Int. J. Rapid Manufacturing, Vol. 5, No. 2, 2015
An independent CAPP system for prismatic parts
Awais Ahmad Khan*
Industrial Engineering Department,
College of Engineering,
King Saud University,
Riyadh 12372, Saudi Arabia
and
Advance Manufacturing Institute,
College of Engineering,
King Saud University,
Riyadh 12372, Saudi Arabia
Email: awais78@gmail.com
*Corresponding author
Emad Abouel Nasr
Industrial Engineering Department,
College of Engineering,
King Saud University,
Riyadh 12372, Saudi Arabia
and
Mechanical Engineering Department,
Faculty of Engineering,
Helwan University,
Cairo, Egypt
Email: eabdelghany@ksu.edu.sa
Abdulrahman Al-Ahmari
Industrial Engineering Department,
College of Engineering,
King Saud University,
Riyadh 12372, Saudi Arabia
and
Advance Manufacturing Institute,
College of Engineering,
King Saud University,
Riyadh 12372, Saudi Arabia
Email: alahmari@ksu.edu.sa
Abstract: Computer Aided Process Planning (CAPP) provides a link between
design and manufacturing in a Computer-Integrated Manufacturing (CIM)
environment. The Automatic Feature Recognition (AFR) plays a significant
role in the contribution of Computer Aided Design and Computer Aided
Manufacturing (CAD/CAM) integration. In this paper, an object oriented
Copyright © 2015 Inderscience Enterprises Ltd.
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A.A. Khan, E. Abouel Nasr and A. Al-Ahmari
approach is applied to prepare the part geometric database from a neutral file
(STEP AP 203) and translates this information to manufacturing knowledge.
The algorithms and rules are then formulated to extract, group and recognise
the form feature and their dimensions. The feature based CAPP system is then
produced along with the setup plan using machining database and an algorithm
based on feature location. The proposed methodology is tested by using a case
study.
Keywords: feature recognition; CAPP; CAD/CAM; STEP AP 203.
Reference to this paper should be made as follows: Khan, A.A., Abouel Nasr,
E. and Al-Ahmari, A. (2015) ‘An independent CAPP system for prismatic
parts’, Int. J. Rapid Manufacturing, Vol. 5, No. 2, pp.129–144.
Biographical notes: Awais Ahmad Khan is a Researcher in Advance
Manufacturing Institute, College of Engineering, King Saud University, Saudi
Arabia, and Assistant Professor in Mechanical Engineering Department,
University of Engineering & Technology, Lahore, Pakistan. He received his
PhD in Industrial Engineering from King Saud University in February 2015.
His current research focuses on feature recognition, process planning, fixture
design and analysis, die design, flexible manufacturing systems.
Emad Abouel Nasr is an Associate Professor in Industrial Engineering
Department, College of Engineering, King Saud University, Saudi Arabia, and
Mechanical Engineering Department, Faculty of Engineering, Helwan
University, Egypt. He received his PhD in Industrial Engineering from
University of Houston, TX, USA, in 2005. His current research focuses on
CAD, CAM, rapid prototyping, advanced manufacturing systems, supply chain
management, and collaborative engineering.
Abdulrahman Al-Ahmari is the Dean of Advanced Manufacturing Institute,
Executive director of CEREM (Center of Excellence for Research in
Engineering Materials), Supervisor of Princess Fatimah Alnijris’s Research
Chair for Advanced Manufacturing Technology, and Supervisor of CMTT
(Center of Manufacturing Technology Transfer). He received his PhD
(Manufacturing Systems Engineering) in 1998 from University of Sheffield,
UK. His research interests are in analysis and design of manufacturing systems,
Computer Integrated Manufacturing (CIM), optimisation of manufacturing
operations, applications of simulation optimisation, FMS and cellular
manufacturing systems.
1
Introduction
The essential factor for the modern manufacturing companies is to develop the
diversified products in short calendars. Consequently, the flexible manufacturing
techniques are growing quickly in order to compete the markets globally. The systems of
Computer Aided Design and Computer Aided Manufacturing (CAD/CAM) facilitated the
development of much higher levels of automation in manufacturing processes that was
not previously possible. CAD/CAM technologies are designed to integrate CAD,
Computer Aided Process Planning (CAPP) and CAM in a hardware configuration which
An independent CAPP system for prismatic parts
131
makes it possible to the user to conceive, design, envisage and control the manufacturing
of the products while automating as many activities as possible (Javorick et al., 1990;
Thomas and Fischer, 1996).
