Check out Roger’s latest Seeq video demonstrating predictive maintenance for a reverse osmosis train. Roger uses linear regression on real (not simulated) RO normalized flow data to predict a timeframe for the next membrane cleaning. This same solution can be used to adjust pre-treatment chemical feeds by monitoring the rate at which the membranes are fowling. Enjoy.
Inductive Automation’s long-anticipated Ignition 8 is slated to be released in the upcoming weeks. One of its many awesome new features is the introduction of the Perspective module which creates a seamless browser-based user experience using HTML5. This new front end allows for responsive screen design that will adjust automatically to a monitor, tablet, or a mobile screen as needed.
We talk a lot about data and analytics in our industry today with the goal of finding and rooting out waste and inefficiency in our plants. Until recently, however, the benefits of big data have been limited to very large enterprises that can afford custom solutions. Seeq's data analytics package is changing all that with their reasonably priced, but very powerful data analytics tool. In this post, I walk you through the process of analyzing cooling system compressor efficiency using Seeq.
Most manufacturing organizations have data in process historians or more traditional databases that can provide significant insights if analyzed with the right tools. Software tools that specialize in reporting, dashboarding, analytics, and/or visualization can provide valuable information to improve operational efficiency in manufacturing and processing environments.
There are a myriad of tools available today for industrial analytics. Some of these tools come from traditional automation software providers, but many come from companies that we are more used to seeing in the office. Here are a few products we have run across that provide an idea of what is out there, and hopefully will provide a starting point for further exploration.
The MQTT protocol is rapidly being adopted as a reliable, efficient protocol in modern industrial data collection applications. MQTT uses a variety of techniques to provide highly efficient use of bandwidth to collect data from a wide range of sources and then make that data available to interested subscribers. Cirrus Link Solutions provides various modules for Inductive Automation Ignition enabling applications to take advantage of this protocol for building IIoT and SCADA applications.
There are two independent web development type modules in Ignition that allow one to host a custom API or web page on a web server directly from Ignition – the WebDev module by Inductive Automation and the Web Services module by Sepasoft. Both of these modules allow external systems (ERP, SAP, DBs, etc.) to interact with Ignition, which can be used as a central hub for bidirectional data processing for these systems. The two main classes of web services are REST (Representational State Transfer) and SOAP (Simple Object Access Protocol). REST is available through both modules and can utilize JSON and XML data formats, while SOAP is available only through the Web Services module and only utilizes XML data formats.
Back in 1834, Samuel Taylor wrote a poem titled “The Rime of the Ancient Mariner” that is still famous in part for its line “water, water everywhere, nor any drop to drink.” Much like those ill-fated mariners, our manufacturing enterprises accumulate ever larger oceans of data, but we struggle to squeeze a drop of information from them. Data analytics to the rescue! From looking at what happened in the past to predicting what might occur in the future, knowing how to effectively apply big data analytics techniques on your plant floor can provide numerous time, cost, and resource saving benefits.
In the current age of information, organizations of all kinds are increasingly collecting and analyzing large amounts of data on everything from production information to client buying behavior and preferences. These data sets are big. Very, very big. And that’s the scientific reason we call them “big data.” More technically, big data is any high-volume, high-velocity, and high-variety informational asset.