22

. Anlaan

1996

ME 445

INTEGRATED MANUFACTURING SYSTEMS

PROCESS PLANNING

. Anlaan

1996

PROCESS PLANNING

The 21st century engineering response to world competition is concurrent engineering.

Concurrent engineering requires the integration of all aspects of the product life cycle, that is:

design,

manufacturing,

assembly,

distribution,

service,

disposal

Two important areas in the life cycle of a product are design and manufacturing. Process planning serves as an integration link between design and manufacturing.

Process planning consists of preparing a set of instructions that describe how to fabricate a part or build an assembly which will satisfy engineering design specifications.

The resulting set of instructions may include any or all of the following:

operation sequence,

machines,

tools,

materials,

tolerances,

cutting parameters,

processes (such as how to heat-treat),

jigs,

fixtures,

time standards,

setup details,

inspection criteria,

gauges,

graphical representations of the part in various stages of completion.

. Anlaan

1996

Process planning emerges as a key factor in CAD/CAM integration because it is the link between CAD and CAM. After engineering designs are communicated to manufacturing, either on paper or electronic media, the process planning function converts the designs into instructions used to make the specified part.

CIM cannot occur until this process is automated; consequently, automated process planning is the link between CAD and CAM.

CAPP

COMPUTER AIDED

PROCESS PLANNING

CAD

Process design

Process planning (CNC codes)

Tool selection

Facilities management

CAM

Conceptual design

Mathematical analysis

Geometric data

(graphical representation)

Some typical benefits of automated process planning include:

50% increase in process planner productivity

40% increase in capacity of existing equipment

25% reduction in setup costs

12% reduction in tooling

10% reduction in scrap and rework

10% reduction in shop labor

6% reduction in work in process

4% reduction in material

. Anlaan

1996

If the process planners productivity is significantly improved:

More time can be spent on methods, improvements and cost-reduction activities.

Routings can be consistently optimized.

Manufacturing instructions can be provided in greater detail

Preproduction lead times can be reduced.

Responsiveness to engineering charges can be increased.

The development of process plans involves a number of activities:

Analysis of part requirement

Selection of raw workpiece

Determining manufacturing operations and their sequences

Selection of machine tools

Selection of tools, workholding devices, and inspection equipment

Determining machining conditions and manufacturing time

ANALYSIS OF PART REQUIRENTS:

The part requirements can be defined as:

part features

process determination

steps of processes

dimensions

machine tool size

tolerance specifications

machine tool capability

CNC code generation

. Anlaan

1996

SELECTION OF RAW WORKPIECE:

It involves such attributes as:

shape

standard materials

rod

slab

blank

profile

pre-shaped materials

cast

forged

extruded

size

machine tool size

material

cutting conditions

tool selection

DETERMINING MANUFACTURING OPTIONS AND THEIR SEQUENCES:

selection of processes

availability

accuracy requirement

suitability

cost

sequence of operations

work holding method

cutting tool availability

SELECTION OF MACHINE TOOLS:

work piece related attributes

part features

dimensions

dimensional tolerances

raw material form

. Anlaan

1996

machine tool related attributes

process capability

size

mode of operation

manual

semiautomatic

automatic

CNC

tooling capabilities

type of tool

size of tool

tool changing capability

manual

automatic

production volume related information

production quantity

order frequency

EVALUATION OF MACHINE TOOL ALTERNATIVES:

Machine tool capability:

. Anlaan

1996

MACHINING CAPABILITY

(

)

=

x

-

x

or

=

R

d

2

s

s

2

1

-

n

MC

=

6

tolerance

100 (%)

s

*

MC < 100% capability is good

MC = 100% process is just acceptable

MC > 100% It is not acceptable ( or parts produced would have to be sorted)

PROCESS CAPABILITY

PC = 1/MC

PC = tolerance/6s

PC > 1 process is acceptable

unit cost of product:

The distribution of the size of finished parts are assumed to be normal

Z

=

t

Z

=

t

u

u

l

l

-

-

m

s

m

s

where:Zu and Zl are the standard normal variates for the

upper and lower tolerance limits,

tu and tl are the upper and lower tolerance

limits

m is the mean of the population

s is the standard deviation

. Anlaan

1996

portion of

accepted parts (AP) = F(Zu) - F(Zl)

where:F(Zu) is the probability of parts having

the dimension less than the upper tolerance value

F(Zl) is the probability of parts having the

dimension less than the lower tolerance value

portion of rejected parts (SC) = 1- AP

SC = 1- F(Zu) + F(Zl)

