Automated cutting tool selection and cutting tool sequence optimisation for rotational parts

ARTICLE IN PRESS

Robotics and Computer-Integrated Manufacturing 20 (2004) 127–141

Automated cutting tool selection and cutting tool sequence optimisation for rotational parts Ali Orala,*, M. Cemal Cakirb a

Mechanical Engineering Department, Balikesir University, Balikesir, Turkey b Mechanical Engineering Department, Uludag University, Bursa, Turkey

Abstract The aim of this work is to define computer-aided optimum operation and tool sequences that are to be used in Generative Process Planning System developed for rotational parts. The software developed for this purpose has a modular structure. Cutting tools are selected automatically using the machinability data, workpiece feature information, machine tool data, workholding method and the set-up number. An optimum tool sequence is characterised by a minimum number of tool changes and minimum tool travel time. Tool and operation sequence for minimum tool change are optimised with a developed optimisation method that is based on ‘‘Rank Order Clustering’’. r 2003 Elsevier Ltd. All rights reserved. Keywords: Computer-aided process planning; Tool selection; Operation sequence; Tool sequence; Optimisation

1. Introduction The first step and one of the main objectives of a computer integrated manufacturing system is to integrate the computer-aided design (CAD) and computeraided manufacturing (CAM) components. The total integration of these two components into a common environment CAD/CAM is still under development. Many of the major developments have been uncoordinated and there is a great deal of overlap in terms of their intended functions. For example, the present CAD/CAM systems have their strength in geometrical definition, i.e., CAD component and CAM is mostly limited to CNC programming. Other important intermediate elements such as process planning are not included. This is due to the fact that the numerical information generated by a CAD system is not sufficient for process planning. Computer-aided process planning systems available in the market are incomplete and limited when compared to the number of CAD and CAM systems available [1]. Process planning is an activity, which determines appropriate procedures to transform a raw material into *Corresponding author. Tel.: +90-266-612-1257. E-mail addresses: [email protected] (A. Oral), [email protected] (M.C. Cakir). 0736-5845/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.rcim.2003.10.006

final product. In manufacturing industry, the task of process planning mainly consists of determining the usage of available resources, such as machine tools, workholding devices, cutting tools, generation of operation sequence, determining machining parameters (i.e., cutting speed, feed rate, depth of cut) and selection of auxiliary functions [2]. The production cost of a component depends upon cost of the workpiece material, tooling cost and overhead costs. Generally, these costs associated with machining a part are fixed; thus the only scope to reduce the overall cost of the part is to focus on the tooling cost. Selection of optimal tooling directly affects the part cost [1]. In the view of the significant reductions in cost that can be obtained by selecting the correct cutting tool and its associated optimum cutting conditions, it is considered that any selection system that does not take into account all of the relevant technological parameters has several limitations [3]. Production time is defined as the machining time plus non-machining time to machine a component. Determination of optimal sequence cutting tools on turret magazine of a CNC machine tool is an important task for achievement of optimal machining sequences for reducing total nonmachining time [4]. The aim of this work is to define computer-aided optimum operation and tool sequencing to be used in

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the generative process planning system developed for rotational parts (GPPS-RotP).

2. State-of-art of cutting tool selection The objectives of tool selection exercise are to select the best tool holder(s) and insert(s) from available cutting tools database. In the past, the operator would select the best tool set according to his experience, which cannot be converted into logic or algorithmic rules. This method is called as manual approach, which commonly results in errors and inconsistencies. Disadvantages of manual approaches led to development of automated approaches that aimed to reduce the probability of errors and inconsistencies. The correct choice of cutting tools is determined by the overall part configuration, rather than by individual contour section or workpieces. Computer-aided tool selection systems have been developed for this purpose. Plummer and Hannam [5] took workpiece material and profile geometry into account but ignored selection of carbide grade, chipbreaker, cutting edge length, and nose radius. Giusti et al. [6] developed the expert tool selection module for turning operations. This module depends heavily upon the expertise of the operator for an efficient structuring of the rule-based approach. Chen et al. [7] developed an automatic tool selection system for rough turning on a CNC lathe. Selection is made from appropriate tool library employing a heuristic method in order to reduce the search time. Tool selection procedure searches for the best tool for a desired operation. Out of the various potential tools, the only criterion for tool selection is least cost. Chen and Hinduja [8] used a tool selection process by checking collision between tool and workpiece or machine tool for workpiece to be machined. In case of any collision, use of two or more tools for machining is considered. Hinduja and Huang [2] carried out a study called OPPLAN in which they assumed that single tool was used for recess or groove machining. Domazet [9] used a hybrid approach in that both algorithms and production rules matrix method were used for tool selection; cutting conditions were determined using tool manufacturer data. Fernandes and Raja [1] carried out tool selection process for external and internal turning, but they considered only cylindrical and face turning operations. Edalew et al. [10] developed a computer-based intelligent system for automatic tool selection system. This system was operated in a fully interactive mode and information associated with a particular subject, such as part status, feature ordering (up to 12 feature types could be used to describe the component) and the component materials were incorporated into system. The analysis of the component included feature specification and dimensions, which were entered by the user.

