A web-based multilevel framework for condition monitoring of industrial equipment
Abstract
Proactive maintenance strategies aim to maintain equipment before failure and, in doing so, avoid expensive repair costs. Condition monitoring provides relevant stakeholders with information on the mechanical health status of equipment. Condition monitoring is therefore a useful tool for assisting with proactive maintenance. Condition monitoring consists of three key steps, namely, data acquisition, data processing, and information transfer and visualisation. Existing literature focuses heavily on data processing techniques, while literature on condition monitoring information transfer and visualisation is limited. The information transfer and visualisation aspect of existing condition monitoring systems focuses mostly on the detailed data of measurements and components. Management level personnel in industrial organisations typically use this condition monitoring information to make resource allocation decisions. These personnel are, however, responsible for numerous operations and manual investigation of each component in these organisations, which creates cognitive overload. This study aims to improve the information transfer and visualisation to relevant stakeholders by reducing the cognitive load and increasing the data accessibility. Thereafter, the study investigates if these improvements can improve proactive maintenance in an industrial organisation by reducing the reaction times to faulty equipment. This study develops a generic, multilevel web-based framework to visualise the processed condition monitoring data of industrial organisations. The multilevel web-based system gives a range of stakeholders remote access to the condition monitoring data to encourage timeous maintenance decisions. The system is generic and usable in numerous industries. The system was implemented across nine operations and five system groups in a mining organisation. The system significantly reduced the cognitive load at management levels, such as the organisational and operational level, while maintaining acceptable levels of cognitive load at detail levels. The system successfully reduced the maintenance reaction times relative to the number of maintenance reactions. As with most practical implementations, there were exceptions: one of the operations showed an increase in relative reaction times. Further investigation indicated that this increase was due to a significant drop in the number of faulty equipment, causing a decreasing denominator. The system is therefore considered a success.
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