Overall Equipment Effectiveness and Overall Line Efficiency Measurement using Fuzzy Inference Systems

Hasan Moradizadeh, Rene V. Mayorga

2014

Abstract

Increasingly, Intelligent Systems (IS) techniques are being used to solve both complex problems and industrial problems with uncertainty. They also can implement the operator’s knowledge (experience) into the system. This Paper aims to improve and compute the well-known manufacturing metrics: the Overall Equipment Effectiveness (OEE), and Overall Line Efficiency (OLE), using IS techniques. The proposed methodologies to improve the OEE and OLE weakness are based on Fuzzy Inference Systems. These techniques result in an effective way to measure OEE and OLE considering different weight of losses and also the difference in machine’s weight factors. Moreover, they allow the operator’s knowledge to be taken into account in the measurement using uncertain input and output with implementation of linguistic terms.

References

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Paper Citation


in Harvard Style

Moradizadeh H. and Mayorga R. (2014). Overall Equipment Effectiveness and Overall Line Efficiency Measurement using Fuzzy Inference Systems . In Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014) ISBN 978-989-758-053-6, pages 199-204. DOI: 10.5220/0005155101990204


in Bibtex Style

@conference{fcta14,
author={Hasan Moradizadeh and Rene V. Mayorga},
title={Overall Equipment Effectiveness and Overall Line Efficiency Measurement using Fuzzy Inference Systems},
booktitle={Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)},
year={2014},
pages={199-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005155101990204},
isbn={978-989-758-053-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)
TI - Overall Equipment Effectiveness and Overall Line Efficiency Measurement using Fuzzy Inference Systems
SN - 978-989-758-053-6
AU - Moradizadeh H.
AU - Mayorga R.
PY - 2014
SP - 199
EP - 204
DO - 10.5220/0005155101990204