3. Tool selection parameters Success in metal cutting depends on the selection proper cutting tool both in respect to the tool and material to be machined. The elements that influence the tool selection decision are: (i) workpiece materials, i.e., chemical and metallurgical state, etc., (ii) part characteristic, i.e., geometry, accuracy, finish and surface integrity, etc. (iii) machine tools characteristics including the workholder, tool number of the tool magazine and tool holder dimension, (iv) cutting tools or insert characteristics [11]. Cutting tools selection is a very important subtask involved in process planning systems. Tool selection module uses knowledge such as geometry for workpiece (feature recognition), surface finish, shape, location and direction tolerance, material of the workpiece, machinability data such as speed, feed rate, depth of cut, machine tool, set-up number, process type, workholding device. GPPS-RotP has seven modules as shown in Fig. 1.

3.1. Feature recognition The first step in automatic process planning activities is recognising the geometry of workpiece. Feature recognition is a design interface for process planning which is an automatic transfer of part description data from CAD system to process planning system [12]. The part-feature recognition system that is developed has got similarities with syntactic pattern-recognition technique developed by Fu [13]. Fu used 24 pattern primitives to formalise the pattern-recognition process. In the present work, 16 pattern primitives were defined as shown in Fig. 2. They are basically different shapes of line and arc segments with a start point, end point and a direction. Turning surfaces can be defined an elements such as diameter, taper, face, arc, chamfer, recess or grooving with the aim of pattern primitive. For example, a diameter can be represented by either the pattern primitive ‘‘A’’ or ‘‘C’’, a face can be represented by ‘‘D’’ or ‘‘B’’. In recognition, features are classified into two groups: primary features and secondary features as shown in Fig. 3. Primary form features are cylinder, taper and arcs. Secondary form features are form features other than cylinders, tapers and arcs often found on rotational components. Giving only the upper half of the 2D profile information, which is a series of lines and arc segments, does the definition of the geometry of a rotational part. A 2D profile information is expressed as a pattern string of ‘‘CBCFCDCDC’’ as shown in Fig. 4. Additional information such as surface roughness, shape, position and direction tolerances are the factors that the

ARTICLE IN PRESS A. Oral, M.C. Cakir / Robotics and Computer-Integrated Manufacturing 20 (2004) 127–141

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DATABASE

Workpiece Materials, Machinability, Machine Tools, Workholding Devices, Cutting Tools

DXF file of workpiece

Feature Recognition Module

Cutting Data Definition Module

Machine Tool Definition Module

Automatic Tool Selection Module

Workholding device selection module

Operation and Tool Sequencing

Tool Path Generation Module

Cutting data, machine tool, workholding device, cutting tools, tool and operation sequencing, tool path Fig. 1. Modules of GPPS-RotP.

developed software compares (Fig. 5). Feature recognition data of a sample part (see Fig. 6) is given in Table 1. In GPPS-RotP, if the maximum diameter is in the middle of the workpiece, the workpiece is divided into two regions: left and right regions. If the maximum diameter is at either end of the workpiece, then it is considered as a single region. 3.2. Determination of cutting conditions Machinability is the ability of the workpiece material to be machined, which means how easy or demanding it is to shape a workpiece with a cutting tool. Cutting speed, depth of cut and feed rate are the parameters that can be used as machinability data. The selection of suitable tools is carried out according to the type and geometry requirements of the operation selected to produce a particular profile. The complexity of the parameters that affected the cutting conditions lead to development of a set of computerised machinability data system [10]. In the present work, machinability data are obtained from Machining Data Handbook [14]. Inputs of the module developed for ‘‘machinability data definition’’ and the determination of cutting parameters are shown in Figs. 7 and 8, respectively.

G

D

C

F

H I J

O P

KL

M N

A

B

E

Fig. 2. Pattern primitives for feature recognition.