In general, there are two approaches in CAPP, variant and generative. Variant
approach requires an operator to classify the information part by part, retrieve a similar
process plan from a database and make the necessary adjustments. This method is suited
for companies that involve stable manufacturing processes and manufactured products,
which vary slightly. The advantage of this approach is the ease of maintenance, but the
shortcoming is the lack of an on-time calculation of manufacturing process and quality of
the process plan still depends on the knowledge of a process planner. Manual input is still
required to establish the mass data of manufacturing processes. In a generative approach,
process plans are generated automatically through decision logic and process knowledge
(Xu et al., 2011).
A CAPP system, depending on the level of complexity, may involve automating the
interface between design and process planning as well as various process planning tasks
such as process selection, machining volume, machine tool, cutting tool, set-up planning
and so on. In the research work presented in this paper, the authors have developed a
feature based generative CAPP system for machined prismatic parts (Jaider et al., 2014).
The paper is organised as follows: Section 2 reviews the literature of process
planning. The proposed methodology is then presented in Section 3. Section 4
demonstrates the implementation steps of the developed methodology using a case study.
Finally, conclusion and future work is presented in Section 5.
2
Literature review
CAPP software tools are useful for reducing demand on skilled human experts and for
ensuring the production of consistent process plans by eliminating redundancies and
conflicts that arise in complex designs (Nee et al., 2004). Supporting the design engineer
at the conceptual phase requires an efficient feature recognition methodology operating
in a period of minutes and able to handle the users CAD format. Various feature
recognition techniques like Joshi and Chang (1988) developed a graph named the
Attribute Adjacency Graph (AAG) to represent the features of a part. The node represents
the part face and the arc represents edges in B-rep. Lockett and Guenoy (2005) propose a
mid-surface-based feature recognition approach for moulded parts. Nasr and Kamrani
(2006) proposed a methodology for extracting manufacturing features from CAD system
using Initial Graphics Exchange Specification (IGES) format as input and translates the
information in the file to manufacturing information. Zhou (1996) used an objectoriented approach to provide an interface with CAD models. In this interface, the part
data file is extracted automatically in the form of neutral file since standard or
nonstandard file formats were used in different applications. Venkataraman (2001)
presented a graph based frame work for feature recognition. The feature recognition step
involved finding similar sub graphs in the part graph. The novelty of this framework laid
in the usage of a rich set of attributes to recognise a wide range of features efficiently.
Han et al. (2001) presented integrating feature recognition and process planning in the
machining domain to achieve the goal of CAD/CAM integration. Ismail et al. (2004)
proposed a rule based approach for the recognition of hole from STEP file by using
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A.A. Khan, E. Abouel Nasr and A. Al-Ahmari
geometry and topology formation from B-rep model. Holland et al. (2002) proposed a
process orientated feature recognition system, in which the pattern recognition is used to
transform the surface boundary model of a component into an Attributed Adjacency
Graph (AAG). Fu et al. (2003) proposed an algorithm for the identification of design and
machining features from a data exchanged part model. Haque (2001) presented a
methodology in which the geometric information of a rotational part is translated into
manufacturing information through a Data Interchange Format (DXF).
In this paper, the part design was introduced and represented via CAD software and
solid model designed by the Constructive Solid Geometry (CSG) technique, respectively.
The solid model of the part design consists of small and different solid primitives
combined to form the required part design. The CAD software generates and provides the
geometrical information of the part design in the form of a STEP file (the standard
format). This provides ability for the proposed methodology to communicate with the
various CAD/CAM systems. The object oriented approach is implemented using Visual
C++ provides an efficient and automatic link between the geometric data, the generated
process and the setup plan.
3
Proposed methodology
Generative CAPP approach is used in the developed methodology due to its capability of
providing detail information in the obtained process plans for the target manufacturing
components. The STEP AP-203 file is used as an input to the system. The significance
of using STEP AP 203 file is its compatibility with several known CAD systems.
The CAPP system uses the 3-D solid model created in CATIA V5. The geometric
information file generated by extracting the relevant data from STEP AP203 file using
object oriented approach. The developed algorithms (coded using C++) used to recognise
and group feature faces and find out their geometric properties. The technological
features contained in the part recognised by establishing the rules based on geometric
reasoning. The process parameters such as machining operation, cutting tool, machine
tool, machining parameters and tool access direction defined based on the feature data
obtained using feature recognition procedures. The feature location methodology is also
developed using TAD data so that a definite setup can be adapted for the feature. The
setup plan algorithm assigns all recognised features to a specific setup for CAM
applications. The methodology is presented in the form of flow chart in Figure 1.
