Published on December 4th, 2019 | by Emergent Enterprise1
What Is a Smart Factory?
This post from Megan Nichols at iotforall.com is an excellent introduction to the Industrial Internet of Things (IIoT). Present day IIoT gives us an idea of what the factories of the future will look like. The production will be quick, efficient, nearly error-free and run 24/7. There will be little human involvement as factories fueled by data and artificial intelligence will take on the mundane, repetitive tasks of manufacturing. These tasks are also often very complex and even dangerous. The workers that are replaced by IIoT can then move on to careers that are more fulfilling and meaningful.
Illustration: © IoT For All
Next-generation smart factories will use what’s known as a cyber-physical system to collect and analyze data to carry out tasks more efficiently and create better products.
Our phones, cars and water have all gotten smart, so it was only a matter of time before industry did, too. You’ve probably heard the term smart factory, or maybe you’ve heard about the industrial internet of things (IIoT). It’s simple to deduce that these next-generation factories introduce new technologies to do things even better. So, how exactly do they do it?
A combination of interconnectivity and tools known as a cyber-physical system (CPS) is what makes a smart factory “smart”. They allow tasks to be carried out more efficiently by collecting and analyzing data. That information can then be used to create better products and more efficient techniques, sometimes by the factory itself.
Hungry for Data
The first step in making a factory smart is to centralize your data. Any successful business should be run with a keen eye on the numbers. In a smart factory, the proper systems are in place to collect and centralize those numbers. In most cases, this is a network of wireless IIoT sensors and devices that are constantly collecting and storing vast amounts of data. This data could be anything from the timing of specific robots to environmental conditions throughout the factory.
Without a good set of aggregated data and the right tools to maintain it, you cannot have a smart factory. Having the data, however, is just the most basic component of a smart factory.
In fact, the smart factory model categorizes available data as level one of four. In this level, data is being captured but in a way that makes it difficult to analyze holistically. Individual processes or systems hold on to the data they collect, and you can’t really get a birds-eye view of factory processes — even if you go to the trouble of collating all the data that’s available.
Level two is accessible data, which means that the data has been pulled out of the silos or disparate corners of the company. The data goes into a central reporting structure of some kind, which employees can then use to make informed decisions. At this point, the kind of data being collected may be standardized so that it’s easier to analyze.
Making Informed Decisions
Having lots of data isn’t enough, though. You need to know what to do with it. This is where the smart factory model begins to shine. As more data is aggregated, it becomes possible to create models of processes and subprocesses that inform the factories’ overall missions. Network-aware CPSes communicate what they’re doing and the outcomes of their tasks via the Internet of Things (IoT). As a result, the factory itself becomes aware of its own successes and failures, which are defined by people in administrative roles using key performance indicators (KPIs).
In level three of the four-level smart factory model, the smart factory manager has implemented advanced data analytics technology powered by artificial intelligence (AI) and big data analysis. These technologies can sift through huge amounts of data — more than even a team of human statisticians could reasonably analyze — and detect patterns and create predictive models.
Factory managers and line employees can then use these insights to improve factory processes or make more informed decisions.