For the specified workpiece and cutting tool material properties, cutting parameters are retrieved from the machinability database which considers the material type, hardness, contents and manufacturing process of the workpiece and cutting tool material. The speed and feed values can also be interpolated for a specified depth of cut. Cutting parameters due to the operations performed are given in Table 2. Since the main objective of this paper is tool selection and optimum tool sequencing, it is not intended to give any information about ‘‘Machine tool selection module’’ of GPPS-RotP. However, selection of workholding

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Workpiece External Features

Internal Features

Primary features

Secondary Features

Primary Features

Secondary Features

1-Cylinder 2-Face 3-Taper 4-Concave 5-Convex 6-Chamfer 7-Radius

1-Groove 2-Recess 3-Thread 4-Axial recess 5-Nicked radius

1-Cylinder 2-Face 3-Taper 4-Concave 5-Convex 6-Chamfer 7-Radius

1-Groove 2-Recess 3-Thread 4-Nicked radius

Fig. 3. Classification of features.

C B C F C D C D C Original set Recess number 1 was excluded from the set CBCCCDC after it was filled. Recess number 2 was excluded from the set CBCDC after filling and cylindrical element character CCC C (C) was assigned instead CCC was changed to C.

(a)

(b) Fig. 4. (a) A nested recess; and (b) an example of feature recognition for a nested recess.

Fig. 5. Feature recognition module.

method needs to be explained in detail since it does affect the cutting direction. 3.3. Selecting the workholding method Safe, fast, accurate and rigid means of holding workpieces on lathes are critical requirements for

successful turning. All the power required at the cutting tool must be transmitted through the workholding device to workpiece. As a result, solid gripping of workpiece is essential. Force requirements for safe workholding depend on many variables, including the geometry and overhang of the workpiece, workpiece materials and their properties,

ARTICLE IN PRESS A. Oral, M.C. Cakir / Robotics and Computer-Integrated Manufacturing 20 (2004) 127–141

cutting tools used, speed and feet rates and whether the workpieces must be kept free of marks and distortion. Turned components could be clamped by different methods of workholding such as barfeed, chuck, clamping one end of a component in a chuck and supporting the other end by centre, between two centres and special fixture [15].

131

Because of workpiece configuration design specification, it cannot be possible to machine the workpiece in one set-up. To guarantee concentricity and run out, requirements are machined in the same set-up as their reference element(s). When machining a long slender shaft, two centres are normally used and this guarantees concentricity and run out requirements [16]. An example flow chart for workholding selection process is depicted in Fig. 9. A typical screen image of the developed software for an example is shown in Fig. 10. Number of set-up should be kept at minimum since this would affect the total time for workpiece production. In the present work, this criterion was taken into consideration. The method of clamping and the number of set-ups are determined by the software that considers the geometry of workpiece, surface roughness, machine tool, shape and position tolerances, and the elastic deflection caused by the cutting forces. Various cutting tools that have various functions are to be used in machining of a workpiece. In the present work, outer and inner surfaces are evaluated separately in tool selection. Cutting tools are chosen for the

Fig. 6. Sample workpiece.

Table 1 Feature recognition information extracted by GPPS-RotP feature recognition module Feature

X1

Y1

X2

Y2

XC

YC

h

Left angle

Right angle

r

Surface finish (Rmax ; mm)

Chamfer angle

Internal taper Internal cylindrical Internal recess Internal cylindrical Internal right recess Internal cylindrical Internal recess Internal cylindrical Internal right recess Internal cylindrical Internal face Internal cylindrage External face External cylindrage External V recess External V recess External cylindrical External face External cylindrical External right recess External recess External recess External recess External cylindrical External recess External recess External cylindrical External face External right taper External left taper External face

62 72 105 109 114 130 140 145 155 171 183 183 200 200 188 174 140 132 132 122 100 98 91 59 54 52 48 42 42 34 20

0 15 15 15 15 15 15 15 15 15 15 20 20 30 30 27 30 30 35 35 31 27 27 35 35 31 35 35 40 50 30

72 105 109 114 130 140 145 155 171 183 183 200 200 188 140 164 132 132 122 59 87 95 88 54 48 49 42 42 34 20 20

15 15 15 15 15 15 15 15 15 15 20 20 30 30 30 27 30 35 35 35 31 27 27 35 35 31 35 40 50 30 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 3 0 3 0 3 0 3 0 0 0 0 0 3 3 0 0 0 4 4 3 3 0 4 4 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 30 0 0 0 20 0 0 0 0 0 22 60 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

25 12.5 25 12.5 25 25 25 25 25 25 25 25 25 12.5 25 25 12.5 25 12.5 25 25 25 25 12.5 25 25 25 25 12.5 12.5 25

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

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Fig. 7. Material selection.

