A GENERIC CONCEPTOF A MANUFACTURING

SYSTEMFOR VARIOUS PLANNING

AND EXECUTION SYSTEMS

Nico J. VandaeleUniversity of Antwerp

Department of Technology Managementnico.vandaele@ua.ac.be

Prof. Dr. Nico Vandaele, University of

Antwerp

Basic Dimensions of Planning

Material

Time

Resources

Prof. Dr. Nico Vandaele, University of

Antwerp

Lead Time Distribution

0

0,01

0,02

0,03

0,04

0,05

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

f(t)

Lead Time

Prof. Dr. Nico Vandaele, University of

Antwerp

Lead Time Distribution

0

0,01

0,02

0,03

0,04

0,05

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

f(t)

Lead Time

Prof. Dr. Nico Vandaele, University of

Antwerp

Lead Time Reduction

0

0,01

0,02

0,03

0,04

0,05

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Safety time

What about customer service and lead times quotes?

Prof. Dr. Nico Vandaele, University of

Antwerp

Lead Time Variability Reduction

0

0.01

0.02

0.03

0.04

0.05

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Safety time

What about customer service and lead times quotes?

Prof. Dr. Nico Vandaele, University of

Antwerp

Combined

0

0,01

0,02

0,03

0,04

0,05

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Safety time

What about customer service and lead times quotes?

Prof. Dr. Nico Vandaele, University of

Antwerp

Production Lead Times:Application for Planning?

Material Requirements Planning Just In Time Theory Of Constraints Finite Scheduling ACLIPS POLCA ...

Prof. Dr. Nico Vandaele, University of

Antwerp

MRP Logic

Tubex

Cap1

Leg4

Surface1

Screw16

Box1

Table1

Prof. Dr. Nico Vandaele, University of

Antwerp

MRP Logic

Time 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Table 20 Leg 80 80 80 80 80 Surface 20 20 20 20 20 20 20 20 20 20 20 20 20 20 Box 20 20 20 20 20 20 20 20 20 20 20 20 20 20 Screw 320 320 320 320 320 320 320 320 320 320 320 320 320 320 Tube X X X X X X X X X X X X X Cap 80 80 80 80 80 80 80 80 80 80 80 80 80

Prof. Dr. Nico Vandaele, University of

Antwerp

JIT Logic

Box

Surface Screw

Cap

Tube

Cutting

Welding

Chroming

Fixing Cap

Assembly

Quality Control

Packing

Prof. Dr. Nico Vandaele, University of

Antwerp

TOC Logic

Tube

Cutting

Welding

Cap

Chroming

Fixing Cap

Surface

Assembly

Box

Quality Control

Packing

Screw

Prof. Dr. Nico Vandaele, University of

Antwerp

TOC Logic

20 21 22 23 24 31302928272625

constraint rope

constraintoperation

shipping rope

release due-date

Prof. Dr. Nico Vandaele, University of

Antwerp

TOC Example 101

Time:

Cash: 3000

Week

Su Machines

Pace: D-FG

9876

4

3

5

2

1

RM

Length in weeks: 2 Weekly expenses: 11 000

H

B-20

G

C-10

R

M-10

W-30

2 2

200

43

6

3

4 4

1

3

2

100

DC F

20

4050350

3

2

1 2

7

1

2 2

1

A B

60

10

40

95 7 8 10

3

3

3

3

4

2 2

2 2

2

2

2

1

1

1

1

6

4 4

7

GE

Prof. Dr. Nico Vandaele, University of

Antwerp

FS Logic

packingquality control

assemblyfixing capchroming

cuttingwelding

Prof. Dr. Nico Vandaele, University of

Antwerp

ACLIPSA

Capacity and Lead Time Integrated

Procedure for Scheduling

Lot Sizing & Lead Time Estimation

Phase

Lot Sizing & Lead Time Estimation

Phase

Tuning PhaseTuning Phase

Scheduling PhaseScheduling Phase

Execution PhaseExecution Phase

OrdersOrders

ResourcesResources

CalandarsCalandars

BOMBOM

RoutingRouting

OvertimeOvertime

OffloadsOffloads

Late Orders

Late Orders

Lot SizesLot Sizes Lead TimesLead Times

Dispatch Lists

Dispatch Lists

Picking Lists

Picking Lists

WIP LotsWIP Lots

New LotsNew Lots

F.G. Inventory

F.G. Inventory

ScrapScrap

ReworkRework Real Time Update

Work Progress

Work Progress

Prof. Dr. Nico Vandaele, University of

Antwerp

Mini Metal

Cutter

Grinder

Lathe

P P

S

S

Prof. Dr. Nico Vandaele, University of

Antwerp

Customer Orders

Product P Order 1 2 3 4 5Quantity 1 5 3 2 4Due Date 22 28 37 41 44

Product S Order 1 2 3 4 5Quantity 1 3 2 3 1Due Date 17 18 19 22 24

Order 6 7 8 9 10Quantity 1 3 2 3 1Due Date 26 27 30 33 34

Order 11 12 13 14 15Quantity 2 3 3 1 1Due Date 35 36 39 42 44

Prof. Dr. Nico Vandaele, University of

Antwerp

Production Parameters

Product Machine Average Variance Average VarianceSetup Setup Processing ProcessingTime Time Time Time

