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Nowadays, managers try to use scientific methods to increase the quality of goods, and simultaneously reduce their final prices as well. Condition Monitoring (CM) is one of the methods which has been popular among industrial managers in recent years and of course it has provided many benefits for organizations. Analyzing the vibrations is one of the condition monitoring methods, and by using it we can avoid rework, and reduce the company's costs considerably. To show this effect for efficiency improvement of production process, Mazandaran Wood and Paper Industries has been selected as a case study, and the vibration analysis, one method of the conditions monitoring has been applied. In this research, we have shown how to prevent stoppages and damages of the equipment by in-time awareness and by imposing preventive repairs. Secondly, considerable conservation in consumption of parts and manpower will be achieved for repairing and maintenance of equipment in order to guide the organization toward efficiency improvement.

In order to diagnose the faults of industrial rotating machines automatically, an expert system is used in this paper. A tri-lobe roots blower compressor is used as a test rig to represent an industrial machine. The proposed method for training the expert system includes: data acquisition, signal processing and intelligent pattern recognition stages. Acceleration signals of healthy and faulty compressor components were acquired in the first stage. The signals were conditioned to be used for the signal processing as the next stage. It is necessary to find pattern recognition criterion of the compressor fault diagnosis. Therefore feature extraction of data was performed as part of the second stage. In the third stage, a support vector machine tool was trained and employed to classify the faults. The proposed procedure was tested and the obtained results showed that this algorithm works very well and it fully classifies the faults automatically. [ABSTRACT FROM AUTHOR]

In this paper predictive-based maintenance and condition-based maintenance have been studied for water pump stations. Measurements of vibrations in suitable places, analysis of the vibration trend and spectrums have been dealt with in details. Using the trend of vibrations, existence of a fault in machinery can be detected. The vibration spectrums can also be used in fault diagnosis. Furthermore, in this paper the practical results of using a condition-based monitoring system in one of Tehran’s water pump stations has been presented. Using this method, the existing faults have been detected before the critical situations and the proper repair has been done on the machinery. Using vibration signals for condition monitoring and fault diagnosis started for the first time at Tehran Water and Wastewater Company. Promising results of this method can be used for other water and wastewater companies.