by Alicia Bowers, Product Manager, Automation Software, GE Digital
The Industrial Internet of Things will improve the end user experience and create new OEM revenue streams.
Thought leaders around the world say the most valued companies will be those that blend digital capabilities and industrial assets. Digital capabilities are required to drive productivity and efficiency to new levels across an organization or environment.
Through the IIoT, automation apps will guide predictive maintenance so equipment never goes offline. And equipment and systems will seamlessly adjust to market demands.
There will be a “digital twin,” a digital model, or twin, of every machine – from a jet engine to a locomotive. Data from these digital twins can be analyzed to help create and grow new business and service models.
In addition, this digital industrial era will bring OEMs and customers closer together. OEMs will use data and analytics across the complete product life cycle. Such a digital thread will enable better initial design, smoother operation, and efficient maintenance in a closed loop.
Filtering and serving information
Today, fourth-generation automation software is helping proactive OEMs make use of the Industrial Internet. Real-time data and advanced analytics algorithms are helping them take advantage of new business opportunities.
Prior to the IIoT, machine data pretty much just went to a screen for an operator to take an action. The operator might see a list of alarms, for example, and react to them. The goal now is to shift from this kind of reactionary response and move to predictive responses. The result will be better machine performance, less equipment downtime and fewer inefficiencies.
Innovative software apps and mobile technologies help OEMs drive real-time operational intelligence where the right operator can receive the right information at the right time and place. It sounds idealistic – yet, it is happening with today’s mobile devices and software apps. The same way these devices and apps have changed our personal lives, they will interact with the IIoT and change our industrial world.
Technology allows us to be smarter about how we filter and serve information. Data can be driven to the device and to the appropriate operator. In some cases, this data could consist of the display tags associated with a particular piece of equipment, or an electric power demand or temperature.
OEMs can create new revenue streams with this real-time end-user data. As an example, a refrigeration OEM offers new services to improve customer experience. In this OEM’s industry uptime can be critical.
Recently, this international OEM turned to GE automation apps to reduce its high warranty costs and provide a way to warn customers of predictable failure. The new system runs diagnostics against real-time performance data from its machines installed at remote end user facilities.
With predictive capabilities, the OEM can respond quickly and send parts, as well as provide timely, critical remote support. These actions cut the costs associated with on-site engineering visits. Asset availability has improved along with end user uptime. In addition to 24/7 monitoring and predicting failures, the GE software provides insight into how to improve system performance – which this OEM has turned into a new revenue stream. Armed with real-time process intelligence, the OEM helps end users reduce energy consumption and minimize water use. This is just one way that OEMs can embrace the IIoT to grow their businesses.
Additionally, engineers can make use of end-user geographical information to inform the right user at the right location.
Geo-intelligence technology takes data, puts context to assets, and then applies a geo-location to that asset. Thus, an OEM can automatically serve the right information quickly on the mobile device closest to the equipment.
For example, the geo-intelligent mobile device knows that the equipment is Pump 2 in the South River Pump Station. The appropriate screen instantly displays the data, such as KPIs. In addition, the mobile device can make use of an adjustable radius – or field of view, and can display all of the pumps located within three miles.
In a manufacturing environment, geo signals are even more accurate thanks to Wi-Fi technology. Operators can be in a noisy factory and use the geo-intelligence and navigation to obtain the right information at their fingertips based on their location. This technology can speed response and reduce troubleshooting time.
The benefits of geo-intelligence multiply when applied to alarms and analytics. For example, OEMs can send an alarm to an operator, engineer or manager based on physical location. As an example, an engineer standing on Floor 4 might hear an alarm related to a machine on Floor 1, which is 25 minutes away. The geo-intelligent system determines that a colleague is 100 feet away from the machine and sends the signal there for a faster response.
Engineers can also deploy IIoT technology to filter alarms for more efficiency. According to analysts, 75% of all alarms are noise, and many companies wish to reduce that number. OEMs can deploy a system that captures all the raw alarms and sorts them based on analytics. The system delivers the right alarm, perhaps even a derived or intelligent alarm, to the operator interface – whether stationary or mobile – rather than delivering several warnings that end up just being confusing.
Predictive knowledge and action
With an IIoT foundation, design engineers can add a layer of proactive analysis for predictive intelligent alarming. For example, if a machine monitors a temperature which exceeds the upper control limit, an alarm activates. Traditionally, an operator would react to the alarm. Analytics make it possible to predict when the event will happen and to take steps in advance of it. Either the OEM can supply analyzed information as a value-added service or it can be a feature of the equipment.
As an example, software on food processing equipment can monitor a temperature, run an analytic on it and predict temperature scenarios based on a statistical model. The OEM can design equipment that sends operator alarms to ensure action takes place quickly, before a batch is ruined. The same could be true for an OEM running a remote monitoring and predictive service for customers related to critical end user operations.
The application of predictive knowledge, delivered as an intelligent alarm in a geo-aware context is far reaching. It offers new ways of consistently optimizing operations – a high value that design engineers can provide to their end users.
Steps to take in the Digital Era
The Industrial Internet of Things has many implications. OEMs can consider several steps to get the true value of the IIoT and maximize the benefits of these new technologies.
Give structure to data
There is no shortage of data, and it is largely unstructured. The first step is to map data to a structured model. This helps capture data and begins the process of transforming it. An equipment model drives structured navigation. From this structure, users easily configure data to the level of entry that makes sense.
Once the data is in a navigable structure, users can apply analytics that create a context for action. A perfect example is the application of analytics to alarms. Most industrial assets have a variety of alarms – and usually an overwhelming amount on a daily basis. With an advanced alarming platform, OEMs can apply analytics to the alarms, take away the noise, and deliver relevant alarms to the appropriate person by role and location. The cost- and time savings can deliver an estimated 20% or more boost in operator efficiency.
Make transitions seamless to drive action
Once there is a navigable structure and analytics for context, the next step is to drive the appropriate action. OEMs can deliver seamless transitions on any device, getting the user the right information quickly, at the right place and time. For example, if an operator receives a critical alarm, a mobile device can immediately show the right information to guide the user through the appropriate response steps.
Leverage secure-by-design methodologies
Finally, OEMs and end users must implement IIoT technology using secure-by-design methodologies. The confidentiality, integrity and availability of systems and data are critical. In our IIoT world, OEM must consider how to deliver information in a staged fashion, how to limit control, and how to expose data for accessing information, anytime, anywhere for secure agility.