Fig. 8. Determination of cutting parameters.

Table 2 Cutting parameters due to the operations performed Workpiece material: unalloyed steel—free machining-carbon steel; condition: hot rolled or annealed; hardness: 100–150 HB Process

Tool material

Coated/uncoated

Tool const.

Width/diameter

Speed (m/min)

Feed (mm/rev)

Dept of cut (mm)

Rough turning Finish turning Drilling Boring Boring

Carbide Carbide Carbide Carbide Carbide

Coated Coated — Coated Coated

Indexable Indexable Indexable Indexable Indexable

— — 21.00 — —

185 240 150 190 365

0.5000 0.1800 0.0900 0.2500 0.0750

4.000 0.500 — 2.500 0.250

ARTICLE IN PRESS A. Oral, M.C. Cakir / Robotics and Computer-Integrated Manufacturing 20 (2004) 127–141 geometric data of the workpiece, user defined position and shape tolerance(udp/st), cutting forces

Analysis of the workpiece for Clamping Surfaces(CS) (Clamping surfaces are cylindirical surfaces on workpiece)

CS is available on workpiece?

Workpiece can conventionally be machined ?

N

fixture=Special workholding method

N

Y Y fixture=Between the centres

L/D <=4 L:diameter of workpiece D:length of workpiece

Y

ed<=udp/st ed:elastic deflection (occurred due to the cutting forces)

Y

N

N

fixture=CHUCK-CENTER L/D > 4 and L/D<=10

N fixture=Between the centres

fixture=CHUCK

Y

N

ed<=udp/st

fixture=Between the centres supporting element

Y fixture=CHUCK-CENTRE

Fixture File

Fig. 9. Flow chart of workholding selection.

Fig. 10. An example of workholding method selection.

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following operations: rough and finish turning, recessgroove turning, threading, face grooving, drilling, boring and inner recess and grooving.

4. Cutting tool selection Cutting tools that are considered consist of two main components: the tool holder and indexable insert. The objective of any tool selection is to determine several parameters such as tool holder (clamping system, type, point angle, hand of cut, size, etc.), insert (shape, size, grade, nose radius, etc.), cutting conditions (in this work insert size is determined according to specified cutting data), type of coolant (if required) and total cost of machining the components [17]. The outline for selecting indexable turning tool selection is first to select the tool holder system, followed by the tool holder and finally the suiting insert. In the present work, tool selection is feature based and fully automatic. Required information for tool selection are: machinability data, feature recognition for workpiece, machine tool to be used, workholding device and initial operation sequence. Initial operation sequence consists of four basic steps: machining of right-external zone (if workpiece consists of two zones, right zone has machining precedence), machining of right-internal zone, machining of leftexternal zone, machining of left-internal zone. Initial operation sequence is changed automatically according to the clamping surface defined by clamping method module. The selection of tool holders is based on the basic machining operations required to transform the workpiece into desired shape. The first check is that the tool holder is of a suitable overall type. Certain critical dimensions of the cutter must also be checked against the shape of the operation, such as effective cutting edge length and gauge length. The overall size of the tool must also fit into the machine tool magazine [18]. 4.1. Cutting tool selection for rough turning operations The various geometrical parameters defining indexable inserts for turning tools are included in ISO code. Tool selection module not only takes the parameters in the ISO codes into consideration, but carbide grades and functions of tools as well. In the present work, inserts with 95
of approach angle and 80
of point angle are considered first for rough turning operations. This enables them to machine stepped profiles without any geometric collision problem.

