Transforming Operations: The Power of AIoT in Real-Time Monitoring

Are you interested in taking your sensor-driven real-time insights to the next level? The latest trends in real-time solutions driving operations excellence for anomaly detection with emissions and corrosion monitoring leveraging Artificial Intelligence of Things (AIoT) come to the forefront in my recent discussion with Molex executive Krishna Uppuluri, from mPACT2WO.  

#AIoT #RealTimeSolutions #Innovation #OperationsExcellence

Transcript

Peter Manos: Welcome to our podcast!  I'm your host, Peter Manos, Director of Research at ARC Advisory Group. And I have with me a person who's well known by folks at many refineries, petrochemical plants and pipeline operators. And I guess, as you say, well known and also highly respected Krishna Uppuluri, VP and GM of mPACT2WO. Thanks for joining us, Krishna.

Krishna Uppuluri: Thanks, Peter. Pleasure to join you.

Peter Manos: So Krishna, I've seen how you and your team focus on your end users from a boots on the ground workforce perspective beyond Molex driving improvements based on your solutions’ technical benefits, why do you have this end user focus? 

Krishna Uppuluri: Yes, so it becomes clear if you look at the legacy of Industrial Internet of Things, so-called IIoT solutions. They focused too much on technology and they were quite complex. A bit too complex at times for optimal adoption by end users—the folks we affectionately describe as the folks with boots on the ground. Hence, at a lot of the industrial sites these legacy technologies ended up giving end users a somewhat incomplete level of adoption, or a spotty adoption with just some isolated islands of efficiency. But for a ground up transformation and continuous improvement, the sites need active adoption by boots on the ground. Such adoption not only increases daily efficiencies, but it addresses the larger issues related to aging workforce with consistent data-enabled decisions. That's why we focus on boots on the ground adoption, and enablement.

Peter Manos: Interesting. So for the emissions monitoring and leak detection solutions, among your other solutions at Molex we are looking at the stewardship aspect and the bottom line benefits, but also obviously from a trend point of view, Artificial Intelligence of Things is also in play—what we call AIoT—as well as EHS or ESG related domains. These span across operational aspects of environmental, health and safety for the workforce and work processes. So how do you harmonize the seeming conflicts between stewardship and the bottom line, versus EHS and all the other concerns?

Krishna Uppuluri: You know there are many areas of concern out there. All of these initiatives fall into a spectrum, ranging from short term tactical initiatives to long term strategic initiatives. They're not necessarily conflicting. However, they can lead to delays and conflict, especially if they're all force fitted into one eclectic mix, so I think it's important at both the site level, and at the level of the enterprise, to prioritize these into incremental initiatives rather than one whole eclectic mix of things.

Peter Manos: That makes sense and fits what I've been seeing when I look at your end users. You're giving them an ability to detect problems a lot earlier and the early detection of anomalies seems to be a big paradigm shift. Can you speak to how plant managers view mPACT2WO?

Krishna Uppuluri: Yes—plant managers are concerned about site-wide safety, compliance risks and unplanned downtimes. Their initial interest in early detection is generally driven by specific and reactive urgent requirements. However, once they see the benefits of early detection. They invest in the broader requirements to proactively transform their operations.

Peter Manos: Interesting, so we all can see that detecting anomalies in an emissions monitoring issue earlier, is of benefit, but you also have the mPACT2WO solutions around corrosion monitoring. So what are the concerns in relation to that, in terms of process or reliability or mechanical integrity engineers and other very specific roles such as a process engineer or other engineers in corrosion-related focus areas.

Krishna Uppuluri: Yeah, corrosion monitoring is deep rooted in a schedule-based approach and is also deeply rooted in inspectors’ expertise. If you look at the legacy sensor-based monitoring solutions, they were all limited by inconsistent, low confidence results.

Peter Manos: In other words, it was a manual process. A worker would go and temporarily place an ultrasonic corrosion monitoring sensor on a pipe in a certain location, get the data, and then go back to the control room or wherever they were. It wasn't like a automated, instrument set of data. In other words?

Krishna Uppuluri: Yes, they used those sensors’ data for directional insights, but still relied heavily on their own gut-feel assessment. But with our high fidelity sensors and AI ML insights, inspectors are now relying on our solution for trusted corrosion insights.

Peter Manos: So it's better data and it's a lot more data too, for the corrosion monitoring. And I guess along similar lines, what about these various end users’ emissions monitoring and leak detection. What are their key areas of concern and the areas they most key care about?

Krishna Uppuluri: Emissions monitoring can lead to inside out issues ranging from fugitive emissions, compliance exceptions to the safety of personnel and communities. So it's a different thing, compared to corrosion monitoring. In the case of emissions monitoring, early detection gives the various stakeholders valuable time to contain their emissions and systematize quick fixes. So sites usually start with known areas of concern such as docks and fence-lines and remote terminals, and then expand to sensitive process units.

Peter Manos: Do you ever see end users sort of stuck, or attached to their old ways of doing things? For example are there situations where they think even though they have less sophisticated systems for leak detection and emissions monitoring, they are willing to get by with those. And not need to put in something more sophisticated?

Krishna Uppuluri: The need to adopt a new paradigm is always triggered by unexpected anomalies or difficulty in staffing, or changes in regulations. So industrial sites which are often in remote areas and with the manual emissions monitoring being a tedious effort, our new paradigm delivers trusted insights and is easy to adopt. As a result, the end users become open to changing from existing human-centered system to the new sensor-outcome centered solution.

Peter Manos: So that's excellent. And does that go for both pipelines and for fence line monitoring as well as the process units and other equipment typically being monitored in facilities?

Krishna Uppuluri: Absolutely. Usually, it's a process that starts with the sites’ immediate need and then it expands to other adjacent use cases, to achieve a more holistic transformation.

Peter Manos: Excellent. So it's like there's a thin end of the wedge in terms of their getting value and then it expands. That's excellent. So, before we wrap up, Krishna, could you highlight the key takeaways for plant managers and the broader industry?

Krishna Uppuluri: Yeah. As I said at the beginning of the session, our focus on “boots on the ground” adoption, and operational efficiency, is what drives our solutions. First, of course, the early detection with trusted insights. Second, consumerized apps for easy adoption. Third, solution as a service business model that helps the sites avoid the burden of the solution components and keeps their focus on their operational anomalies. So our solutions’ focus on boots on the ground leads to systemized operational efficiencies. It also addresses the issues related to aging workforce, with consistent data enabled decisions. So, with mPACT2WO Solutions, that's how we lead to a more transformative, holistic effect on industrial operation.

Peter Manos: Well, it certainly sounds like mPACT2WO is very well named because of the impact that it has. And I want to thank you, Krishna for these valuable insights. So it's pretty clear that embracing technological advancements like AIoT is crucial for achieving operational excellence and sustainability. As we conclude this episode, I think it's important to recognize that the path forward involves a lot more collaboration and innovation than in the past for folks to meet challenges that they face. Finally, to all listeners, we want to thank you for joining us today and we hope this discussion has given you some practical insights and inspiration to drive positive change in your operations. And until next time, stay informed and stay engaged. And again thank you Krishna for your time and expertise.

Krishna Uppuluri: Thank you, Peter. Excellent.