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E Tech Group’s Vice President of Business Development, Laurie Cavanaugh was a presenter for this Control Engineering webcast, where she and Matt Ruth, President of Avanceon, discuss what “just enough data analysis” is, pros and pitfalls, and the future of data analysis in automated manufacturing. The webcast included live Q&As from the audience, and was followed up with an article offering even more answers to automation professionals’ questions about data analytics in their plant processes. Just-in-time supply chain strategy limits were exposed in a global pandemic. Is just-enough industrial data analysis working for operations? Is the right data getting to the right people to optimize operations in time? Where are the bottlenecks and how are they being addressed? Where’s data going to become information and who’s seeing it? In the cloud or on premise or both? Are your knowledge brokers seeing the right information quickly enough to make the right decisions, or are your analytics too much, too late to be effective? Utilizing case studies as illustrations and an interactive format, Cavanaugh and Ruth advise control system integrators on how to: Determine if just-enough data analytics provides enough benefits to operations. Identify if enough data intelligence (results of analytics) is getting to people who matter. Examine bottlenecks in data analysis and how to address them. Review tools and architectures for eliminating bottlenecks. See lessons learned in applying data analytics (too little too late or just enough in time). This presentation focused on the future of data analytics in industrial manufacturing, including obstacles control engineers need to overcome in order to move forward in the industry and embrace the new role data analysis will take in the field. Visit E Tech Group’s blog for more automation industry news and insights.
by Mark Noseworthy, Group Engineering Manager I was recently working at a client and made some DeltaV code changes on the Development system to a composite1 used in a control module. One of the code changes involved adding an Alias2 reference out to a different control module to obtain some information running in that other module concurrently. Once it was all configured and tested, the code was downloaded successfully to the Production system, and I didn’t think any more on it. Fast forward a few months, and a colleague is modifying the same code for a different project. He was experiencing some odd behavior in the code that he couldn’t explain. He pulled in the client and me to look at it, and none of us could figure out what was happening. The phase that was running on the unit module that contained the control module with the composite that we had both updated would not run successfully the first time through the code, but if manually manipulated, the phase would run as expected subsequent to that first pass through the logic. We troubleshot the issue by first reinstalling the code without my colleague’s changes, assuming that would fix things. It did not. We were flummoxed. Since my colleague’s logic needed to be used in Production, the client indicated that it was acceptable to put on the Production system, attributing the odd behavior as a Development system issue. Upon doing this there were no issues running in Production. Although grateful, we were doubly flummoxed now. Clearly the issue lies in the Development system, but where? Trying to Uncover the Mystery Flaw in the Control System Further investigation discovered a yellow question mark (which generally means some sort of error) on a CALC (calculation) block that was definitely not there when the initial code was verified. This also happens to … Continued
“The best jobs we’ve had are the ones that have everyone involved up front, sitting down together at the beginning to discuss the project. Operations folks should also be engaged before the project starts. Get champions identified earlier on.” Craig Cooper, Engineering Account Manager, and Jason Phelps, Project Manager, recently authored a in a blog post for Automation World on the psychology of change and how to best prepare when taking on a project upgrade: Here’s a scenario—we’re contacted by a company to help them with a system upgrade. The client wants a system upgraded with Ethernet, databases, historians, etc. We provide a proposal, and upper-level engineering love it. Then, the project kicks off. But the boots-on-the-ground operations people hate it. They spend much of the project execution trying to make the new system exactly like it was before. Throughout this process, we try to coax the operations folks to see our way is better, and to show them why it’s better and how it will help them. It feels like a constant sales presentation. This results in a lot of rework, because we want to make them happy. And then as they adjust, they go back and forth on changes. Sound familiar? Often when companies approach an upgrade project, they go straight into the technology, functional requirements, and business needs. These are all very important considerations, but an important piece of the puzzle is missing: the psychology of the change itself and how best to manage it. To an operations team with production goals and other metrics to meet every shift, change is not exactly embraced with open arms. Change can mean adaptation (which takes time that they think they don’t have), it can be scary (even the best ideas can be poorly executed with catastrophic results, and they’ve probably seen … Continued
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