4.2. Tool selection for recess and groove turning In comparison to tool selection criteria used for rough turning, more comprehensive tool selection criteria should be used for recessing and grooving. The recess term used in this paper refers to a feature that has a minimum width of 16 mm and that can be machined by one or two tools of opposite hands [2]. The study reported herein adopts this definition. Yet it does not use this definition as a sole criterion for cutting tool selection for groove and recess. The width of a feature is commonly used as a criterion for classifying it as a groove. If no accessibility problem occurs during machining, then another cutting tool other than grooving tool can be selected. The characteristics of the features such as width, depth, and concave, convex and taper parts should also be considered in selecting appropriate cutting tools. In tool selection process, it is necessary to analyse the feature information through a series of IFyTHEN structures. Thus, appropriate tool holder and insert are automatically chosen from the tool library. Insert with the largest point angle is the most preferred one in terms of insert strength, therefore is the starting point. However, large point angle may cause a problem in accessing to the feature. Accessibility to the feature is then checked for the tool with a smaller point angle. This control routine is carried on until the most appropriate tool is found. If this control routine cannot find any appropriate tool for recessing, the accessibility of two tools to the feature is tested via methods of geometric analyses. Different criteria to be used to machine a recess with a single tool and appropriate tool parameters are given in Table 3. Different recessing methods and tools are sketched in Fig. 11. Recesses that can be machined with a single tool or two tools are shown in Fig. 11a and c, respectively. For any problem in accessing to the feature with all available tools, accessibility of the feature using two tools is checked through methods of geometric analyses. Geometric analyses are applied to check any collision between workpiece and tool that prevents accessibility to the feature. If there is any collision, the geometry of workpiece is temporarily modified as shown in Fig. 11b. For the un-machined region on the recess/ groove, another tool with an opposite feed direction is chosen (Fig. 11c). For the temporarily modified geometry, there should be no collision between workpiece and tool to be able to machine the recess/groove. If no collision is detected, two tools are assigned for the operation. Geometric analysis in tool selection module ATOS (Automatic Tool Selection Module) is carried out as follows: 1. During the last pass of the first tool that does the machining, first contact point K of tool on the groove base is determined. 2. Groove contact point L of the second tool that finishes the machining is determined.

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Table 3 Different criteria that are to be used to machine a recess with a single tool and appropriate tool parameters No.

Shape of feature

1

Control criteria

Insert clamping method

Insert shape

Tool holder type

Clearance angle on major cutting edge

Entering/ insert angle

0oap22:00

M

T

J

N

93/60

22:01oap27:00 27:01oap44:00 44:01oap50:00

P M S

D V V

J J J

N N B

93/55 93/35 93/35

0oap22:00

M

T

J

N

93/60

22:01oap27:00 27:01oap44:00 44:01oap50:00 50:01oap55:00 55:01oap60:00 60:01oap70:00

P M S M S S

D V V T D V

J J J E N V

N N B N C B

93/55 93/35 93/35 60/60 63/60 72.5/35

0oap22:00

M

T

J

N

93/60

22:01oap27:00 27:01oap44:00 44:01oap50:00

P M S

D V V

J J J

N N B

93/55 93/35 93/35

α 1 α

2

α

α

2

3

α 3 α

α

A B

β

D

A

A

D

D

B

C

K

β>α

B

C

L

K

C

β<α

(a)

(b)

A B

(c)

D

A B

KL C

(d)

D C

(e)

Fig. 11. Various examples of recess/grooves turning.

After steps 1 and 2, one can conclude that: 1. If L is smaller than KðLoKÞ; groove or recess can be machined by two tools and tool selection is done accordingly (see Fig. 11c).

2. If L is bigger than KðL > KÞ; due to the collision between workpiece and tool, recess or groove cannot be machined by two tools (see Fig. 11d). In this case recessing tool has to be chosen for machining (Fig. 11e).

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In the present work, tool selection is also possible for recesses/grooves that lie inside each other (Fig. 12). In this process, the tool to machine the recess on outside diameter is determined by the method outlined above. In the tool selection process to machine groove K1 ; collision between workpiece and tool is checked by considering the groove at upper level. In this control, both collision check for groove K1 and tool and accessibility check for groove K2 are done. Accessibility check for groove K1 is carried out by the method explained above. In the tool selection process for groove K2 ; first thing to check is whether a single tool can machine the groove or not. There are two conditions to machine a groove K2 shown in Fig. 13a. Firstly, tool must not collide the groove K1 when it moves with the largest trailing angle. Secondly, trailing angle b must be larger than angle a: To prevent any collision between tool and groove K1 ; x coordinate of A ðAx Þ must be less or equal to the starting point of groove K1 : If this condition is satisfied no collision occurs. Ax can be calculated as in Eq. (1).

Fig. 13b). To be able to use the second tool to machine the region that was not machined by the first tool, the distance between C1 and C2 should be bigger than f1 : If this is not true, groove K2 has to be machined by a groove tool.

Ax ¼ Bx þ h=tanðaÞ:

5. Optimisation of operation and tool sequence

ð1Þ

If Ax is larger than starting point of groove K1 and/or boa; it is not possible to machine groove K2 by one tool. In this case two tools should be considered for the operation. In this process groove contact point C1 of first tool during last pass is determined first (see

K1 K2 K3 Fig. 12. Recess and groove turning using two tools.