Yi = Yo + Ys

where: Yi = number of parts being machined

Yo = number of accepted parts

Ys = number of rejected (scraped) parts

SC

=

Y

Y

k

=

Y

Y

k

=

Y

Y

s

i

i

i

o

s

s

o

k

=

SC

1

-

SC

k

=

1

+

k

s

i

s

where: ki and ks are the technological coefficients

material balance

Yi = ki Yo

Ys = ks Yo

. Anlaan

1996

cost of a part

Xi Yi + Yi f(Yi) = Xo Yo+ Xs Ys

Xo = ki Xi - ks Xs + ki f(Yi)

where: Xi is the unit cost of a raw part

Xo is the unit cost (value) of a machined part

Xs is the unit value of a scraped part

f(Yi) is the processing (machining) cost per unit

average manufacturing lead time

T = S + t ki Yo

where:T is the average lead time

S is the setup time

t is the average machining (processing) time

EXAMPLE:

Suppose 500 units of a shaft are to be manufactured within

25

0.075

mm. Suppose there are three alternative machine tools as follows:

Types of machine tools

Standard deviation; s (mm)

Processing cost per Unit ($/unit)

Processing time per Unit (min/unit)

Setup time (min)

Turret lathe

0.175

7

1.00

15

Engine lathe

0.025

10

0.90

30

Automatic screw machine

0.013

15

0.70

60

Unit raw material cost = $10.00

Unit salvage value = $2.00

Process average = 25.038 mm

. Anlaan

1996

Determine the most suitable machine tool for the job.

(Take the turret lathe case first)

Z

=

25.075

-

25.038

0.175

=

0.21

Z

=

24.925

-

25.038

0.175

=

-

0.64

u

l

Use a normal distribution table to determine the scrap rate.

F(Zu) = 0.5832

F(Zl) = 0.2611

% of parts above upper tolerance limit =

(1 - 0.5832) x 100 = 41.68

% of parts below lower tolerance limit =

(0.2611) x 100 = 26.11

total scrap:

SC = 0.4168 + 0.2511 = 0.6779

technological coefficient of scrap:

technological coefficient of input:

ki = 1 + ks = 1 + 2.1047 = 3.1047

number of units scraped:

Ys = ks Yo = 2.1047 x 500 = 1052

number of raw part required:

Yi = ki Yo = 3.1047 x 500 = 1552

. Anlaan

1996

manufacturing lead time:

T = S + t Yi = 15+1.00 x 1552 = 1567 min

unit output cost:

Xo = ki Xi - ks Xs + ki f(Yi)

Xo = 3.1047 x 10.00 - 2.1047 x 2.00 + 3.1047 x 7.00

Xo = 48.47 $/part (for turret lathe case)

Type of machine tools

Unit cost

($/unit)

Scrap

(units)

Manufacturing lead time (min)

Turret lathe

48.57

1052

1567

Engine lathe

21.28

33

510

Automatic screw machine

25.03

1

410

Turret lathe should not be the choice. However there is a trade-off between the unit cost and the number of units of scrap as well as the manufacturing lead time for the engine lathe and automatic screw machine.

SELECTION OF TOOLS, WORKHOLDING DEVICES, AND Inspection EquIpment:

Tools

tool material

shape

size

nose radius

tolerance

Workholding devices

The primary purpose of a workholding device is to position the workpiece accurately and hold it securely.

manually operated devices

collets

chucks

mandrel

faceplates

. Anlaan

1996

designed devices

power chucks

specially designed fixtures and jigs

flexible fixtures used in flexible manufacturing systems

Inspection equipment

on-line inspection equipment

off-line inspection equipment

DETERMINING CUTTING CONDITION AND MANUFACTURIN TIMES:

Machining conditions

cutting speed

feed rate

depth of cut

Object is to set the cutting conditions in such a way that the economically best production state is achieved.

What is the economically best production state?

It is :

1- Minimum production cost

or

2- Maximum production rate

CHOICE OF FEED

Finishing cut: Proper feed rate to provide desired surface quality (relatively low)

Roughing cut: Feed rate is not effective as cutting speed over tool life, therefore, feed should be set to maximum possible value

limitations:

maximum tool force that the machine or the tool can stand and themaximum power available

CHOICE OF CUTTING SPEED

Cutting speed is set to provide the optimum tool life.

