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.
Railway Transportation Efficiency Improvement: Loco Health Assessment by Time Domain Data Analysis to Support Condition Based Maintenance Implementation