4.3. Tool selection for various other operations Tool selection module is capable of selecting tools for face grooving, threading, internal turning, drilling, and boring and internal recess/groove turning operations. Different types of face grooves and related cutting tool parameters [19] are given in Table 4. Feature accessibility, hole diameter, distance of internal recess/groove to the tool side are important factors that affect tool selection for internal recesses/ grooves. Various internal recess/groove types and related tool parameters are given in Table 5.

Having completed the tool selection outlined above, tool elimination is done in order to reduce the number of tools. An optimum tool sequence is characterised by a minimum number of tool changes and minimum tool travel time. Tool and operation sequence for minimum tool changing are optimised with a developed optimisation method that is based on ‘‘Rank Order Clustering’’ [20]. Recess tools are specially taken into consideration during cutting tool elimination. For instance, if two tools were selected for two recesses having two different widths, larger recess tool is excluded from the tool list when possible. Once tools required for manufacturing are all determined, optimum tool order has to be investigated for minimum tool changes. Thus, the diameter matrix that holds the diameters of the features and the tools that machine these features is generated. This is the matrix that is also used in optimisation process. If the

2th tool

recess start point

f1

A h

K1 B

c2

K2

(a)

K2

(b) Fig. 13. Rules for nested recesses.

c1

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Table 4 Types of face grooves and related cutting tool parameters Feature shape

α

α

Control criteria (angle)

Sandvik code

Insert clamping method

Insert shape

Tool holder type

Clearance angle on major cutting edge

Entering/insert angle

0oap21:99 22:00oap26:99 27:00oap43:99 44:00oap49:99 50:00oap59:99 aX60

C3 =C4 C3 =C4 C3 =C4 C3 =C4 C3 =C4 C3 =C4

M P S M S S

T D D V V V

J J J J J V

N N C N B B

93/60 93/55 93/55 93/35 93/35 72.5/35

Table 5 Various internal recess/groove types and related tool parameters Shape of feature

α

Max. angle

Min. hole diameter

Tool type

Insert code

Entering/insert angle

24

32

PTFN

T

91/60

27

32 20 13 20 22 50

PDUN L 571.05C SDUC L 571.05C SVQB MVUN

D D D D V V

93/55 93/55 93/55 93/55 107.5/35 93/55

20

L AG 551.31

N151.3

90/90

32

L AG 151.22

N151.3

90/90

Dmin α

Dmin

30 35 50

Dmin Dmin

workpiece has to be machined in two set-ups, each set-up should be evaluated separately. There are mainly two steps in optimisation: First step: Diameter matrix is generated. In the diameter matrix, rows are for the tool codes and columns are for the feature numbers on the workpiece. This means i of the diameter matrix D½i; j represent the tool code and j represents the feature number. The diameter of the jth feature that will be machined by ith tool is the D½i; j element of the matrix. If there is no operation to be performed to the jth feature by the ith tool, then ‘‘null’’ is assigned as the diameter value. External turning tools have a higher priority; therefore, they need to be in the first row. Since threading and axial recessing are the last operations, these tools are not

included into the optimisation process. They are added to the end of tool list. Consequently decimal weights for rows are calculated by multiplying each column by 2i as follows: wi ¼

number of rows X

Diameterði; jÞ2i :

ð2Þ

i¼1

After the sum of decimal weights for each column is calculated, columns are ranked in descending order accordingly. First row is for the tool that forms the external shape; therefore, it is excluded from the sorting process. The matrix is then rearranged. Second step: Tool order is generated. The value of ‘‘1’’ is assigned to the matrix elements that are non-zero.

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Begin

10

20

Classification of the feature to be machine by same tool

Sort the w(i) s in descending order in the first row (except the first tool). Arrange the operation sequence

Sort the w(j) s in descending order: Arrange the new tool sequence

Tool List

i=1, number of tool j=1, number of feature

Diameter(i,j)=Feature diameter(j) (Diameter of j th feature machined by i th tool)

Form the solution matrix that represents new tool and operation sequence according to the new arrangements

i=1,number of tool

j=1, number of feature

No

Tool and operation sequence that gives the minimum tool change

Diameter(i,j)<>0 Yes Tool matrix(i,j)=1

i=1,number of tool

END i=1,number of tool

j=1, number of feature j=1, number of feature

w (i) = 2i * Diameter(i, j)

w(j) = 2 j * Tool matrix (i, j)

10

20

Fig. 14. Flow chart of optimisation and tool sequencing process.

