Data acquisition
HOW DATA CAN IMPROVE MAINTENANCE ENGINEERING
Across process applications, maintenance teams are in a constant battle to maintain operational productivity and minimise downtime. Although maintenance team resources are often stretched, implementing data-driven diagnostics can enhance their capabilities. This approach can minimise the potential of maintenance challenges developing long-term, as well as increasing the speed of response to emergency situations. The good news is that the required hardware might already be installed as an existing feature of process control. Even if not, integrating the right technology could be easy to set-up, and provide a fast return on investment. Bürkert industry manager, Greg Wainhouse, explains how to achieve an effective, data-driven diagnostic maintenance system.
oday, there is an availability of data throughout industrial processes like never before. Whether it is the water treatment sector, food and beverage production, or pharmaceutical manufacture, data is everywhere. The significant advantage for maintenance engineering teams is the improvement to diagnostics it can help to achieve. Data analysis can give an awareness that enhances preventative maintenance, minimising the prospect of unexpected downtime. In the event of maintenance emergencies, data can also enable a faster, more effective response. The crucial advantage of automated control is that data, whether emerging from a component such as a valve or a sensor, can be collected, in real-time, in a continuous stream. As a result, this data can be analysed to provide reports, giving intelligence over time to enable effective diagnostics, as well as automated alerts. However, this data omnipresence can be overwhelming. For a data-driven approach to help achieve effective diagnostics, maintenance teams need a clear plan of what data they need, and how they are going to collate and analyse it. While establishing this initial process management stage
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takes time initially, embracing data availability can reduce the time, cost, and efficiency of maintenance engineering in the long run.
WHAT TO DO WITH THE DATA? A common challenge is an awareness of what to do with the available data, and the benefits that effectively managing it can bring. A workable approach to identify where to collate data from, is to prioritise the equipment, as well as their constituent components, in an operations-critical order. This inventory will span a time period of urgency, from issues that would demand emergency attention, to challenges that could signal a longer-term problem. Crucially, this
approach will also identify the condition indicators from which data needs to be collated and managed to achieve effective diagnostics. Starting with emergency maintenance, data- driven alerts from automated systems achieve significantly faster diagnostics to enable a rapid response. Taking pH level monitoring as an example, an important parameter across diverse processes, if a digital sensor returns an abnormal reading, real-time data can quickly confirm device health status and the validity of its reading.
As a result, the maintenance engineer can instantly realise if the fault lies with the sensor, or make a fast progression with the diagnostic procedure. Additional digital alarms may have triggered in parallel, but even if not, sensors from upstream devices, such as dosing pumps or control valves, can be compared to diagnose the issue, all from a remote setting.
EFFECTIVE PREVENTATIVE MAINTENANCE For urgent maintenance requirements, a data- driven system can also provide an operational comparison over time, giving greater context to help understand the actual source of the fault, supporting a faster response. However,
September 2024 Instrumentation Monthly
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