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PdM

PdM (predictive maintenance) is a type of equipment maintenance based on diagnosing and monitoring its condition.

A modern approach to equipment maintenance is based on the RCM methodology, according to which the goal of maintenance is not to maintain each piece of equipment in perfect condition (which requires unreasonably high costs), but to ensure the reliability of production and technological processes that are critical for the enterprise’s activities. In this case, traditional services can be used for non-critical equipment:

• Reactive – mean time between failures without maintenance; it is used when the equipment is easily replaced or repaired without damage to the activities of the enterprise.
• Preventive – it is similar to the system of scheduled preventive maintenance (SPM) and is used for equipment; the cost of downtime is low, and repair does not take much time.

Predictive maintenance is used in cases when the degree of use of equipment in the production chain is assessed as high, and its failure or long-term downtime leads to substantial financial losses.

Predictive maintenance, as opposed to preventive, allows repairing not according to a predetermined plan, but when it is necessary. Due to this, it is possible, on the one hand, not to spend money and time for routine maintenance of equipment, which can normally work for several months without repair. On the other hand, the probability of unplanned downtime caused by an unexpected breakdown is reduced.

This is achieved by:

• collection of data on the technical condition of the equipment and their preliminary processing
• early fault detection
• predicting the time of failure
• service planning
• optimization of resources allocated to equipment maintenance

As the industrial Internet of Things (IIoT) develops, in particular, by equipping equipment with various sensors, it will not be possible to perform data collection on its technical condition periodically, but continuously, without stopping the operation of equipment. The timely detection of even small deviations of the working parameters will allow taking prompt measures to ensure the normal operation of the equipment. Big Data technologies will allow predicting the time of failure with high accuracy.

The main advantages of the PdM system:

• effectiveness of service planning
• prevention of unforeseen failures

With information on what equipment needs maintenance, relevant works can be planned for the period when they will be most cost-effective. In this way, unplanned downtime is converted to shorter planned one and equipment availability time is increased.

Other potential benefits of PdM:

• increasing the service life of equipment
• increasing production safety
• reducing the number of accidents with negative environmental impact
• formation of an optimal set of spare parts and materials

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