Decimal weights for columns are calculated by multiplying each row with 2j : Then all these weights are summed and rows are ranked this time in ascending order according to their sum of weights. wj ¼

numberX of columns

26 27 29

25

28

24 23

30

31

22

20 21

19 18 17 16

j

Tool matrixði; jÞ2 :

ð3Þ

32

14

j¼1

At the end of the process the tool order that provides minimum tools change is established. Flow chart of optimisation and tool sequencing process is given in Fig. 14.

15

1

2 3

4

5

6

7 9 8

11 10

12

13

5.1. Sample workpiece Tools chosen by ATOS for the workpiece shown in Fig. 15 are presented in Table 6. Sample workpiece has two regions: right and left regions. Outer and inner recesses are evaluated separately for both regions. For the right outer region, diameter matrix and tool order matrix are given in Table 7 and 8, respectively. Generation of the diameter matrix and the tool order matrix for the external right of the sample workpiece is as follows: After the classification of features that are to be machined using the same tool is completed, the

Fig. 15. Sample workpiece.

diameter matrix given in Table 7 is generated in two steps: (i) By placing the tools into first column and the features into first row, the matrix with the

ARTICLE IN PRESS A. Oral, M.C. Cakir / Robotics and Computer-Integrated Manufacturing 20 (2004) 127–141

dimension of ‘‘number of tools  number of features’’ is generated and ‘‘null’’ is assigned to the elements of the matrix. (ii) The diameter of the jth feature that will be machined by ith tool is assigned as the D½i; j element of the matrix. For instance, feature 26 (which will be machined by the tool coded PCLNL2020K09) has the diameter of 159 mm. This is repeated for the whole set of tools and features and the diameter matrix is generated. Operation sequence is generated in two steps by using the diameter matrix: (i) Matrix elements are multiplied by the weight factors (which is 2i where i is the row number). (ii) The decimal weights for columns are calculated by summing the products of multiplication (the decimal weights are kept at the last row of each column)

and the columns are ranked in descending order accordingly. Features that are machined by the first tool (features 26, 25, 20, 19, 18, 17, 16, 15 and 14) are kept unchanged (since PCLNL2020K09 forms the external shape).

The feature order obtained after this process is the operation sequence for the sample workpiece. The next step is the determination of tool sequence. The steps to be taken in order to do this are as such: (i) The value of ‘‘1’’ is assigned to the elements of the diameter matrix that are non-zero and the tool order matrix is generated (Table 8). (ii) Matrix elements are multiplied by the weight factors (which is 2j where j is the column number) and the decimal weights for rows are calculated. The rows are then ranked in ascending order (Table 9).

Table 6 Feature list and tool list for the sample workpiece Feature number

Tool holder order code

139

Insert order code

Insert grade

Tools selected for features on the external right 26 PCLNL 2020K09 25 PCLNL 2020K09 20 PCLNL 2020K09 19 PCLNL 2020K09 18 PCLNL 2020K09 17 PCLNL 2020K09 16 PCLNL 2020K09 15 PCLNL 2020K09 14 PCLNL 2020K09 24 RF151.22202030 23 RF151.22202060 22 RF151.22202030 21 MVJNL 2020K16

CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM N151.2.200-30-4G N151.2.800-80-4G N151.2.200-30-4G VNMG 16 04 12-PM

GC4025 GC4025 GC4025 GC4025 GC4025 GC4025 GC4025 GC4025 GC4025 GC235 GC235 GC235 GC4025

Tools selected for features on the internal right 3 R416.2-0370L40-41 4 S25T-PCLNL 09 5 S25T-PCLNL 09 6 S25T-PCLNL 09 8 S25T-PCLNL 09 10 S25T-PCLNL 09 12 S25T-PCLNL 09 13 S25T-PCLNL 09 7 L AG 151.32-32S-40 9 L AG 151.32-32S-40 11 S40V-PDUNL 15

WCMX 06 T3 08 R-53 CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM N151.3-500-40-4G N151.3-500-40-4G DNMG 15 06 12-PM

GC235 GC4025 GC4025 GC4025 GC4025 GC4025 GC4025 GC4025 GC235 GC235 GC4025

Tools selected for features on the external left 27 PCLNL 2020K09 29 PCLNL 2020K09 32 PCLNL 2020K09 30 RF151.22202030 31 L 166.4FG-2020-16 28 C3-MTJNR-22040-16