P Cutter 20 0 30 0Grinder 20 400 10 100Lathe 24 0 12 0

S Lathe 16 0 8 0Grinder 20 400 10 100

Prof. Dr. Nico Vandaele, University of

Antwerp

Lot Size and Lead Time Results

Product Optimal Operation Utilization Waiting Setup Processing Lead Lot Size Time Time Time Time

P 4 cutter 73 7 20 120 147 grinder 87 109 20 40 169 lathe 82 41 24 48 113 collection 72 total 501

S 6 lathe 82 41 16 48 105 grinder 87 109 20 60 189 collection 61 total 355

Prof. Dr. Nico Vandaele, University of

Antwerp

Grouping Customer Orders

Lot Customer # Average Planned Due Release Orders Lead Lead Date Date Time Time

P1 1-2 6 534 719 528 -191P2 3-4 5 482 521 888 367P3 5 4 430 472 1056 584S1 1-2-3 6 295 351 408 57S2 4-5-6 5 277 336 528 192S3 7-8 5 277 336 648 312S4 9-10-11-12 9 349 397 792 395S5 13-14-15 5 277 336 936 600

Prof. Dr. Nico Vandaele, University of

Antwerp

Networka(50)

7(140)

c(30)

1(200)

4(170)

3(96)

6(84)

9(72)

b(84)

8(60)

d(80)

2(80)

5(70)

11(80)

19(70)

13(70)

15(70)

17(110)

10(64)

18(56)

12(56)

14(56)

16(88)

E

B

Prof. Dr. Nico Vandaele, University of

Antwerp

Gantt-chart

11

12

11

12

21

22

21

32

31

42

13

52 3222

332351

ij

ij

operation j of order i of product P

operation j of order i of product S

41

31

100 20 30 40

Prof. Dr. Nico Vandaele, University of

Antwerp

The POLCA Control System

Paired-cell Overlapping Loops of Cards with Authorization

Relates the releases on the shop floor to a push-signal and a pull-signal

Suri, Quick Response Manufacturing, 1998

Krishnamurthy, 2004

Prof. Dr. Nico Vandaele, University of

Antwerp

For P1 to start working on the order, the order needs to be authorized and P1 should have a P1/F2 POLCA card

2

P1

F2

P1/F2 LOOP

MATERIAL IN P1’S INPUT BUFFER

P1/F2

F2’S INPUT BUFFER

P1

AVAILABLE P1/F2 CARDS

P1/F2

P1 Cell Team’s Decision Process (after Authorization)

Prof. Dr. Nico Vandaele, University of

Antwerp

2

P1

F2

P1/F2 LOOP

MATERIAL IN P1’S INPUT BUFFER

P1/F2

F2’S INPUT BUFFER

P1

AVAILABLE P1/F2 CARDS

P1 Cell Team’s Decision Process (after Authorization)

For P1 to start working on the order, the order needs to be authorized and P1 should have a P1/F2 POLCA card

Prof. Dr. Nico Vandaele, University of

Antwerp

2

P1

F2

P1/F2 LOOP

MATERIAL IN P1’S INPUT BUFFER

P1/F2

F2’S INPUT BUFFER

P1

AVAILABLE P1/F2 CARDS

P1 Cell Team’s Decision Process (after Authorization)

For P1 to start working on the order, the order needs to be authorized and P1 should have a P1/F2 POLCA card

Prof. Dr. Nico Vandaele, University of

Antwerp

For F2 to start working on the order, the order needs to be authorized and F2 should have an F2/A4 POLCA card

F2/A4 LOOP

P1/F2 LOOP

P1

A4

F2P1/F2

F2/A4

F2/A4F2/A4

AVAILABLE P1/F2 CARDS

P1/F2

F2 Cell Team’s Decision Process (after Authorization)

Prof. Dr. Nico Vandaele, University of

Antwerp

F2/A4 LOOP

P1/F2 LOOP

P1

A4

F2P1/F2

F2/A4P1/F2

F2/A4F2/A4

AVAILABLE P1/F2 CARDS

F2 Cell Team’s Decision Process (after Authorization)

