Manufacturing intelligence is not a new application area, but it is facing new challenges as the process industries begin to add more sensors and intelligent devices into the mix in an effort to jump on the Industrial Internet of Things (IIoT) bandwagon.
The challenge here becomes how to integrate different data sources from both structured and unstructured information. Given that most manufacturers adopt enterprise manufacturing intelligence (EMI), also referred to as operational intelligence, to improve visibility in order to make faster decisions and extract more value from data, EMI software could lose its luster if it doesn’t evolve with the rest of the plant.
This was the topic of conversation at the ARC Industry Forum in Orlando this past February in which a panel of end users, integrators and suppliers talked about the future of operational intelligence. Despite the IIoT obstacle, the future for EMI is actually very bright as the technology evolves with the times and new suppliers enter the arena.
One EMI supplier coming on to the scene is Seeq. The company touts its technology as the “Google” of industrial process data. It works with existing process historians, such as the OSIsoft PI System, Emerson’s Advanced Continuous Historian and Honeywell’s Uniformance Process History Database (PHD). By leveraging data management innovations like visual search, annotations, capsules and worksheets, the software can perform discovery and diagnostics across existing historians, batch systems, asset management and even ERP. To that end, Seeq also includes a comprehensive REST API for the creation of industry-specificapplications that leverage Seeq functionality, as well as enabling interoperability with business intelligence (BI) tools such as Excel, Tableau, SAS, and MATLAB.
The Seeq secret, the company says, is that it is a browser-based application for engineers to find insights into time-series data, and, they claim it’s one-of-a-kind, as there isn’t a category of existing products within which it fits. It’s particularly useful in oil & gas, power generation, chemicals and pharmaceutical industries as it can search complex data sources, enables collaborative problem-solving by aggregating and combining plant and production data with operator insights, and the ability to quickly optimize asset performance.
According to the company, the “Google-like” search capabilities use advanced algorithms to find pattern matches, limit conditions, and define time periods of interest. There is a scripting language to write equations to combine and analyze results and scatter plots to visualize data sets. And all of this can be shared with colleagues, in real time, through Seeq’s brower-based interface.
Brandon Lake, senior business systems analyst at Iberdrola Renewable Energy Services is responsible for getting users reliable data so that they can make informed decisions. As a large wind energy company, there was data coming in from all different directions, including a variety of in-house analytic tools including OSIsoft, SAP and a SCADA system. Lake and his team layered Seeq on top of the existing tools—without adding more complexity.
“We [collect a lot] of data per day at the main site and we don’t duplicate that with Seeq, we just index it and look at data in there,” Lake said during the panel discussion. “Seeq helps us find key aspects of the data that we were not able to find before.”
For example, they can see the data signals coming in from different sources and they are able to add context to the data, like what time of day wind is coming in from various operating sites, he said.
Perhaps the key here is the involvement of the people using the analytics. The engineers and operators have the knowledge and experience to understand what matters most in the production process. So, while technology on the plant floor evolves, the future of EMI is actually in your hands. You just need to “seek out” the right tools.