CNMG 09 03 08-PM CNMG 09 03 08-PM CNMG 09 03 08-PM N151.2.200-30-4G L166.0G-16MM01-050 TNMG 16 04 12-PM

GC4025 GC4025 GC4025 GC235 GC1020 GC4025

Tools selected for features on the internal left 2 S25T-PCLNL 09 1 S25T-PCLNL 09

CNMG 09 03 08-PM CNMG 09 03 08-PM

GC4025 GC4025

ARTICLE IN PRESS A. Oral, M.C. Cakir / Robotics and Computer-Integrated Manufacturing 20 (2004) 127–141

140

Table 7 Diameter matrix for the external right of the workpiece

PCLNL RF151A RF151B MVJNL Swi

26

25

20

19

18

17

16

15

14

24

22

23

21

159 0 0 0 318

159 0 0 0 318

104 0 0 0 208

104 0 0 0 208

100 0 0 0 200

92 0 0 0 184

88 0 0 0 176

88 0 0 0 176

84 0 0 0 168

0 90 0 0 360

0 94 0 0 376

0 0 94 0 752

0 0 0 104 1664

21 22 23 24

Table 8 Tool order matrix for the external right of the workpiece

PCLNL RF151A RF151B MVJNL

26

25

20

19

18

17

16

15

14

1

1

1

1

1

1

1

1

1

22

24

1

1

212

213

Swj 1022 12,288 2048 1024

1 22

23

24

25

26

27

Table 9 Optimum tool and operation sequence for the external right of the workpiece 26 25 20 19 18 17 16 15 14 21 23 22 24 PCLNL 1 MVJNL RF151B RF151A

1

1

1

1

1

1

1

1 1 1 1

1

1022 1024 2048 12,288

28

Table 10 Diameter matrix for the external left of the workpiece 27

29

32

30

159 0 318

104 0 208

96 0 192

0 96 384

21 22

Tool sequence

27

29

32

1

1

1

1

2

2

2

3

2

30 1 24

210

Tool holder order code

External features 1 PCLNL 2020K09

3

MVJNL 2020K16 RF151.22202060

4

RF151.22202030

Internal features 1 R416.2-0370L4041 2 S25T-PCLNL 09 3

Table 11 Tool order matrix for the external left of the workpiece

29

211

Table 12 Tool and operation sequence for the right region of the workpiece

2

PCLNL RF151A

23

1 21

PCLNL RF151A SwI

21

4

L AG 151.3232S-40 S40V-PDUNL 15

Insert order code

Machining sequence

CNMG 09 03 08PM

14, 26, 25, 20, 19, 18, 17, 16, 15 21

VNMG 16 04 12PM N151.2.800-804G N151.2.300-304G

WCMX 06 T3 08 R-53 CNMG 09 03 08PM N151.3-500-404G DNMG 15 06 12PM

23 22, 24

3 4, 5, 6, 8, 10, 12, 13 7, 9 11

Swj 14 16

Table 13 Tool and operation sequence for the left region of the workpiece Tool sequence

Sample workpiece shown in Fig. 15 has to be machined in two set-ups. For the left region of the workpiece that is to be machined in the second set-up, the same processes are repeated and diameter and tool order matrices are obtained. Diameter matrix for left outer region is given in Table 10 and tool order matrix in Table 11. Optimum tool and operation sequence for the right and left regions are given in Tables 12 and 13, respectively.

Tool holder order code

External features 1 PCLNL 2020K09 2 3 4

RF151.22202030 L 166.4FG-202016 C3-MTJNR22040-16

Internal features 1 S25T-PCLNL 09

Insert order code

Machining sequence

CNMG 09 03 08PM N151.2.300-30-4G L166.0G16MM01-050 TNMG 16 04 12PM

27, 29, 32

CNMG 09 03 08PM

30 31 28

1, 2

ARTICLE IN PRESS A. Oral, M.C. Cakir / Robotics and Computer-Integrated Manufacturing 20 (2004) 127–141

6. Conclusion In this work, cutting tool selection was carried out by taking the geometry of workpiece, surface roughness, chip breaking area of the cutting tools, machinability data, machine tools information, workholding methods and number of set-ups into consideration. Tools are chosen and operation sequence is then optimised with a developed optimisation method that is based on ‘‘Rank Order Clustering’’. More than 500 practical rules and years of experience are used in the determination of machinability data, machine tool, workholding method and cutting tools; and the application of the software into practical life shows that the system developed is capable of providing fast and successful process plans for complex workpieces.

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