A TOOL FOR OPTIMISING FACILITIES DESIGN FOR CAPITAL GOODS COMPANIES

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A TOOL FOR OPTIMISING FACILITIES DESIGN FOR
CAPITAL GOODS COMPANIES

• Christian Hicks
• Email Chris.Hicks_at_ncl.ac.uk
• University of Newcastle,
• England.

http//www.staff.ncl.ac.uk/chris.hicks/presentatio
ns/presin.htm
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Capital Goods Companies

• Products and processes usually complex.
• Typical products include steam turbines for power
  generation, oil rigs and bespoke cranes.
• Production facilities include jobbing, batch,
  flow and assembly systems.
• Customised to meet individual customer
  requirements.
• Engineered-to-order.
• Low volume, lumpy, erratic demand.

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Facilities Design Problems

• Block plans show the relative positioning of
  resources.
• Plans may be evaluated in terms of static
  measures e.g. total distance travelled by
  components.
• Problems may be classified as
• Green field designer free to select processes,
  machines, transport, layout, building and
  infrastructure
• Brown field existing situation imposes many
  constraints.

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Genetic Algorithm Tool

• Based upon an analogy with biological evolution
  in which the fitness of an individual determines
  its ability to survive and reproduce.
• Uses GAs to create sequences of machines or
  chromosomes.
• Applies a placement algorithm to generate
  layouts.
• Evaluates layouts in terms of total direct or
  rectilinear distance to determine fitness.
• The probability of survival of a chromosome to
  the next generation is a function of its fitness

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Genetic Algorithm Procedure
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Placement Algorithm
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Case Study

• Heavy engineering job shop.
• 52 Machine tools.
• 3408 complex components.
• 734 part types.
• Complex product structures.
• Total distance travelled
• Direct distance 232Km
• Rectilinear distance 642Km.

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Initial facilities layout
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Total rectilinear distance travelled vs.
generation (brown field)
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Resultant brown-field layout
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Total rectilinear distance travelled vs.
generation (green field)
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Resultant green field layout
Note that brown field constraints, such as
walls have been ignored.
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Conclusions

• Significant body of research relating to
  facilities layout, particularly for job and flow
  shops, but much of the research is related to
  small problems.
• Capital goods companies utilise flow, cellular,
  jobbing and assembly systems.
• Job shops incorporate most capital intensive
  plant and produce the highest value, longest
  lead-time items.
• GA tool generated layout reduces total
  rectilinear distance travelled by 25 for the
  brown field case.

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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 with respect to
  static and dynamic performance criteria.

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