Collaborating on real-time data

In a recent article by my USA colleague Wolfgang Kratzenberg, titled ‘Be Driven by Data and Decrease Downtime’¹, the point was made that making decisions based on real data rather than guessing or relying on theoretical values is an obvious step to improving quality and efficiencies in manufacturing.

This got me thinking about how we can work together to empower manufacturers with relevant real-time data. Sometimes the most obvious statements like “be driven by (real) data” are the hardest to put into practice and I think that this is often due to a combination of factors. These include knowledge about the technology to be implemented, the will to disrupt a settled process in order to increase efficiency or quality, and of course an understanding of ROI. In almost every case a manufacturer is the expert on his product and process but often may not have an in-depth knowledge of subsystems or machine parts used within the process.

Simply put, to make an informed decision we need to generate data about a specific part of the process and then make this available to a controller or some sort of intelligence, which can then analyse the data and provide the feedback needed. This is how we enable good decision-making around our operations. On the implementation side of these decisions, the decision could be fully automated or made by an operator or manager in real time, having been presented with the data in a meaningful context and representation. It is not necessarily about reviewing historical data through spreadsheets and databases, although this of course has a very valuable place.

The example used in Kratzenberg’s article was based around condition monitoring sensors that can generate data about temperature, vibration, humidity, ambient pressure etc to provide an indication at the earliest possible stage that something is changing within the process and that an informed decision must be made. My own company, Balluff, is expert in data generation via sensors and presenting this data to the controller. This, however, can only ever be a part of the solution: the plethora of information available from a condition-monitoring sensor is most valuable when the data is selected to be relevant to the process — for example, a vibration velocity (RMS), acceleration (RMS) or vibration peak-to-peak value, which are all available from the sensor, can indicate different issues for different components. For this we need an expert to help interpret the data. For example, this could be an expert on the particular component technology such as pneumatics, gearboxes or fans — they have an understanding of what the outcome and cost implication would be if this data is not acted upon. We also need to establish a clear path on how best to process and present this data to an operator or to automatically feed back into the process, in order to make an informed change. The end user is the expert for the overall process but other stakeholders can make a valuable contribution.

In my opinion it is desirable to actively seek out partnerships and work together within industry (and academia) to ensure that the whole is greater than the sum of the parts. There is always ground for cooperation and to pool knowledge to achieve the best outcome. You don’t have to be an expert on everything — just on your part of the process!

Jim Wallace is Sales Manager for Balluff Australia & New Zealand. He is also an active member of the Open IIOT Group, which is a collaboration between Balluff, SMC Corporation, ZI-Argus, NORD Drivesystems and Beckhoff Automation, aimed at furthering the implementation of Industry 4.0.

Reference

1. Kratzenberg W 2020, 'Be Driven by Data and Decrease Downtime', Automation Insights,<<https://automation-insights.blog/2020/12/02/be-driven-by-data-and-decrease-downtime/>>

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