3.1 Geometric data extraction from STEP AP-203
Initially, a 3-D Solid model is developed to represent part design. The solid model
consists of different solid primitives combined together to form the required part
geometry. The geometrical information of solid model is stored in STEP AP203 file. As
mentioned earlier, STEP AP203 is a standard CAD format used to store the geometrical
information in a neutral file format that is independent of and platform and can
communicate between different CAD systems such as CATIA, Unigraphics (UG), PROE and Solid Works (Figure 2). Geometrical and topological information in STEP format
can be represented in the form of entities. Brief descriptions of some STEP elements are
listed in Table 1.
An independent CAPP system for prismatic parts
Proposed methodology
CAD Database
Generation of STEP File
Generation of faces, loops, edges,
vertices ids and face direction
Selection of Machining Operation
Creation of Part Geometric
Database
Selection of Cutting Tool
Extraction feature faces, loops,
edges and vertices
Selection of Machine Tool
Object‐
Oriented
Technique
Extraction &
Dimensional
Algorithm
Extraction of dimensional
information like length, width,
height, radius etc
Setup Plan Generation by
applying Feature Location
Algorithm
Generation of CAPP Data
Rule Based
Generation of Feature
Recognition File
Machining
Database
Figure 1
133
Figure 2
STEP data format for manufacturing
Table 1
Description of STEP entities
STEP entity
Closed shell
Advance face
Face surface
Description
A collection of one or more faces which bounds a region in three
dimensional space
The face that associated with a type of surface
A type of face in which the geometry is defined by the associated
surface, boundary and vertices.
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Table 1
A.A. Khan, E. Abouel Nasr and A. Al-Ahmari
Description of STEP entities (continued)
STEP entity
Face outer bound and face
bound
Edge loop
Edge curve
Vertex point
Cartesian point
Description
A loop used for bounding a face. The face outer bound represents
the external loop whereas face bound represents the internal loop
The closed path formed by the oriented edges
It contains the magnitude and direction information of an edge
A point defining the geometry of a vertex
Address of a point in Cartesian space
Among different geometric representation techniques, B-rep is taken because most
mechanical parts can be modelled based on B-rep model. The data extraction process
starts with the extraction of geometric and topological information from STEP AP 203
and redefining it as a new object-oriented data structure. The hierarchy structure of object
oriented technique presented in Figure 3. In this hierarchy, the highest level is the
designed object, known as called shell. The shell consists of faces that are further
classified as plane, cylindrical and conical faces (Figure 4). The plane faces are further
categorised as straight and inclined faces (Figure 4). The determination of straight or
inclined surface is through the face vector direction. For straight face, the vector direction
is in 0 or 1 otherwise it is between 0 and 1. The next level in the hierarchy is the edge
loop. The edge loop contains edge curve and vertices. The edge loop is further classified
as external and internal loop. The face outer bound represents the external loop and face
bound represents the internal loop. If a feature exists within face boundary such as hole
or pocket feature, it will be a face bound (internal loop) inside this face as shown in
Figure 4.The next level in the hierarchy is edge curve that consist of line or circle edges.
The line edge can be represented as plane line edge and tangent line edge. The plane line
edge is the common line edge between two plane faces and tangent line edge is the
common line edge between plane and cylindrical face or between two cylindrical faces as
presented in Figure 4.
3.1.1 Geometric information file
To translate the STEP files, the EXPRESS information model for STEP AP203 is
compiled to produce C++ classes using Qt library. The modular Qt library provides a rich
set of application building blocks, delivering all of the functionality needed to build
advanced, cross-platform applications. An EXPRESS schema contains a data model
made up of classes that are themselves made up of attributes, references, aggregates and
rules. These classes are used to describe entities in STEP AP203 and map them into C++
class’s information memory model. The output file is generated through the analysis of
the geometric information available in the STEP AP 203 File. This information identifies
all face in B-rep format using faces, loops, edges and vertices along with the surface type
and the normal vector direction. The faces, edges and vertices are given a unique id
number. Information regarding the face conditions (plane, cylindrical, conical), edge
conditions (plane line, tangent line and circle edge), face and edge directions are
collected. Moreover, the orientation, direction of a face vector and external and internal
loops are also established.
