal
of
Advanced
ManufacturingTechnology, vol. 42, pp.850-872 .
Bhandarkar, M.P. et.al. (2000) Migratingfrom IGES
to STEP: one to one translation of IGES drawing to
STEP drafting data,Computers in Industry, pp. 261277.
Dimov, S.S., Brousseau, E.B. and Setchi, R. (2007),
A hybridmethod for feature recognition in computeraided design models. Proceedings of the Institution of
MechanicalEngineers
Part B: Journal of
Engineering Manufacture, vol. 221, pp.79-96.
Hayasi, M.T and Asiabanpour, B (2009), Extraction
of manufacturing information from design-byfeaturesolid model throughfeature recognition,
International
Journal
of
Advanced
ManufacturingTechnology, Vol. 44, pp.1191-1203.
Joshi, S. and Chang, T.C. (1988), Graph based
heuristics for recognition of machined features from a
3D solid model, Computer Aided Design, vol. 20,
pp.58-66.
Kang, M., Han, J. and Moon, J.G. (2003), An
approach for interlinking design and process
planning,
Journal
of
MaterialsProcessingTechnology, vol.139, pp.589595.
Kannan TR and Shunmugam MS (2009) Processing
of 3D sheetmetal components in STEP AP-203
format
Part I: feature recognition system.
International Journal of Production Research, vol.
47, pp. 941-964.
Lau, H.C.W. et. al. (2005), Development of a
computer integrated system to support CAD to
CAPP. International Journal of Advanced
ManufacturingTechnology, vol. 26, pp.1032-1042.
Nagarajan, S and Reddy, N.V. (2010), STEPbasedautomatic system for recognising design and
manufacturingfeatures,International
Journal
of
Production Research, Vol. 48, pp.117-144.
Prabhu, B.S., Biswas, S. and Pande, S.S. (2001),
Intelligent system for extraction of product data from
CADD models. Computers in Industry,vol. 44, pp.
79-95.
Prabhu, B.S. and Pande, S.S. (1999),Automatic
extraction of manufacturable featuresfrom CADD
modelsusingsyntactic
pattern
recognition
technique,International Journal of Production
Research, vol. 37, pp. 1259-1281.
Verma, A.K. and Rajotia, S. (2008), A hintbasedmachiningfeature recognition system for 2.5D
parts. International journal of production research,
vol. 46, pp.1515-1537.
Yifei, T. et. al. (2007),A feature-extraction-based
process-planning system. International Journal of
Advanced Manufacturing Technology,vol. 38,
pp.1192-1200.
623-6