@article {3149,
	title = { A Temporal Neuro-Fuzzy Monitoring System to Manufacturing Systems, May  ISSN 1694-0814},
	journal = {IJCSI International Journal of Computer Science Issue},
	volume = {Vol. 8},
	number = {Issue 3 N{\textdegree}1},
	year = {2011},
	abstract = {Fault diagnosis and failure prognosis are essential techniques in improving the safety of many manufacturing systems. Therefore, on-line fault detection and isolation is one of the most important tasks in safety-critical and intelligent control systems. Computational intelligence techniques are being investigated as extension of the traditional fault diagnosis methods. This paper discusses the Temporal Neuro-Fuzzy Systems (TNFS) fault diagnosis within an application study of a manufacturing system. The key issues of finding a suitable structure for detecting and isolating ten realistic actuator faults are described. Within this framework, data-processing interactive software of simulation baptized NEFDIAG (NEuro Fuzzy DIAGnosis) version 1.0 is developed.  This software devoted primarily to creation, training and test of a classification Neuro-Fuzzy system of industrial process failures. NEFDIAG can be represented like a special type of fuzzy perceptron, with three layers used to classify patterns and failures. The system selected is the workshop of SCIMAT clinker, cement factory in Algeria},
	url = {https://arxiv.org/ftp/arxiv/papers/1107/1107.3302.pdf},
	author = {Mahdaoui Rafik and Mouss Leila Hayet and Mouss Med Djamel}
}
