© C.Hicks, University of Newcastle C.F.Earl, Open University IDMME02/1 A Genetic Algorithm Tool for...

© C.Hicks, University of Newcastle C.F.Earl, Open University

IDMME02/1

A Genetic Algorithm Tool for Designing Manufacturing

Facilities in the Capital Goods Industry

Dr Christian Hicks,

University of Newcastle,

England

Email: [email protected]


IDMME02/2

Capital Goods Companies

• Complex products e.g. turbine generators, oilrigs, cranes

• Complex processes including component manufacturing, assembly, construction and commissioning

• Highly customised designs• Very low volume production with highly

variable demand.


IDMME02/3

Capital goods company activities

DEPTH OF PRODUCT STRUCTURE

FLOWDEEPSHALLOW

MA

NU

FAC

TU

RIN

G P

RO

CE

SS

SUBCONTRACT

BATCH

MAIN PRODUCT

SPARES

JOBBING

COMPANY TYPE "A"


IDMME02/4

Types of Facilities Design Problems

• Green field – designer free to select processes, machines, transport, layout, building and infrastructure

• Brown field – existing situation imposes many constraints


IDMME02/5

Facilities Layout Problem

Includes:• Job assignment – selection of

machines for each operation and definition of operation sequences

• Cell formation – assignment of machine tools and product families to cells

• Layout design – geometric design of manufacturing facilities and the location of resources

• Transportation system design

This paper considers cell formation and layout design


IDMME02/6

Cell Formation Methods

• “Eyeballing”

• Coding and classification• Product Flow Analysis• Machine-part incidence matrix

methods– Rank Order Clustering– Close Neighbour Algorithm

• Agglomerative clustering– Various similarity coefficients– Alternative clustering strategies


IDMME02/7

Rank Order Clustering Applied to data Obtained from a capital goods company


IDMME02/8

Similarity Coefficient

1

654

32

S ij = m ax(n ij/n i, n ij/n j)

S2,5 = m ax(2 /3 , 2 /2)

S2,5 = 1


IDMME02/9

Agglomerative clustering using the singlelinkage strategyEquation 1


IDMME02/10

Agglomerative clustering with complete linkage strategy


IDMME02/11

Clustering applied to capital goods companies

Limitations• Few natural machine-part clusters• Long and complex routings mitigate

against self contained cells• Clustering only uses routing

information• Geometric information is not used.


IDMME02/12

Genetic Algorithm Design Tool

Based upon: • Manufacturing System Simulation

Model (Hicks 1998) • GA scheduling tool (Pongcharoen et

al. 2000)


IDMME02/13

Manufacturing Planing &Control System

Manufacturing Facility

Manufacturing System Simulation Model

Planned Schedule

Resourceinformation

CAPM modules used

System parameters

Product information

Operational factors

System dynamics Logic

Measures ofperformance

Flow measurementCluster AnalysisLayout generation methods

Tools


IDMME02/14

GA Procedure

• Use GAs to create sequences of machines

• Apply a placement algorithm to generate layout.

• Measure total direct or rectilinear distance to evaluate the layout.


IDMME02/15

Genetic Algorithm

Similar to Pongcharoen et al except, the repair process is different and it is implemented in Pascal

Start Encode GenesChromosome

Chromosome

Chromosome

Ran

dom

ly c

ombi

ne g

enes

Crossover Function

Parent 1

Parent 2

X

Offspring 1

Offspring 1

Parent 1 Offspring 1

Mutation Function

Genetic Operators

Ran

dom

ly s

elec

t chr

omos

omes

Check and eliiminateduplication

Produce layout usingplacemenrt algorithm with

constraint checking

Evaluate "fitness" in termsof total direct / rectilinear

distance travelled

RouletteWheel

Stop

Terminate ?

Display

Create population forgenerationYes

No


IDMME02/16

Placement Algorithm


IDMME02/17

Case Study

• 52 Machine tools• 3408 complex components• 734 part types• Complex product structures• Total distance travelled

– Direct distance 232Km

– Rectilinear distance 642Km


IDMME02/18

Initial facilities layout


IDMME02/19

Total rectilinear distance travelled vs. generation (green field)


IDMME02/20

Resultant Brown-field layout


IDMME02/21

Total rectilinear distance vs. generation (green field)

Note the rapid convergence with lower totals than for the brown field problem


IDMME02/22

Resultant layout (green field)

Note that brown field constraints, such as wallsHave been ignored. The solution is not realistic because there is insufficient space for materials.


IDMME02/23

Conclusions

• Significant body of research relating to facilities layout, particularly for job and flow shops.

• Much research related to small problems.

• Capital goods companies very complex due to complex routings and subsequent assembly requirements.

• Clustering methods are generally inconclusive when applied to capital goods companies.

• GA tool shows an improvement of 55% in the green field case and 30% in the brown field case.


IDMME02/24

Future Work

• The GA layout generation tool is embedded within a large sophisticated simulation model.

• Dynamic layout evaluation criteria can be used.

• The integration with a GA scheduling tool provides a mechanism for simultaneously “optimising” layout and schedules.

© C.Hicks, University of Newcastle C.F.Earl, Open University IDMME02/1 A Genetic Algorithm Tool for...

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