Is a condition-based maintenance technique used in rotary and alternative machinery. The commonly used diagnostic techniques are measurement of total vibration in a broad or narrow frequency band, spike energy, envelopment or peakvue analysis, analysis of kurtosis or skewness, harmonic analysis, peak vibration synchronicity measurements, etc. This can detect disequilibrium, excessive clearance, problems with bearings and gears, electrical faults, etc. and is the most widely used predictive technique.
Published in Chapter:
Decision Making in the Choice of Condition-Based Maintenance Techniques in a Subsidiary of a Petrochemical Company
María Carmen Carnero-Moya (University of Castilla-La Mancha, Spain & Universidade de Lisboa, Portugal) and Francisco Javier Cárcel-Carrasco (Universitat Politècnica de València, Spain)
Copyright: © 2019
|Pages: 20
DOI: 10.4018/978-1-5225-7152-0.ch017
Abstract
Condition-based maintenance (CBM) may be considered an essential part of the Industry 4.0 environment because it can improve production processes through the use of the latest digital technologies, which allows improvements to products, processes, and business models. Nonetheless, despite this importance, there are no models or methodologies in the literature to assist in choosing predictive techniques and the level of complexity to be used in a given organization. This chapter describes a model for choosing the most suitable CBM technique to be introduced in a subsidiary of a petrochemical plant. The predictive techniques of vibration analysis, lubricant analysis, and a combination of the two were considered at three technological levels. The model was built using the measuring attractiveness by a categorical based evaluation technique (MACBETH) approach. The present model could avoid failures in these programmes when making decisions about the techniques and technologies most suited to the characteristics of the industrial plant.