An independent CAPP system for prismatic parts
Figure 3
Hierarchy structure of object oriented technique
Figure 4
Classification of faces, loops and edges (see online version for colours)
135
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A.A. Khan, E. Abouel Nasr and A. Al-Ahmari
3.2 Feature recognition
Feature recognition involves the identification and grouping of feature entities from a
geometric model. Such ‘post definition’ of features can be done interactively or
automatically. Usually, identified entities (i.e. the recognised features) are extracted
from the model and additional engineering information such as tolerances and nongeometric attributes are then associated with the feature entities (Sreevalsan and Shah,
1992). The feature recognition is based on geometric properties and object oriented
approach for the recognition of form features. The geometric properties like parallelism,
perpendicularity, edge types, surface types etc are established from geometrical
information file. The main objective is to recognise the technological features within
solid model.
3.2.1 Extraction and dimensional algorithms
The extraction algorithms are designed to identify and extract feature faces and establish
their geometric properties. The faces are grouped by common edges (line and circular).
The dimensions of these features calculated from the edges of extracted faces by simple
algorithms. The algorithm is described in the following steps for Step Blind Round
Corner feature in Figure 5:
Step 1: Calculate the min and max x, y and z value of the part by reading the edge loops
of the geometric information file for the selected part.
Step 2: Extract the Faces that have constant coordinate value between min and max
(value > min and < max) x, y or z throughout the edge loop (plane face).
Step 3: Extract the faces that has no constant coordinate value throughout the edge loop
and 1(inclined face) or 2 (conical and quarter-cylindrical face) coordinates are changing
(throughout the edge loop) between min and max x, y, z value (value > min and < max)
of the part.
Step 4: Extract and group the feature faces with respect to the common edge such that if
Face 1 has common edge with Face 2 and Face 2 has common edge with Face 3, then
Faces 1,2 and 3 should be grouped.
Step 5: The feature dimensions are calculated from all grouped feature faces such that:
Step 5.1: Height is the difference of constant coordinate value (between the two vertices)
of two circle edge curves.
Step 5.2: Radius is extracted directly from circle edge curve ‘Value’.
Step 5.3: Length and Width are calculated by extracting changing coordinates value
(between the two vertices) of non-common edges of face that contains both line and
circular edges and find their differences to calculate length and width of feature such that
the bigger value will become length and smaller will become width.
An independent CAPP system for prismatic parts
Figure 5
137
Step blind RC feature (see online version for colours)
3.2.2 Parallelism and perpendicularity algorithm
The parallelism and perpendicularity property between the two faces as illustrated in
Figure 6 is described in the following steps:
Step 1: Extract the normal vectors of two faces.
Step 2: Compare the extracted vector (x, y, z) values.
Step 3: If the normal vector of Face 1 = Face 2, the faces are parallel otherwise
perpendicular.
Figure 6
Face normal vector (see online version for colours)
Table 2 displays the data attributes required for each class in the object oriented data
structure that is defined before.
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Table 2
Definition of classes and attributes
Class name
Cartesian_Point
Vertex_Point
Edge_Curve
Attribute
Type
X_Coordinates
(Real)
Y_Coordinates
(Real)
Z_Coordinates
(Real)
Vertex_ID
(Integer)
Vertex_Count
(Integer)
Cartesian_Point
(Pointer to Cartesian Point)
Edge_ID Edge_Type
(Integer)
Start_Vertex
(Enumerated constants)
(Vertex pointer)
Terminate_Vertex
(Vertex pointer)
Dimension
(Real)
Oriented _Edge
Edge_Curve
(Pointer to Vertex Point)
Edge_Loop
Edge_List
(A list of edges)
Axis2Placement_3D
Face_Direction
(Pointer to the point)
Surface
Advance_Face
Closed_Shell
Feature
Surface_Type
(Enumerated constants)
Face_Direction
(Pointer to the
AXIS2PLACEMENT3D)
Face_ID Surface_Pointer
Number
External_Loop
(Pointer to the surface)
(Loop pointer)
Internal_Loop_Count
Number
Internal_Loop_List
(Vector of loop pointers)
Face_List Part Min and
Max Value
(Vector of face pointers)
(String)
Feature_ID
(Number)
Feature_Name
(String)
Length
(Real)
Width
(Real)
Height
(Real)
Radius
(Real)
Face_List
(Vector of face pointers)
The created feature library contains both flat and cylindrical features. The flat features
contains through, blind and round corners. The feature library contains ten machining
features as shown in Figure 7.
