How Texmark Chemicals pursues analysis-rich, IoT-pervasive path to the ‘refinery of the future’

Oil refinery industry

The next BriefingsDirect Voice of the Customer discussion revisits the drive to define the “refinery of the future” at Texmark Chemicals.

Texmark has been combining the best of operational technology (OT) with IT and now Internet of Things (IoT) to deliver data-driven insights that promote safety, efficiency, and unparalleled sustained operations.

Stay with us now as we hear how a team approach — including the plant operators, consulting experts and latest in hybrid IT systems — joins forces for rapid process and productivity optimization results.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy.

To learn how, are are joined by our panel, Linda Salinas, Vice President of Operations at Texmark Chemicals, Inc. in Galena Park, Texas; Stan Galanski, Senior Vice President of Customer Success at CB Technologies (CBT) in Houston, and Peter Moser, IoT and Artificial Intelligence (AI) Strategist at Hewlett Packard Enterprise (HPE). The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Stan, what are the trends, technologies, and operational methods that have now come together to make implementing a refinery of the future approach possible? What’s driving you to be able to do things in ways that you hadn’t been able to do before?

Galanski

Galanski: I’m going to take that in parts, starting with the technologies. We have been exposed to an availability of affordable sensing devices. These are proliferating in the market these days. In addition, the ability to collect large amounts of data cheaply — especially in the cloud — having ubiquitous Wi-Fi, Bluetooth, and other communications have presented themselves as an opportunity to take advantage of.

On top of this, the advancement of AI and machine learning (ML) software — often referred to as analytics — has accelerated this opportunity.

Gardner: Linda, has this combination of events dramatically changed your perspective as VP of operations? How has this coalescing set of trends changed your life?

Salinas: They have really come at a good time for us. Our business, and specifically with Texmark, has morphed over the years to where our operators are more broadly skilled. We ask them to do more with less. They have to have a bigger picture as far as operating the plant.

Today’s operator is not just sitting at a control board running one unit. Neither is an operator just out in a unit, keeping an eye on one tower or one reactor. Our operators are now all over the plant operating the entire utilities and wastewater systems, for example, and they are doing their own lab analysis.

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This technology has come at a time that provides information that’s plant-wide so that they can make more informed decisions on the board, in the lab, whenever they need.

Gardner: Peter, as somebody who is supplying some of these technologies, how do you see things changing? We used to have OT and IT as separate, not necessarily related. How have we been able to make those into a whole greater than the sum of their parts?

OT plus IT equals success 

Moser

Moser: That’s a great question, Dana, because one of the things that has been a challenge with automation of chemical plants is these two separate towers. You had OT very much separate from IT.

The key contributor to the success of this digitization project is the capability to reboot those two domains together successfully. 

Gardner: Stan, as part of that partnership, tell us about CBT and how you fit.

Galanski: CBT is a 17-year-old, privately owned company. We cut our teeth early on by fulfilling high-tech procurement orders for the aerospace industry. During that period, we developed a strength for designing, testing, and installing compute and storage systems for those industries and vendors.

It evolved into developing an expertise in high-performance computing (HPC), software design platforms, and so forth.

About three years ago, we recognized the onset of faster computational platforms and massive amounts of data — and the capability for software to control that dataflow — was changing the landscape. Now, somebody needed to analyze that data faster over multiple mediums. Hence, we developed a practice around comprehensive data management and combined that with our field experience. That led us to become a systems integrator (SI), which is what we’ve been assigned to for this refinery of the future.

Gardner: Linda, before we explore more on what you’ve done and how it improves things, let’s learn about Texmark. With a large refinery operation, any downtime can be a big problem. Tell us about the company and what you are doing to improve your operations and physical infrastructure.

Salinas

Salinas: Texmark is a family-owned company, founded in 1970 by David Smith. And we do have a unique set of challenges. We sit on eight acres in Galena Park, and we are surrounded by a bulk liquid terminal facility.

So, as you can imagine, a plant that was built in the 1940s has older infrastructure. The layout is probably not as efficient as it could be. In the 1940s, we didn’t have a need for wastewater treatment. Things may not have been laid out in the most efficient ways, and so we have added these things over the years. So, one, we are landlocked, and, two, things may not be sited in the most optimal way.

For example, we have several control rooms sprinkled throughout the facility. But we have learned that siting is an important issue. So we’ve had to move our control room to the outskirt of the process areas.

As a result, we’ve had to reroute our control systems. We have to work with what we have, and that presents some infrastructure challenges.

Also, like other chemical plants and refineries, the things we handle are hazardous. They are flammable, toxic, and they are not things people want to have in the air that they breath in neighborhoods just a quarter-mile downwind of us.

So we have to be mindful of safe handling of those chemicals. We also have to be mindful that we don’t disrupt our processes. Finding the time to shut down to install and deploy new technology, is a challenge. Chemical plants and refineries need to find the right time to shut down and perform maintenance with a very defined scope, and on a budget.

And so that capability to come up and down effectively is a strength for Texmark because we are a smaller facility and so are able to come up and down and deploy and test and prove out some of these technologies. 

Gardner: Stan, in working with Linda, you are not just trying to gain incremental improvement. You are trying to define the next definition, if you will, of a safe, efficient, and operationally intelligent refinery.

How are you able to leapfrog to that next state, rather than take baby steps, to attain an optimized refinery?

