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© C.Hicks, University of Newcastle HIC288/1 A TOOL FOR OPTIMISING FACILITIES DESIGN FOR CAPITAL GOODS COMPANIES Christian Hicks

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Presentation on theme: "© C.Hicks, University of Newcastle HIC288/1 A TOOL FOR OPTIMISING FACILITIES DESIGN FOR CAPITAL GOODS COMPANIES Christian Hicks"— Presentation transcript:

1 © C.Hicks, University of Newcastle HIC288/1 A TOOL FOR OPTIMISING FACILITIES DESIGN FOR CAPITAL GOODS COMPANIES Christian Hicks Email: Chris.Hicks@ncl.ac.ukChris.Hicks@ncl.ac.uk University of Newcastle, England. http://www.staff.ncl.ac.uk/chris.hicks/presentations/presin.htm

2 © C.Hicks, University of Newcastle HIC288/2 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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4 © C.Hicks, University of Newcastle HIC288/4

5 © C.Hicks, University of Newcastle HIC288/5 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.

6 © C.Hicks, University of Newcastle HIC288/6 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’

7 Genetic Algorithm Procedure

8 © C.Hicks, University of Newcastle HIC288/8 Placement Algorithm

9 © C.Hicks, University of Newcastle HIC288/9 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.

10 © C.Hicks, University of Newcastle HIC288/10 Initial facilities layout

11 © C.Hicks, University of Newcastle HIC288/11 Total rectilinear distance travelled vs. generation (brown field)

12 © C.Hicks, University of Newcastle HIC288/12 Resultant brown-field layout

13 © C.Hicks, University of Newcastle HIC288/13 Total rectilinear distance travelled vs. generation (green field)

14 © C.Hicks, University of Newcastle HIC288/14 Resultant green field layout Note that brown field constraints, such as walls have been ignored.

15 © C.Hicks, University of Newcastle HIC288/15 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.

16 © C.Hicks, University of Newcastle HIC288/16 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.

17 © C.Hicks, University of Newcastle HIC288/17


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