Self diagnostics: an enabler for predictive maintenance

15 May 2017

Control Engineering Europe reports on the use of level measurement devices which are able to monitor build up and automatically alert maintenance personnel when cleaning is required.

Imagine a production process where devices can diagnose themselves: They would know when something is wrong and send an alarm. If, for example, excessive build-up occurred in a silo or tank measurement sensors would be able to signal the need to clean a process. 

The Kanmantoo Copper Mine in Australia has already started to experience the advantages of self-diagnostics following its trial of smart sensing solutions. The company had two clear objectives for which it required a smarter level measurement solution – to increase production by being able to fill its ROM bins as close to capacity as is safely possible and to reduce maintenance costs. 

The company wanted to use the maximum fill heights of a ROM bin used to store unprocessed copper ore. To accommodate this increase in fill heights, the existing radar level sensor needed to be relocated to a new position, where it would unavoidably get covered in dirt. This posed a problem because it meant that the strength of the measuring signal emitted and received by radar level transmitters – a critical factor for precise measurements – would diminish. Under these conditions conventional radar and ultrasonic level transmitters would need to be regularly cleaned, sometimes as often as every hour. This would be time-consuming for the maintenance personnel and the ROM bin would be stopped, which would lead to costly downtime. 

Avoiding mechanical changes
The copper mine also wanted to avoid expensive mechanical changes so made the decision to trial the Endress+Hauser Micropilot FMR57 radar level transmitter with Heartbeat Technology. This function monitors the extent of dirt build-up, and reports it back to the control room to alert the personnel of the need to clean the transmitter. The FMR57 also features a PTFE horn protector that helps reduce the rate of build-up. This means cleaning is required less frequently. 

Self-diagnostics has been standard in a variety of Endress+Hauser flow devices since 2012 and its portfolio recently been expanded to include level devices. Instruments incorporating its Heartbeat Technology are able to offer permanent process diagnostics and in-situ diagnostic functions. The Micropilot FMR5x radar level transmitter is made for continuous, non-contact level measurement in powdery to granular bulk solids. Dust, filling noises, temperature layers and gas layers do not affect measurement. For challenging bulk solids measurement applications, for example, extremely narrow or multi-chamber silos, the transmitter is offered with a 3.5° microwave beam angle, which enables measurement to the bottom of the silos. 

Endress + Hauser’s Heartbeat Technology tracks the performance of a device to ensure it is not adversely affected by abrasion, corrosion or sticky build-up. Standardised and clear diagnostic messages are sent regarding what needs to be done in order to maintain the plant economically and as a matter of priority. As the devices run their own diagnostics, proof tests are only necessary in maximum extended cycles. Furthermore, the automatically generated protocols provided by Heartbeat Technology without process interruption support documentation relating to international standards. For future-orientated predictive maintenance the instruments offer parameters to monitor the performance for process optimisation.

Self diagnostics
Instruments which incorporate self-diagnostics allow plants to run more cost-effectively and safely with no interruptions. A simple, predefined procedure will guide the maintenance team through the verification procedure and, at the end, the verification results are documented. The SIL test, according to the safety manual and documentation, saves time and reduces costs and an automatically generated verification protocol supports the evidence demanded by regulations, laws or plant standards. 

The data acquired through self-diagnostics facilitates trend recognition for the implementation of predictive maintenance programmes. A combination of instrument and process parameters provides the information needed to undertake the next steps in maintenance, or for targeted process optimisation. 

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