Predictive maintenance boosts productivity.

An important new growth market is predictive maintenance is being driven by condition monitoring technologies. Specifically, it helps users predict equipment life and plan maintenance for reducing unplanned downtime. Predictive maintenance reduces costs, and boosts productivity through higher machine utilisation.

Condition monitoring detects changes by measuring relevant parameters like motor currents, vibration, temperature etc. Checking these against benchmarked performance highlights anomalies via an HMI or SCADA reporting system.

Data from a wide range of sensors on a machine or production area are input into a controller module. This makes implementation scalable according to budgets and available resources. Moreover, one big benefit is that the new products are suitable for retrofitting on most machines.

One recent case was at Muntons Malt, one of the UK’s largest producers of malted barley for beer, spirits and foodstuffs. Muntons chose Smart Condition Monitoring (SCM) from Mitsubishi Electric to protect vital fan motors in the production process. Production of malted barley is in large batches, where consistent conditions are critical. They had experienced issues with difficult-to-reach bearings inside a large fan housing and wanted to avoid a repeat.

Plant Engineer Michael Plawecki explains, “the malting process developed thousands of years ago. It involves steeping, germination and kilning of barley ears, but the big difference now is the scale of operation. We process many tonnes at a time and the last two processes both rely on a steady supply of blown air. This means the fans and motors that provide the air are critical to our operations.”

“Like many food industries, the principles of the process are quite traditional. We rely a lot of automation, electro-mechanical equipment and sensors to provide fine control over air flow, heat and moisture. Each batch is very valuable, not just in monetary terms but also to the customer. For this reason we are pro-active when it comes to service and maintenance of our equipment.

“However, we were caught-out by a bearing failure inside a fan assembly. We only realised we had problems when it was too late and we had to make an unscheduled stop on one of the lines to make repairs. Determined to learn from that lesson we found what looked like an ideal solution from Mitsubishi Electric.”

Linking predictive maintenance to existing SCADA

“The key for us was to find a predictive maintenance technology onboard for linking to the existing SCADA system. This would provide us with the maximum forewarning of any future issues yet was quick and easy to install.”

The SCM solution provided by Mitsubishi Electric comprises of smart sensors. Attaching them to bearing housings, gearboxes, pumps and motors tells us when equipment starts to operate outside its normal envelope. Furthermore, it provides a sophisticated early warning system for critical pieces of rotating equipment.

Vibration frequencies and temperatures fed to an L-Series Mitsubishi PLC over Industrial Ethernet cables. The sensors from bearing expert FAG can be set-up to recognise tell-tale signs, allowing them to identify complex vibration patterns specific to the connected equipment.

The intelligent software compares the input data with established data models such as from previous installations. This provides an almost fool proof analysis and alert system for the user. Live information and any alarms are displayed on a GOT Series HMI mounted in the control enclosure. It was easy to connect the visual information and alerts with the existing automation SCADA software platform.

The initial system provided condition monitoring for two large 315kW fan sets and a single 90kW fan set. It references the electric motor, power transmission coupling and main fan shaft bearing on each.

Finally, we recognised that the investment in automation and predictive maintenance pays off very quickly. In detail, it avoids unscheduled downtime and increases operational effectiveness and productivity.”

Additionally, material is given in Mitsuibshi’s application datasheet SMART CONDITION MONITORING for Preventive Maintenance.

 

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