The feature faces are extracted and grouped by applying the above algorithms along
with their parallelism and perpendicularity properties. Dimensions are calculated from
the edges of the selected faces. The extraction procedure for some features from feature
library is listed in Table 3. Rules are then formulated based on geometric reasoning to
recognise the technological features. Every feature has been given a unique feature (id) as
shown in Table 4.
An independent CAPP system for prismatic parts
Figure 7
The feature library (see online version for colours)
Table 3
Feature faces extraction
• Plane Faces 1 and 2 •
are extracted and
grouped by one
common plane
edge.
• Face 1 is
perpendicular to
Face 2.
•
• Length and width is •
calculated from
Face 1 edges and
•
height from Face 2
edge.
•
Cylindrical Faces 1 •
and 2 are extracted
and grouped by
two common
tangent edges.
•
• Plane Face 3 is
Face 1 is
extracted and is
perpendicular to
•
made by circular
Faces 2–4.
edges of
Face 3 is parallel to
cylindrical Faces 1 •
Face 4.
and 2
Face 2 is
• Radius is
perpendicular to
determined from
Faces 1, 3 and 4.
the circular edge •
of Face 1 or
Length and width is
calculated from
Face 2
Face 2 edges and
• Height is
height from Face
calculated from
1edge.
line edge of Face
1 or Face 2
Plane Faces 1–4 are •
extracted and
grouped by four
common plane
edges.
139
Plane Faces 1, 2, 4 and
cylindrical Face 3 are
extracted and grouped
by five common edges.
Face1 is perpendicular
to Faces 2, 3 and 4.
Face2 is perpendicular
to Face 4.
Height and radius is
calculated from the
tangent and circular
edges of Face 3.
Length and width is
calculated from Face 1
edges.
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A.A. Khan, E. Abouel Nasr and A. Al-Ahmari
Table 4
Feature recognition
Feature rule
•
For the two extracted faces.
•
If the two faces (Face 1 and Face 2)
are plane and perpendicular to each
other.
•
If Face 1 and Face 2 are connected
with each other by a plane common
edge.
•
Then the feature is step through.
•
For the four extracted faces.
•
If the four faces are connected such
that Face 1, Face 2 have three
common plane edges and Face 3,
Face 4 have two common plane
edges in their edge loops.
•
If Face 1 perpendicular to Face 2,
Face 3 and Face 4 and Face 3 and
face4 are parallel to each other.
•
If Face 2 is perpendicular to Face 3
and Face 4.
•
Then the Feature is Slot Blind.
•
For the three faces.
•
If the Faces 1 and 2 generate
cylinder.
•
If Face3 is plane and it is formed by
two common circular edges of Face 1
and Face 2.
•
If the one loop formed by the circular
edges of the Face1 and 2 is an
internal loop.
•
Then the Feature is Hole Blind.
•
For the four extracted faces
•
If Face 1, Face 2 and Face 4 are plane
and Face 3 is cylindrical.
•
If all the faces are connected such
that Face 1 has two common plane
edges with Face 2and Face 4, and one
common circular edge with Face 3.
•
If Face 2, Face 3 and Face 4 are
connected by tangent edges.
•
If all the plane faces are
perpendicular to each other.
•
Then the Feature is Step Blind Round
Corner.
Feature illustration
Recognition output
An independent CAPP system for prismatic parts
141
3.3 Process and setup plan generation
A database is created for the selection of suitable machining operation, cutting tool,
machine tool and machining parameters for each feature. The algorithm for determining
the manufacturing setup plan is illustrated in the following steps:
1
Define the part coordinate system and assign Tool Access Direction (TAD) for a
block shaped part machined on 3-axis milling centre (Figure 8).
2
Define six setup plans corresponding to each TAD.
3
Assign a definite TAD to every feature so that it can be assigned to a definite setup.
Figure 8
Tool access direction (TAD) (see online version for colours)
Notes
TAD1 defined by (1, 0, 0); +X direction.
TAD2 defined by (–1, 0, 0); –X direction.
TAD3 defined by (0, 1, 0), +Y direction.
TAD4 defined by (0, –1, 0); –Y direction.
TAD5 defined by (0, 0, 1); +Z direction.
TAD6 defined by (0, 0, –1); –Z direction.
