The adage “What gets measured gets managed” is an old one, and we’ve all heard it many times. A director of mine in a previous job had his own unique spin on it: “What gets measured gets managed gets improved.”
That last bit about improvement is of the utmost importance in today's environment. But, so many times, we often follow just the first two points, or only the first.
Here’s how this happens: Many facilities capture every bit of data they can. Then, when management evaluates the data, they can’t see the forest for the trees. The huge amount of data gathered makes it impossible to run any analyses, leaving us stuck with just the first part—getting measured.
To address this, businesses have begun using artificial intelligence (AI) in the form of IBM’s Watson, SAP HANA and others. These technologies have proven to be valuable tools, but the resources typically involved in integrating them into existing installations can be cost-prohibitive.
That is, until now.
With the growth of devices enabled by the Industrial Internet of Things (IIoT), the integration of AI tools is getting easier, giving more companies access to these analytical tools. This means that, instead of people sitting in a conference room poring over data, the data can be published directly to business intelligence tools that deliver real-time analytics to help improve processes. We can now actually manage the processed data and develop ways to improve.
A capable IIoT edge device
So, just what are these IIoT devices I’m referring to, and how do they make integration easier? Take a look at what can be accomplished in an existing site by using Opto 22’sgroovEPIC (Edge Programmable Industrial Controller). Using MQTT/Sparkplug to efficiently publish and subscribe to data points,groovEPIC has the ability to directly publish data to cloud resources that can interpret data for you and give you that push toward actual improvement. In this way, data also becomes available to manufacturing execution system (MES), enterprise resource planning (ERP) and supervisory control and data acquisition (SCADA) solutions so that everyone within the plant—from the operators to the C-suite—can access pertinent information for decision-making. All of this is made possible by one piece of hardware and some very easy-to-implement programming features.
Using these features, you can introduce the goals of Industry 4.0 to create your own smart factory via four key aspects:
- Interoperability—the communication between machines, devices and people using IIoT. This is the first step to creating a smarter factory.
- Transparency—in this context, it is the use of data across different machines and processes within the factory, and then gathering that data for processing and interpretation. In other words, this is the transportation of data to management, engineering or business intelligence systems.
- Technical assistance—the ability to move from reactive or preventive maintenance on machines to a predictive style, allowing operators to have knowledge of likely issues and mean time between failure (MTBF) data.
- Decentralized decision-making—using business intelligence to allow machines and people to perform tasks for the factory at a semi-autonomous level.
Of course, with any new technology or industry focus, there will undoubtedly be some resistance to it amid a preference for familiar, traditional automation systems. But I look at automobile safety as a great example of how new technologies have been of considerable benefit. After all, automobiles went from no restraints to seat belts to airbags to auto-stopping—all with the help of technology.
As Maya Angelou said, “Do the best you can until you know better. Then when you know better, do better.” We are at the point of knowing better; it is time to start doing better to get more out of our automation.
Using these ideas—and leveraging the power of thegroovEPIC system—will give factories the ability to go beyond measuring and managing and to start improving.