• Engineering
  • Published 2016

Minimisation of energy consumption variance in manufacturing through production schedule manipulation

@inproceedings{Duerden2016MinimisationOE,
  title={Minimisation of energy consumption variance in manufacturing through production schedule manipulation},
  author={Christopher James Duerden},
  year={2016}
}
In the manufacturing sector, despite the vital role it plays, the consumption of energy is rarely considered as a manufacturing process variable during the scheduling of production jobs. Due to both physical and contractual limits, the local power infrastructure can only deliver a finite amount of electrical energy at any one time. As a consequence of not considering the energy usage during the scheduling process, this limited capacity can be inefficiently utilised or exceeded, potentially… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 84 REFERENCES

myPowerMoitor

  • M.S.
  • [online] NI Community. Available from: https://decibel.ni.com/content /docs/DOC-23214 [cited 15
  • 2012
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

Measuring Reactive Power in Energy Meters

  • E. Moulin
  • Metering International, (1), pp. 52 – 54.
  • 2002
VIEW 1 EXCERPT
HIGHLY INFLUENTIAL

Knowledge extraction from artificial neural network models

  • Zvi Boger, Hugo Guterman
  • Computer Science
  • 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation
  • 1997
VIEW 1 EXCERPT
HIGHLY INFLUENTIAL

Power Factor Correction Device (The Corrector)

VIEW 1 EXCERPT
HIGHLY INFLUENTIAL

Ensemble Learning

  • Gavin Brown
  • Computer Science
  • Encyclopedia of Machine Learning and Data Mining
  • 2017
VIEW 1 EXCERPT