. Anlaan

1996

High V :low tool life

high tool cost

high production rate

short production time

Low V: high tool life

low tool cost

low production rate

long production time

MINIMUM COST PER PIECE:

Cost per

component, Cu =nonproductive cost

+ machining cost

+ tool changing cost

+ tooling cost

C

u

=

+

+

+

c

t

c

t

c

t

t

T

c

t

T

o

l

o

c

o

d

ac

t

ac

where:

co =labor and overhead cost ($/min)

ct = tool cost per cutting edge ($/edge)

tl = nonproductive time (min/piece)

tc = machining time (min/piece)

td = tool changing time (min/edge)

For a single pass turning operation:

t

c

=

p

LD

vf

where:

tc = machining time (min/piece)

L = length of workpiece (mm)

D = diameter of workpiece (mm)

v = cutting speed (mm/min)

f = feed rate (mm/rev)

. Anlaan

1996

Taylors equation for tool life:

vT

n

=

C

where:

v = cutting speed (mm/min)

T = tool life (min/edge)

n = Taylor exponent

C = cutting speed for one minute of tool life

(mm/min)

Combine the above equation one can get the cost per piece equation:

(

)

(

)

(

)

(

)

(

)

C

u

=

+

+

+

c

t

c

LD

vf

c

LD

vf

v

C

t

c

LD

vf

v

C

o

l

o

o

n

d

t

n

p

p

p

1

1

Differentiating this equation with respect to cutting speed and equating to zero, then solving for cutting speed will give the cutting speed for minimum production cost.

(

)

(

)

v

T

min

min

=

-

+

=

-

+

C

n

c

t

c

c

n

c

t

c

c

o

d

t

o

n

o

d

t

o

1

1

1

1

MAXIMUM PRODUCTION RATE:

Time per

piece:Tu = nonproductive time

+machining time

+tool changing time

(

)

(

)

(

)

T

or

T

u

u

=

+

+

=

+

+

t

t

t

t

T

t

LD

vf

LD

vf

v

C

t

l

c

d

c

l

n

d

p

p

1

. Anlaan

1996

Differentiating Tu with respect to v and equating it to zero, then solving for v will give the cutting speed for maximum production rate:

(

)

(

)

v

and

T

max

max

=

-

=

-

C

n

t

n

t

d

n

d

1

1

1

1

MANUFACTURING LEAD TIME:

Lead time = S + Tu Q

where:S = major set up time

Tu = production time per piece

Q = lot size

EXAMPLE:

A lot of 500 units of steel rods 30 cm long and 6 cm in diameter is turned on a CNC lathe at a feed rate of 0.2 mm/rev and a depth of 1 mm. The tool life is given by:

vT0.2 = 200 (m/min)

The other data are:

Machine labor rate = 10 $/hr

Machine overhead rate= 50% of labor

Grinding labor rate = 10 $/hr

Grinding overhead rate = 50% of grinding labor

Workpiece loading and

unloading time= 0.5 min/piece

Tool= Brazed insert

Cost of tool= 27.96 $/tool

Grinding time= 2 min/edge

Tool changing time= 0.5 min/edge

Tool can be ground only five times before it is discarded.

. Anlaan

1996

Determine:

a) Optimum tool life and optimum cutting speed to minimize the cost

b) Optimum tool life and optimum cutting speed to maximize the production rate

c) Minimum cost per component, time per component and corresponding lead time

d) Maximum production rate, corresponding cost per component, and lead time

SOLUTION:

a)

c

=

0.25 $

/

min

0

=

+

10

0

5

10

60

.

x

c

5.16 $

/

edge

t

=

+

+

=

27

96

6

2

10

0

5

10

60

.

(

.

)

x

T

T

min

min

min

=

-

+

=

-

+

=

1

1

1

0

2

1

0

25

0

5

5

16

0

25

84

56

n

c

t

c

c

x

o

d

t

o

.

.

.

.

.

.

(

)

v

82.3 m

/

min

min

=

=

=

C

T

n

min

.

.

200

84

56

0

2

b)

(

)

T

2 min

v

m

/

min

max

max

=

-

=

-

=

=

=

=

1

1

1

0

2

1

0

5

200

2

174

1

0

2

n

t

C

T

d

n

.

.

.

max

.

. Anlaan

1996

c) Minimum cost:

t

LD

v

=

3.14 x 300

x 60

x 82.3 x

0.2

=

3.4 min

/

piece

c

min

=

p

f

1000

C

u

=

+

+

+

c

t

c

t

c

t

t

T

c

t

T

o

l

o

c

o

d

ac

t

ac

Cu = 0.25 $/min x 0.5 min/piece

+ 0.25 $/min x 3.43 min/piece

+ 0.25 $/min x 3.43 min/piece

x (1/84.56) edge/min x 0.50 min/edge

+ 5.16 $/edge x 3.43 min/piece

x (1/84.56) edge/min

Cu = 1.20 $/piece

Time per component:

