Một phương pháp cải tiến nhận dạng đặc tính gia công cơ khí tự động từ mô hình cứng 3d

An Improved Method of Automatic Machining Feature Recognition from 3D Solid Model Phung Xuan Lan*, Hoang Vinh Sinh Hanoi Umversity ofScience and Technology, No.. Nam Received: Februar

An Improved Method of Automatic Machining Feature Recognition

from 3D Solid Model

Phung Xuan Lan*, Hoang Vinh Sinh Hanoi Umversity ofScience and Technology, No I Dai Co Viel Str., Hai Ba Trung, Ha Noi, Vie! Nam

Received: February 18, 2014; accepted: Aprd 22, 2014

Abstract

Automatic machining feature recognition from 3D solid model is seen as one of the most complicated tasks recognition method for extracting machining features from 3D solid model Overcoming the limitations of eartier studies, this proposed system is capable of not only recognizing many kinds of design features such sketch based design feature It is also effective to recognize both isolated and complex interacting feature extracted features are equipped with the essential manufacturing information that can be directly applicable for various applications such as computer aided process planning (CAPP)

Keywords: Feature recognition Rule-based method Machining feature

I Introduction

Integrated design and manufacturing systems

are considered as an effective approach to increase

productivity The initial step in designing such

integration system is machining feature recognition

machining featiire Design feature is a form feature or

geometric feature of interest to the designer such as

boss, sweep, and hole Machining feature is a

volume or material to be moved to produce a form

feature [ I ] The design feature contains detailed

geometric infonnation of part; however they are not

manufactiumg information directly used in the

manufacturing activities such as process planning In

the last two decades, many feature recognition

methods have been proposed for exttacting

machining information from geometric information

There are two main approaches: extemal approach

and intemal approach The first approach uses neutral

files in formats such as DXF, IGES or STEP to

exttact the desired features One of limitations of this

approach is that significant amount information

associated with the model is lost in the ttanslation

process [2] In the second approach, both the creation

of the CAD part model and the feature recognition

are done m the same feature based design CAD

system such as Solidworks, Pro-Engineer, Autodesk

one CAD system, it has some advantages such as the

accessibihty to the object library of design features

• Corresponding author: Tel: (+84) 935.^ 8.435

easily, the reduction of time for recognition process

this research

One of the most difficult tasks in feature recognition is the interaction feature which can distorts the relationship between faces, edges and characteristics of vertexes in the part and thus it results in the significant errors in feature recognition Among the intemal approaches, M.T.Hayasi e t a l recognized machining feature through the number of

its base face [2] The method was able to effectively recognize non-interacting features but couldn't applied for recognizing features whose boundaries at the 3D bounding box interacting each other such as

P M F 6 a n d P M F I 3 ( F i g 2)

X Zhou et.al [3] used similar method to M.T.Hayasi et.al Although it could recognize more kinds of design features, it still had same drawback None of these algorithms were able to handle the multiple-contour sketch based features This problem can be explained as follow The designer can

sketch For instance, there are three specific cases including (PMF2, PMF3), (PMF5, PMF6, PMF7) and (PMFI5, PMFI6) (Fig 4) which are constmcted from only one design feature named boss-extmde2, cut-extmde2 and cut-extrude7 respectively Both mentioned methods could only recognize them as one machining feature although they should be different machining featiues because of the differences of machining operations or cutting tools It is surely an undesirable result in feature recogmtion

I Open Solidworks applicabon with active part |

Algonlhm 2:

Oeteimining ihe sketch face and base face

AlgortJiin 3'

Recognizing feature interaction through

finding interaciion algorithm

Fig 1 The flow chart of recognition Fig 2 Feature interaction example Other method from V.S, Muniappan was

based on checking inner loop and outer loop of faces,

determining transition characteristic of each vertex

and the concavity of all edges on base face [4] It also

failed to recognize the interacting features such as

PMFI, PMF6 and PMF13 (Fig.2) The main reason is

changed due to interaction while the feature

definition was still not changed Hence, the

recognition result could be distorted One more

drawback of this method is that it limited to the

step but couldn't recognize the complex features

including revolve pocket, loft pocket and sweep slot

such as PMF4 (Fig 4) This paper seeks to overcome

the drawbacks of the existing methods through the

next section Algorithms of separating into

unit-machining features and determining the feature

interaction type according to each edge type are the

key to success of the proposed method

2 Proposed Method

The mle-based method is used to identify both

interacting and isolated featture in uniform way The

procedure of proposed method for feature recognition

is shown in Fig 1 Through this procedure, most of

major machining features according to ISO

10303-224 [5] such as pocket, slot, step, planar, boss, fillet

and chamfer with many kinds of shapes are

recognized

Algorithml: Separating into unit-design features if

exist

If the design feature composes of many sketch

contours and it is not boss-extmde-thin type,

algorithm I is applied to re-group faces of design

feature into multiple unit-groups

Stepl Determine the design feature composing of

multiple imit-features

Step2: Get all faces of the design feature Step3: Determine the similarity coefficient of faces