• For F2 to start working on the order, the order needs to be authorized and F2 should have an F2/A4 POLCA card

Prof. Dr. Nico Vandaele, University of

Antwerp

F2/A4F2/A4

F2/A4 LOOP

P1/F2 LOOP

P1

A4

F2P1/F2

AVAILABLE P1/F2 CARDS P1/F2

F2 Cell Team’s Decision Process (after Authorization)

For F2 to start working on the order, the order needs to be authorized and F2 should have an F2/A4 POLCA card

Prof. Dr. Nico Vandaele, University of

Antwerp

The POLCA Control System

Trade-off: Push - Authorization: urgency Pull - Card: capacity feasibility

POLCA does control the release as a function of available capacities downstream

Determination ofI. Release authorizationsII. Number of POLCA cards

Prof. Dr. Nico Vandaele, University of

Antwerp

I. Release Authorizations

A Capacity and Lead time Integrated Procedure for Scheduling (Vandaele et al., 1998):

- Lot Sizing and Lead Time Estimation Phase

- Tuning Phase

- Scheduling phase POLCA

- Execution

Prof. Dr. Nico Vandaele, University of

Antwerp

I. Release Authorizations

Product 1: A => B => CProduct 2: C => B

Prof. Dr. Nico Vandaele, University of

Antwerp

II. Number of POLCA Cards

mLT

D

BANumBLTALT *cards A/B ofNumber

mlNum /

Prof. Dr. Nico Vandaele, University of

Antwerp

II. Number of POLCA Cards

A. The number of manufacturing orders that go from workstation l to workstation m during the planning horizon D:

mokkolmkol

kkk

kK

k

O

omkol

OQQY

DOQmlNum

k

)1(

*1 1

Prof. Dr. Nico Vandaele, University of

Antwerp

II. Number of POLCA Cards

B. The weighted ‘average’ lead time:

Weights: relative # of manufacturing orders

Safety cards: on queue time Function of manufacturing batch size

kokkkoq

kkk

kK

k

O

okom

kkk

kK

k

O

okom XOQQTQWS

OQQY

DOQ

OQQY

DOQmLT

m

kk**

%*1 1

*1 1

Prof. Dr. Nico Vandaele, University of

Antwerp

Load Based Version of POLCA

Multiply the number of cards by the average workload of the operations planned in the loop during the planning horizon:

lokkommokkolmkol

kkk

kK

k

O

omkol

K

k

O

o

kokkko

kkk

kmkol

OQQY

DOQXOQQT

OQQY

DOQmlWL

kk

)1()1(

*1 11 1

*

*

Prof. Dr. Nico Vandaele, University of

Antwerp

E-POLCA atSpicer Off-Highway Products Division

A few years ago, the company implemented the software i-CLIPS, which computerizes the aggregate planning. Provides authorizations

At each workstation a display will show: list mentioning the authorized production

orders production orders

Green: capacity is available (POLCA card) Red: capacity not available now (no POLCA card)

E stands for paperless environment

Prof. Dr. Nico Vandaele, University of

Antwerp

Machine X Machine Y

P C N P C NMachine Load Machine Load Machine Load Machine Load Machine Load Machine Load

A 5 X 4 Y 5 X 2 Y 6 A 4

B 7 X 2 F 2 X 3 Y 5 E 8

D 6 X 3 Y 1 A 5 Y 4 G 5

A 4 X 6 Y 1 A 8 Y 8 D 2

C 2 X 5 A 2 A 9 Y 5 A 5

C 5 X 4 D 4 X 4 Y 2 B 1

A 5 X 8 Y 5 C 2 Y 5 B 1

E 8 X 5 B 6 X 5 Y 1 D 4

G 4 X 2 B 8 X 1 Y 3 D 8

D 2 X 5 B 5 D 2 Y 5 B 5

A 3 X 1 Y 2 X 2 Y 8 D 2

B 5 X 1 A 3 X 4 Y 9 D 5

B 8 X 2 C 4 X 8 Y 4 E 1

D 9 X 5 Y 2 C 5 Y 2 E 6

D 4 X 5 Y 1 A 2 Y 6 E 5

E 2 X 6 D 5 X 5 Y 5 A 4

E 5 X 4 D 2 X 1 Y 4 C 8

E 1 X 2 Y 4 A 1 Y 8 B 5

A 2 X 1 Y 1 X 2 Y 5 D 2

C 2 X 3 D 1 D 5 Y 2 A 5

LOOP XY 125 Wait Y 89

Open X 36

Prof. Dr. Nico Vandaele, University of

Antwerp

Conclusions

ARP is a generic approach for many planning and execution systems

ARP is based on stochastic modelling of manufacturing systems

Industry is eager to use the models