3.3.1 Sequence of machining operation in each setup
Every setup plan (S + x, S – x, S + y, S – y, S + z, S – z) contains the following features:
1
Sequence the operation to minimise the tool change in a setup.
4
Case study
The proposed methodology is tested and validated using a case study. The 3-D solid
model is created in CATIA V5 as shown in Figure 9. The geometric information is
extracted from STEP AP 203 file using object-oriented technique. 44 faces are extracted
in geometric information file along with their loops. Edges, vertices and face directions.
Fourteen feature faces are extracted and grouped along with their dimensions using
extraction and dimensional algorithms. The formulated rules are then applied on the
extracted data and eight manufacturing features are successfully recognised along with
their dimensions as listed in Table 5. The process parameters like machining operation,
cutting tool, machine tool are then defined each feature using machining database. An
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algorithm is then developed based on feature location to generate the setup plan for each
feature. The CAPP output is generated automatically as presented in Table 6 for the
sample case study.
Figure 9
Case study (see online version for colours)
Table 5
Feature data
Feature ID Feature name
Face Ids
Feature dimensions
Pocket through
(5, 2, 1, 40)
Length: 20 Width: 10 Height: 47
2
Slot through
(34, 9, 39)
Length: 100 Width: 10 Height: 15
3
Slot blind round
corner
(10, 33, 12, 13, 12, 11)
Length: 30 Width: 20 Height: 12
Radius: 6
4
Slot blind
(17, 16, 15, 32)
Length: 20 Width: 20 Height: 6
(22, 31, 30, 29, 28)
Length: 30 Width: 10 Height: 8
1
5
Pocket blind
6
Pocket blind round
corner
7
Step blind
(35, 37, 38)
Length: 20 Width: 20 Height: 10
8
Hole blind
(43, 42, 44)
Radius: 10 Height: 20
Table 6
CAPP data
(27, 21, 26, 20, 25, 19, 24, Length: 60 Width: 20 Height: 7
18, 23)
Radius: 7
Feature Machining Machining
Cutting tool
Id
volume operation
Machine
tool
feature location
Setup plan
8326
Pocket
milling
Corner
rounding
milling
cutter
Milling
machine
TAD (0, 0, –1)
Location XY_TOP
1 (XY_TOP)
3
7153
Slot
milling
Corner
rounding
milling
cutter
Milling
machine
TAD (0, –1, 0)
Location ZX_BACK
TAD (0, 0, –1)
Location XY_TOP
1 (XY_TOP)
2
15000
Slot
milling
End mill
cutter
Milling
machine
TAD (0, 0, –1)
Location XY_TOP
1 (XY_TOP)
6
An independent CAPP system for prismatic parts
Table 6
CAPP data (continued)
Feature Machining Machining
Cutting tool
Id
volume operation
Machine
tool
feature location
Setup plan
1 (XY_TOP)
9400
Pocket
milling
End mill
cutter
Milling
machine
TAD (0, 0, 1)
Location
XY_BOTTOM
TAD (0, 0, –1)
Location XY_TOP
4
2400
Slot
milling
End mill
cutter
Milling
machine
TAD (–1, 0, 0)
Location YZ_RIGHT
TAD (0, 0, –1)
Location XY_TOP
1 (XY_TOP)
5
2400
Pocket
milling
End mill
cutter
Milling
machine
TAD (0, 0, –1)
Location XY_TOP
1 (XY_TOP)
1 (XY_TOP)
1 (XY_TOP)
1
5
143
7
4000
Shoulder
milling
Side mill
cutter
Milling
machine
TAD (1, 0, 0)
Location YZ_LEFT
TAD (0, –1, 0)
Location ZX_BACK
TAD (0, 0, –1)
Location XY_TOP
8
6280
Drilling
Twist drill
Milling
machine
TAD (0, 0, –1)
Location XY_TOP
Conclusion
The methodology presented in the paper is successfully tested with a sample case study.
The proposed methodology is implemented using Visual C++ that interacts with existing
CAD packages. The significance of using C++ is to create a standalone system for
CAPP. All the relevant geometrical data is extracted from STEP AP 203 file in the form
of faces, loops, edges and vertices along with their IDs. The part geometric database is
created using an object oriented technique. The object oriented technique found very
useful in defining STEP entities and map them to C++ class’s information memory
model. The output file is generated through the analysis of the geometric information
available in the STEP AP 203 File. In the next step, the designed algorithms are applied
to automatically extracted the feature faces, establish their geometric properties and
dimensions. The logical rules then successfully recognise the technological features in
the sample case study based on geometric reasoning approach. Each feature has been
given a unique feature id. Machining database is created to define machining parameters
for each feature. The setup plan algorithm is applied to place each feature in a definite
setup. In the future, the standalone system can be used to develop a fixture design module
for manufacturing and inspection planning. Moreover, the scope can be extended by
adding cylindrical parts.
