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  • By Tony Waller
  • In Blog
  • Posted 29/11/2017 08:59:00

Last month, the University of Greenwich and Ford Motor Company presented their joint WITNESS modelling project on the ‘Optimisation of Compressed Air System’s Energy Usage Through Discrete Event Simulation: Compressor Performance’ at the 31st European Simulation and Modelling conference in Lisbon.

In this excellent presentation, Robbie Mulvany from the University of Greenwich and Michael Higgins from Ford Motor Company, highlighted the high costs of producing compressed air in manufacturing and the capability of simulation modelling to identify waste and savings potential.

The WITNESS model utilised a novel modelling approach to simplify the use of compressed air in a way that leads to efficient modelling; the presented “AirBlocks” methodology significantly reduces the aggregate data required to represent the dynamic and interdependent nature of the compressed air systems. By combining the AirBlocks approach with a manufacturing simulation model, a compressed air demand profile can be developed. This illustrates periods of sustained peak, average and minimum air demand and incidents of production stoppages due to air starvation. This data enables right sizing of compressor facilities and understanding of the effects of different production control.

WITNESS offers many methods to model energy use. The ‘Costing and Sustainability’ dialog allows the definition of any resource and the appropriate units for measurement. Usage can then be overlaid on a process or facility model and a full report is automatically generated. If you would like to see examples of WITNESS being used to model Electricity and Water usage, please contact me at  twaller@lanner.com for more information on these applications.

To read the full conference paper, please click  here.

Paper Authors

•Robbie Mulvany, Dr. Alan Arokiam, Dr. Hafid Belaidi
-University of Greenwich, Faculty of Engineering and Science

•John Ladbrook, Michael Higgins
-Ford Motor Company, Dunton Technical Centre 


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