You may not realize it, but your interactions on the internet are being leveraged as the information sources used to make decisions in a variety of very clever software-based systems. Leading tech firms – such as Google and Netflix – regularly leverage user-specific search and activity data to feed algorithms that ultimately streamline and enhance customer deliverables. The result being that you gain an online experience customized to your tastes.
Interestingly, if we replace ‘user-specific data’ with ‘machine/process-specific data’ it quickly becomes clear that the same Big Data approach – coupled to machine learning – has the potential to revolutionize industry. The problem is that even simple manufacturing cells can generate huge amounts of data. So how do you make sense of it all and – more importantly – then use it to your advantage?
This is where AI and machine learning will step in. By distinguishing relevant data from noise, defining logical connections and correlations and removing any non-connectable data, AI can quickly provide pertinent information upon which decisions can be made. Feed it even more historical data and it will make even better decisions.
This isn’t a pipe dream either. AI and machine learning can be catered for, now, by any company running any solution. Indeed, adding data-gathering capabilities to even the ‘dumbest’ manufacturing operation is relatively straightforward and can be achieved with a very palatable financial outlay. In the very near future this data will (more than likely) be fed to subscription-based services that will securely collect, collate, translate and deploy solutions and answers that will not only allow users to make better decisions, but will also create the next industrial paradigm.
Luckily Big Data does not need big pockets. At RS Components, we already have many initiatives in place to both cater for the demands and exploit the benefits of the Big Data-driven manufacturing economy. Even the most basic manufacturing data – especially when leveraged intelligently – can make a huge difference and the path to adoption is already wide open and incredibly well supported for applications of any size, and at a sensible budget.
Editor's note: This is a sponsored blog post from RS Components.
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