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A.A. Khan, E. Abouel Nasr and A. Al-Ahmari
Acknowledgements
This work was supported by NSTIP strategic technologies program number (10-INF
1280-02) in the kingdom of Saudi Arabia. Moreover, the authors would like to thank the
Advance Manufacturing Institute (AMI) at King Saud University for their support
throughout the research work.
References
Fu, M.W., Ong, S-K., Lu, W.F., Lu, W.F., Lee, I.B.H. and Nee, A.Y.C. (2003) ‘An approach to
identify design and manufacturing features from data exchanged part model’, Computer-Aided
Design, Vol. 35, No. 11, pp.979–993.
Han, J., Kang, M. and Choi, H. (2001) ‘STEP-based feature recognition for manufacturing cost
optimization’, Journal of Computer-Aided Design, Vol. 33, No. 9, pp.671–686.
Haque, A. (2001) ‘Manufacturing feature recognition of parts using DXF files’, 4th International
Conference on Mechanical Engineering, 26–28 December, Dhaka, Bangladesh, Vol. 4,
pp.111–115.
Holland, P., Standring, H.L. and Mynors, D. (2002) ‘Feature extraction from STEP (ISO 10303)
CAD drawing files for metal forming process selection in an integrated design system’,
Journal of Material Process Technology, Vol. 125, pp.446–455.
Ismail, N., Osman, M.R., Tan, C.F., Wong, S.V. and Sulaiman, S. (2004) ‘Extraction of cylindrical
features from neutral data format for CAD/CAM integration’, International Journal of
Engineering and Technology, Vol. 1, No. 2, pp.206–212.
Jaider, O., Elmesbahi, A. and Rechia, A. (2014) ‘Manufacturing computer aided process planning
for rotational parts. Part 1: automatic feature recognition from STEP AP203 Ed2’, Journal of
Engineering Research and Applications, Vol. 4, No. 5, pp.14–25.
Javorick, L., Cabadaj, J. and Chvojka D. (1990) ‘Aspects of computer-aided fixture design’, CIMS,
Vol. 3, No. 2, pp.111–114.
Joshi, S. and Chang, T.C. (1988) ‘Graph based heuristics for recognition of machined features from
3D solid model’, Computer-Aided Design, Vol. 20, No. 2, pp.58–66.
Lockett, H.L. and Guenov M.D. (2005) ‘Graph-based feature recognition for injection moulding
based on a mid-surface approach’, Journal of Computer-Aided Design, Vol. 37, No. 2,
pp.251–262.
Nasr, E.S.A. and Kamrani, A.K. (2006) ‘A new methodology for extracting manufacturing features
from CAD system’, Computers & Industrial Engineering, Vol. 51, No. 3, pp.389–415.
Nee, A.Y.C., Kumar, A.S. and Tao, Z.J. (2004) An Advanced Treatise on Fixture Design and
Planning, World Scientific Publishing Co. Pte. Ltd.
Sreevalsan, P.C. and Shah, J.J. (1992) ‘Unification of form feature definition methods’, IFIP
Transactions B-Applications in Technology, Vol. 4, pp.83–99.
Thomas, K.K. and Fischer, G.W. (1996) ‘Integrating CAD/CAM software for process planning
applications’, Journal of Materials Processing Technology, Vol. 61, Nos. 1/2, pp.87–92.
Venkataraman, S. (2001) ‘A graph based frame work for feature recognition’, Proceedings of 6th
Annual Symposium on Solid Modelling and Applications, SMA’01, pp.194–205.
Xu, X., Wang, L. and Newman. S.T. (2011) ‘Computer-aided process planning – a critical
review of recent developments and future trends’, International Journal of CIM, Vol. 24,
No. 1, pp.1–31
Zhou, F.B.S. (1996) Form Feature and Tolerance Transfer from A Three-Dimensional Solid Model
To Set Up a Planning System, Master Thesis, The Texas Tech University, Lubbock, TX, USA.