A Genetic Algorithm Tool for Designing Manufacturing Facilities

Types of Facilities Design Problems • Green field – designer free to select processes,

Facilities Layout Problem Includes: • Job assignment – selection of machines for each operation

Cell Formation Methods • “Eyeballing” • Coding and classification • Product Flow Analysis •

Rank Order Clustering Applied to data Obtained from a capital goods company IGLS 02/5

Similarity Coefficient IGLS 02/6 © C. Hicks, University of Newcastle

Agglomerative clustering using the single linkage strategy. Equation 1 IGLS 02/7 © C. Hicks,

Agglomerative clustering with complete linkage strategy IGLS 02/8 © C. Hicks, University of Newcastle

Clustering applied to capital goods companies Limitations • Few natural machine-part clusters • Long

Genetic Algorithm Design Tool Based upon: • Manufacturing System Simulation Model (Hicks 1998) •

IGLS 02/11 © C. Hicks, University of Newcastle

GA Procedure • Use GAs to create sequences of machines • Apply a placement

Genetic Algorithm Similar to Pongcharoen et al except, the repair process is different and

Placement Algorithm IGLS 02/14 © C. Hicks, University of Newcastle

Case Study • • • 52 Machine tools 3408 complex components 734 part types

Initial facilities layout IGLS 02/16 © C. Hicks, University of Newcastle

Total rectilinear distance travelled vs. generation (brown field) IGLS 02/17 © C. Hicks, University

Resultant Brown-field layout IGLS 02/18 © C. Hicks, University of Newcastle

Total rectilinear distance vs. generation (green field) Note the rapid convergence with lower totals

Resultant layout (green field) Note that brown field constraints, such as walls Have been

Conclusions • Significant body of research relating to facilities layout, particularly for job and

Future Work • The GA layout generation tool is embedded within a large sophisticated

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A Genetic Algorithm Tool for Designing Manufacturing Facilities in the Capital Goods Industry Dr Christian Hicks, University of Newcastle, England Email: Chris. Hicks@ncl. ac. uk IGLS 02/1 © C. Hicks, University of Newcastle

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 IGLS 02/2 © C. Hicks, University of Newcastle

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 IGLS 02/3 © C. Hicks, University of Newcastle

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 IGLS 02/4 © C. Hicks, University of Newcastle

Rank Order Clustering Applied to data Obtained from a capital goods company IGLS 02/5 © C. Hicks, University of Newcastle

Similarity Coefficient IGLS 02/6 © C. Hicks, University of Newcastle

Agglomerative clustering using the single linkage strategy. Equation 1 IGLS 02/7 © C. Hicks, University of Newcastle

Agglomerative clustering with complete linkage strategy IGLS 02/8 © C. Hicks, University of Newcastle

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. IGLS 02/9 © C. Hicks, University of Newcastle

Genetic Algorithm Design Tool Based upon: • Manufacturing System Simulation Model (Hicks 1998) • GA scheduling tool (Pongcharoen et al. 2000) IGLS 02/10 © C. Hicks, University of Newcastle

IGLS 02/11 © C. Hicks, University of Newcastle

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. IGLS 02/12 © C. Hicks, University of Newcastle

Genetic Algorithm Similar to Pongcharoen et al except, the repair process is different and it is implemented in Pascal IGLS 02/13 © C. Hicks, University of Newcastle

Case Study • • • 52 Machine tools 3408 complex components 734 part types Complex product structures Total distance travelled – Direct distance 232 Km – Rectilinear distance 642 Km IGLS 02/15 © C. Hicks, University of Newcastle

Total rectilinear distance vs. generation (green field) Note the rapid convergence with lower totals than for the brown field problem IGLS 02/19 © C. Hicks, University of Newcastle

Resultant layout (green field) Note that brown field constraints, such as walls Have been ignored. IGLS 02/20 © C. Hicks, University of Newcastle

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 70% in the green field case and 30% in the brown field case. IGLS 02/21 © C. Hicks, University of Newcastle

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. IGLS 02/22 © C. Hicks, University of Newcastle