T

u

=

+

+

t

t

t

t

T

l

c

d

c

Tu = 0.5 min/piece

+ 3.43 min/piece

+ 3.43 min/piece

x (1/84.56) edge/min x 0.5 min/edge

Tu = 3.95 min/piece

Lead Time = 500 units x 3.95 min/piece

Lead Time = 1976.4 min

d) Maximum production rate:

LD

v

=

3.14 x 300

x 60

x 174.1 x

0.2

=

1.62 min

/

piece

min

p

f

1000

. Anlaan

1996

Production time per piece:

T

u

=

+

+

t

t

t

t

T

l

c

d

c

Tu = 0.5 min/piece

+ 1.62 min/piece

+ 1.62 min/piece x () edge/min

x 0.5 min/edge

Tu = 2.53 min/piece

Lead Time = 500 units x 2.53 min/piece

Lead Time = 1264.4 min

Cost for maximum production rate:

C

u

=

+

+

+

c

t

c

t

c

t

t

T

c

t

T

o

l

o

c

o

d

ac

t

ac

Cu = 0.25 $/min x 0.5 min/piece

+ 0.25 $/min x 1.62 min/piece

+ 0.25 $/min x 1.62 min/piece

x (1/2) edge/min x 0.50 min/edge

+ 5.16 $/edge x 1.62 min/piece

x (1/2) edge/min

Cu = 4.82 $/piece

THE PRINCIPAL PROCESS PLANNING APPROACHES:

Manual experience-based process planning method

Computer-aided process planning method

. Anlaan

1996

Manual experience-based process planning method:

most widely used method

time consuming

inconsistent plans

requires highly skilled, therefore, costly planners

Computer-aided process planning method:

it can systematically produce accurate and consistent process plans

it can reduce the cost and lead time of process planning

less skilled process planners may be employed

it increases the productivity of process planners

manufacturing cost, manufacturing lead time and work standards can easily be interfaced with the CAPP system

Organizational

planning

system

CAD

MRP

Material resource

planning

Capacity planning

CAPP

CAM Production control

Machine tool

Fixture

Data bank

Product design and

development request

Corrected data

Part list

Geometry data

Parts master file

Process plan

Production

order

Actual

data

NC

program

Corrected

data

A computer-aided process planning framework

There are two basic methods used in computer-aided process planning:

1) Variant CAPP method

2) Generative CAPP method

. Anlaan

1996

The Variant CAPP Method:

process plan is developed for a master part which represent the common features of a family of parts

a process plan for a new part is created by recalling, identifying, and retrieving an existing plan for a similar part and making necessary modifications for the new part

to use the method efficiently, parts classifying coding system must be used

Advantages of variant process planning:

efficient processing and evaluation of complicated activities and decisions, thus reducing the time and labor requirements

standardized procedures by structuring manufacturing knowledge of the process planers to companys needs

lower development and hardware costs and shorter development times

Disadvantages of variant process planning:

maintaining consistency in editing is difficult

it is difficult to adequately accommodate various combinations of

material,

geometry,

size,

precision,

quality,

alternative processing sequences,

machine loading

The quality of the final process plan generated depends to a large extent on the knowledge and the experience of the process planners

The Generative CAPP Method:

In a generative approach, process plans are generated by means of

decision logic

formulas

technology algorithm

geometry based data

to perform uniquely the many processing decisions for converting a part from raw material to a finished state

. Anlaan

1996

There are basically two major components of generative process planning system:

a geometry based coding scheme

process knowledge in the form of decision logic and data

Geometry Based Coding Scheme:

The objective is to define all geometric features for all process-related surfaces together with feature dimensions, locations, and tolerances, and the surface finish desired on the features.

The level of details is much greater in a generative system than a variant system.

Process Knowledge in the Form of Decision Logic and Data:

In this phase, part geometry requirement is matched with manufacturing capabilities in the form of decision logic and data.

Selection of

processes

machine tools

tools

jigs and fixtures

inspection equipment

sequence of operations

are achieved.

Finally, operation instruction sheets (for manual operations) or NC codes (for CNC) machines are generated.

DECISION TABLES:

Decision tables provide a convenient way to document manufacturing knowledge.

EXAMPLE:

Consider the problem of the selection of lathes or grinding machines for jobs involving turning or grinding operations. Data on conditions such as lot size, diameter, surface finish and tolerance desired are available.

. Anlaan

1996

They are compiled in form of a decision table as shown below.

Conditions

Rule 1

Rule 2

Rule 3

Rule 4

LS< = 10

X

LS>= 50

X

X

LS>= 4000

X

Relatively large diameter

Relatively small diameters

X

X

X

X

SF 2-3 mm

X

SF 1-2 mm

X

X

X

+-0.05 < tol