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Across the industrial sector, data analytics and the corresponding visualization of its results are expected to drive change and simplify the digitalization of the factory floor. As has been noted by many, while the average data analyst understands the figures and numbers on an analytical dashboard, the average factory-floor operator does not have the required training to transcribe analyzed data. Thus, simplified processes to visualize data for everyone is required.
To understand the importance of data visualization, the analogy of two accelerating cars – one with a speedometer and the other without one – paints a perfect picture of what it’s like to be able to visualize and not visualize data in real-time. In this scenario, two cars are driving parallel to one another at approximately 70 mph on a road with a speed limit of 75 mph. The driver/operator in one car has a working speedometer which serves as a reference point for how fast the vehicle is moving. The second driver has a defective speedometer and relies on the speed of the other to maintain the speed limit.
Getting to a fork in the road, both drivers take different directions. And while the first driver continues to drive within the speed limit, the driver with a defective speedometer drives “blind” and is finally caught and penalized for going over the limit. In a digitalized factory, the equivalent of a speedometer is necessary to provide a means to visualize data. Operators with real-time information can work according to the master production plan, while operators who are “driving blind” end up experiencing downtime or have significant changes to expected throughput.
Building an interconnected framework, as well as capturing and analyzing data are just the first phases to the digitalization of the factory floor. Providing the end-user, operators, and decision makers with the information required to take action is the next important phase to digitally transform all operational processes. Here, data visualization refers to dynamic stories or information that actually provide insight.
According to Gartner, dynamic data and data visualization technologies are expected to replace the traditional point and click dashboards used in brownfield factories. These technologies will include human-machine interfaces (HMI), dynamic web-based HMIs or panels, and smart mobile devices.
Web-based HMIs are fast becoming the technology of choice for visualizing data in a digitalized factory. The increasing reliance on web-based HMIs, also known as web panels, is due to their ability to deliver contextual information through rich animations, graphs, and informal content. The ability of web-based HMIs to provide clients with updated applications that require no configurations is another reason for their popularity in the industrial sector.
Smart mobile devices and wearables also offer a viable ecosystem for visualizing industrial data remotely and on the go. The remote access that modern data visualization technologies provide is a staple of Industrie 4.0 and the digitized factory floor. The ability to visualize data remotely ensures real-time insight into industrial operations without the limit of location. In an interconnected environment, actions can also be taken remotely which then ensures safety and improves the performance of factory processes.
Although web-based HMIs are excellent tools for visualizing data from individual equipment and interconnected systems, the digital twin is a powerful data analysis and visualization tool rolled into one digital platform. The digital twin is a digital mirror of physical processes that runs on data. The data collected using sensors, IoT devices, and from digital transformation initiatives are fed into a digital twin to recreate the entire factory and a virtual environment for running optimization tests.
The digital twin does not work in a vacuum, rather it relies on data visualization hardware such as web-based panels and smart devices to showcase its results to decision makers.
The ability to visualize data from individual equipment, a connected system, and a factory’s entire production line improves performance in multiple ways. One example is the ability to optimize data-driven plant performance optimization plans. Accessing data from individual equipment and running analysis on how the data compares to the optimal benchmark data of the equipment shows an operator in a specific area if a piece of equipment is lagging behind. The operator can then investigate further to pinpoint the reasons for its reduced performance.
In this scenario, benchmark data refers to historical data highlighting the optimal throughput or performance that the equipment is capable of. The provision of animations highlighting how and why a piece of similar equipment lags behind provides the information needed to fine-tune the equipment or the production process.
A simpler example is the use of general display panels to showcase the performance of individual machines within a production unit. General display panels, which every operator can see, quickly highlight which workstation or operator is struggling to get the best result out of a piece of equipment. Thus, more experienced operators or the factory-floor manager can come to the aid of the operator to ensure that optimal performance is achieved.
Digitalization of the factory floor is the future of industrial pursuits, and data visualization has a huge role to play in implementing a digital transformation initiative or strategy. Thus, factory owners who intend to continuously implement digital transformation policies must constantly search for the best data visualization solutions that ensure the implementation process is a success.