This similarity coefficient is based on the shortest sharing the same edge give the highest similarity coefficient

Slep4: Use the linear cell clustering algorithm [6] to

group together these faces that have the highest value

of the similarity coefficient to form face group

Step5 Determine the real type of unit features (cut,

boss, sweep, e t c )

Algorithm2: Determining the sketch face and the

base face of all features

Stepl: Determine the sketch face The sketch face is

the face on which the sketch was drawn

Step2: Determine the base face The base face is the

planar face having maximum number of concave or convex edges and its norma! is compared with too! axis, [4]

Step3 Determine the bottom condition of feature

The bottom condition code is 0 or I in case of through, blind feature respectively

Algorithm3: Recognizing feature interaction This

process is only earned out in case of blind cut feature

Stepl Determine the concavity of all edges of outer

loop on base face [4],

Stepl: Determine the interaction characteristic of

each edge of outer loop on base face Based on the basic types of interaction such as volume interaction, adjacent interaction and ttansition interaction [7], this

interaction types as shown in Table 1 It only

considers the interaction characteristic of each edge

type is shown in Fig 2

Table I Name and code of interaction

TvDe of edge

Concave edge

(inner edge)

Convex edge

(outer edge)

Tvoe of interaction

No interaction

Volume interaction

Boss interaction

Side interaction

Transition interaction

No interaction

Nested interaction

Side interaction

Volume interaction

Transition interaction

Code 2"

2' 2=

2=

2"

2^

2^

2^

1^

2"

Step3: Calculate the number of edge interaction for

each type defined by No-Edge(i) where i respects to

the superscript of interaction code If many edges are

on a same line or circle, the counting result is not

to prevent error due to volume interaction which

happens between PMFI and PMF8 as shown in Fig.2

Algorithm4: Recognizing machining feature

Rulel Cut-blmd recognition

For each cut-blmd feature,

Stepl: Machining type feature definition

If the feature is constmcted from a slot sketch or it

has only two planar side faces and they are parallel to

each other, it is a slot

If it is not a slot and No-Edge(5) is

a) < = I , the feature is a pocket

b) = 2 , ifsumofNo-Edge(0) + No-Edge(3) is

+ <= 2, it is a step

+ otherwise, it is a pocket

c) >=3, ifsumofNo-Edge(0) + No-Edge(3) is

+ <= 1, it is a step

+ otherwise, it is a pocket

Step2: Side-condition feattue definition

If No-Edge(5) is equal to

a) 0, the feature is a close feature

b) I, it is a one-side open feature

c) 2, it is a two-side open feature

e) otherwise, it is multiple-side open feature

Step3: Shape type feattire definition

Depending on the type of side faces (circular, planar, spline based surface.,,), the feature is defined

as a circular, polyline-based or spline-based shape type

Rule2: Cut-through recogmtion

For each cut-through feature in feature list, the feature is through closed pocket or through open

interacting feattues The feature is rectangular, circular or V slot dependmg on shape type

Rule3: Boss recognition

For each exttude featiue a) If the feature type name is "extmsion", the machining feature name is base

b) If the feature type name is "boss" the machining feature name is boss

c) The shape type feature is also recognized by checking type of side faces as mentioned before

Rule4: Hole-Wizard Recognition

Compared to extemal methods, the internal method has merit to reduce time for hole recognition

function

a) For each hole-wizard feature m the feature list, get type name feature

b) There are more than fourty type name codes Each code represents for one type of machining hole-feature, for example, code 5 represents for simple drill hole, code 20 represents for counter-bored through hole

Rule5: Revolve, sweep, loft recognition

a) In "revolve-cut" case, if it is open feature, the machining feature is a revolve pocket, otherwise, it is a revolve hole By checking the shape type of all faces of the feature and the

of revolve hole is defined such as counter-bored drillhole, simple hole

b) In "sweep-cut" case, if it is a open type and having a base face, it is a sweep slot, otherwise, it is a sweep pocket

c) In "loft-cut" case, it is a loft pocket d) In "boss" case, it is a revolve, sweep or loft boss respectively

