|Collapsing architecture is impacting|
industrial control systems
Collapsing architecture in an automation environment is a fairly new term that refers to the changing way in which systems in a factory communicate with one another. Systems in a plant are segregated into layers - from hardware level on the plant floor through to enterprise resource planning (ERP) computer networks in the office.
Traditionally, each layer of the factory worked on different networks; information from the factory floor was kept away from the office network and vice-versa. This was partly due to security and partly because raw data from sensors and actuators wasn't thought to be particularly valuable to the overall process.
However, in the modern age of manufacturing where margins are tight and everybody is looking for an edge, data can be collated and analysed to better understand factory processes and maximise efficiency.
With a new emphasis on quality and quantity of data, all layers of the factory are starting to communicate with one another. This means traditional network architecture in factories is starting to collapse, giving way to a new overarching, more fluid transfer of information. Industry calls this new level of interconnectedness the Internet of Things (IoT).
Whereas before, PCs on the corporate network couldn't access raw data from SCADA or hardware level, now information can be retrieved through secure access to different network cells. There is a definite trend, not just for more data, but for more intelligence and this is spreading beyond the factory floor.
Infrastructure is no longer publically owned. Like electricity and gas before it, water supply has become commercialised and understandably, there is now more pressure to turn a profit.
With this in mind, the factory model of collapsing architecture is starting to be seen in utilities. Competition is driving companies to look at their systems and ask how they can make them more intelligent.
The more data collected in infrastructure cells like pumping stations, the more likely it is to identify useful information. All this data can be collated and analysed to offer better insight and make more informed decisions that result in more profitable outcomes.
For example, let's say a supervisor at a pumping station turns on a pump to fill a reservoir upon arriving to work in the morning. The reservoir fills and the supervisor turns the pump off, job done. However, if you collect data at each step of this short process, certain questions arise.
Is this a peak time of day when the electricity needed to power the pump is more expensive? Can the reservoir wait to be filled during off-peak time? Does the reservoir need to be completely full or is it more efficient to only fill it to 75 per cent capacity? All this information can be processed to form more efficient results.
The IoT has brought about the collapsing architecture model with a view to improving efficiency by making better, more informed decisions. The end goal is to equip industrial computers and control systems with decision-making abilities. This allows the supervisor to concentrate on tasks that require more skill that intelligent automation can't muster...yet.