Ruled: Draft recognition

If the feature type name is "draft", the

machining feature name is draft side face

3 CASE STUDIES AND DISCUSSIONS

The mput to the system is the ,sldprt file of the part

The part is constmcted in feature based design system

Solidworks modeler The recognition system and user

interface has been implemented using visual basic for

application (VBA) and automatic programming

interface (API) of Sohdworks

Two case studies having many kinds of interaction

and design features were tried out using proposed

method

Case study 1

Fig,2 shows a part model with many kinds of

interaction features The part is modeled in

Solidworks and saved as *,sldprt file Fig.3 shows

the result of recognition process The proposed

system can recognize all fifteen machining features

with detail information including the base design

feature, end condition, base face, sketch face, bound

feature As one machining feature in feature list is

machining feature are shown

While other algorithms have to create and analyze

virtual faces to deal with interaction problem, the

proposed method only considers the interaction

characteristic of each edge type Most importantly,

the algorithm is quite simple and effective As can be

seen, all complex voltune interaction features such as

PMFI, PMF6, PMFI3 and ttansition interaction such

as PMFI4 are easily recognized through the proposed

method This is due to that the number of edges really

affecting to the recognition result is exactiy

determined Thus, it can remove all effects of

interaction feature to machining feature recognition

Case study 2

Fig.4 shows the part which is constmcted usini multiple, overlapped and enclosed sketch contoun and many kinds of design features The recognitior process can be applied even through the sketch i; drawn on the reference plane and the extracted result

is shown in Fig.5

The proposed method can efficiently solve the multiple-contoiu sketch based design feature problem Seventeen machining feahires are recognized and extiacted from 3D solid model containing twelve design feattires As can be seen, both PMF2 and PMF3 belong to the same design feature (boss-extmde2) while PMF2 is a blind close circular pocket and PMF3 is a circular boss PMF9 is constmcted from two overlapped sketch contours,

although they are generated from one design feature named cut-exttude7 With the ability of separating mto unit-machining feahires, the designer is more flexible in designing 3D CAD model In addition, the proposed method can recognize various complex feahires such as close arc slot (PMF14) from cut-extmde6, close sweep slot (PMF4) from cut-sweepl and counter-bored drill hole-countersunk top (PMFI2) from cut-revolvel

Fig 3 Exttaction machining feature data of part

Fig 4 Part model for case study 2 Fig 5 Exttaction machining feature data for part

Eb

Fig 6 Extracted database relationship for

hole-machining feature

The extracted data is automatically transferred

from Solidworks to Microsoft SQL server (Fig 6) It

is essential data for process plannmg activities for

previous reported studies, the current work has many

capabilities as following: (a) to separate into

unit-machming features; (b) to distinguish and recognize

many complex interaction features; (c) to handle

many complex design features

4 Conclusions

In the present work, the process of machining

feature recognition from 3D solid model is

introduced The algorithm successfully recogmzes

interaction features The algorithm also solves the

multiple-contour sketch based design feature case

which is always used in design stage The proposed

method was verified by two case studies The

exttacted data will be used as input for CAPP Future

work would extend the scope to machining feature

conesponding to commercial computer aided

manufactiumg (CAM) packages

References

[1] Andrew Kusiak Computational intelligence in

design and manufacturing John Wiley & Sons

Inc, (2000) 112-113

[2] Mohammad T.Hayasi et.al Extraction of

manufacturing information from

design-by-feature solid model through design-by-feature recognition

Int J Adv Manuf Technology, 44 (2009)

[3] Xionghui Zhou et.al, A feasible approach to the

integration of CAD and CAPP Computer-Aided

Design 39 (2007) 324-338

[4] V.S, Muniappan, Automatic feature recognition and tool path generation integrated with process planning, MS Thesis University of Waterloo, Canada(2012)

[5] International Organization for Standardization,

2000, ISO 10303-224 Industiial Automation Systems and Integration-Product Data Representation and Exchange - Application Protocol: Mechanical product definition for process planning using machining features [6] Jerry C Wei et.al Commonality analysis: A linear cell clustering algorithm for group technology Intemalionai Joumal of Production Research, 27 (1989) 2053-2062

[7] V.B Sunil et.al An approach to recognize interacting features from B-Rep CAD models of prismatic machined parts using a hybrid ( and mle based) techmque Computers Industry 61 (2010) 686-701