Challenges of change 

Galanski: First we sat down with the customer and asked what the key functions and challenges they had in their operations. Once they gave us that list, we then looked at the landscape of technologies and the available categories of information that we had at our disposal and said, “How can we combine this to have a significant improvement and impact on your business?”

We came up with five solutions that we targeted and started working on in parallel. They have proven to be a handful of challenges — especially working in a plant that’s continuously operational.

The connected worker solution is garnering a lot of attention in the marketplace. With it, we are able to bring real-time data from the core repositories of the company to the hands of the workers in the field.

Based on the feedback we’ve received from their personnel; we feel we are on the right track. As part of that, we are attacking predictive maintenance and analytics by sensoring some of their assets, their pumps. We are putting video analytics in place by capturing video scenes of various portions of the plant that are very restrictive but still need to have careful monitoring. We are looking at worker safety and security by capturing biometrics and geo-referencing the location of workers so we know they are safe or if they might be in danger.

The connected worker solution is garnering a lot of attention in the marketplace. With it, we are able to bring real-time data from the core repositories of the company to the hands of the workers in the field. Oftentimes it comes to them in a hands-free condition where the worker has wearables on his body that project and display the information without them having to hold a device.

Lastly, we are tying this all together with an asset management system that tracks every asset and ties them to every unstructured data file that has been recorded or captured. In doing so, we are able to put the plant together and combine it with a 3D model to keep track of every asset and make that useful for workers at any level of responsibility.

Gardner: It’s impressive, how this touches just about every aspect of what you’re doing.

Peter, tell us about the foundational technologies that accommodate what Stan has just described and also help overcome the challenges Linda described.

Foundation of the future refinery

Moser: Before I describe what the foundation consists of, it’s important to explain what led to the foundation in the first place. At Texmark, we wanted to sit down and think big. You go through the art of the possible, because most of us don’t know what we don’t know, right?

You bring in a cross-section of people from the plant and ask, “If you could do anything what would you do? And why would you do it?” You have that conversation first and it gives you a spectrum of possibilities, and then you prioritize that. Those prioritizations help you shape what the foundation should look like to satisfy all those needs.

That’s what led to the foundational technology platform that we have at Texmark. We look at the spectrum of use cases that Stan described and say, “Okay, now what’s necessary to support that spectrum of use cases?”

But we didn’t start by looking at use cases. We started first by looking at what we wanted to achieve as an overall business outcome. That led us to say, “First thing we do is build out pervasive connectivity.” That has to come first because if things can’t give you data, and you can’t capture that data, then you’re already at a deficit.

Then, once you can capture that data using pervasive Wi-Fi with HPE Aruba, you need a data center-class compute platform that’s able to deliver satisfactory computational capabilities and support, accelerators, and other things necessary to deliver the outcomes you are looking for.

The third thing you have to ask is, “Okay, where am I going to put all of this computing storage into?” So you need a localized storage environment that’s controlled and secure. That’s where we came up with the edge data center. It was those drivers that led to the foundation from which we are building out support for all of those use cases.

Gardner: Linda, what are you seeing from this marriage of modernized OT and IT and taking advantage of edge computing? Do you have an ability yet to measure and describe the business outcome benefits?

Hands-free data at your fingertips 

Salinas: This has been the perfect project for us to embark on our IT-OT journey with HPE and CBT, and all of our ecosystem partners. Number one, we’ve been having fun.

Two, we have been learning about what is possible and what this technology can do for us. When we visited the HPE Innovation Lab, we saw very quickly the application of IT and OT across other industries. But when we saw the sensored pump, that was our “aha moment.” That’s when we learned what IoT and its impact meant to Texmark.

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As for key performance indicators (KPIs), we gather data and we learn more about how we can employ IoT across our business. What does that mean? That means moving away from the clipboard and spreadsheet toward having the data wherever we need it — having it available at our fingertips, having the data do analytics for us, and telling us, “Okay, this is where you need to focus during your next precious turnaround time.”

The other thing is, this IoT project is helping us attract and retain talent. Right now it’s a very competitive market. We just hired a couple of new operators, and I truly believe that the tipping point for them was that they had seen and heard about our IoT project and the “refinery of the future” goal. They found out about it when they Googled us prior to their interview.

We just hired a new maintenance manager who has a lot of IoT experience from other plants, and that new hire was intrigued by our “refinery of the future” project.

Finally, our modernization work is bringing in new business for Texmark. It’s putting us on the map with other pioneers in the industry who are dipping their toe into the water of IoT. We are getting national and international recognition from other chemical plants and refineries that are looking to also do toll processing.

They are now seeking us out because of the competitive edge we can offer them, and for the additional data and automated processes that that brings to us. They want the capability to see real-time data, and have it do analytics for them. They want to be able to experiment in the IoT arena, too, but without having to do it necessarily inside their own perimeter.

Gardner: Linda, please explain what toll processing is and why it’s a key opportunity for improvement?

Collaboration creates confidence 

Salinas: Texmark produces dicyclopentadiene, butyl alcohol, propyl alcohol, and some aromatic solvents. But alongside the usual products we produce and sell, we also provide “toll processing services.” The analogy I like to tell my friends is, “We have the blender, and our customers bring the lime and tequila. The we make their margaritas for them.”

So our customers will bring to us their raw materials. They bring the process conditions, such as the temperatures, pressures, flows, and throughput. Then they say, “This is my material, this is my process. Will you run it in your equipment on our behalf?”

When we are able to add the IoT component to toll processing, when we are able to provide them data that they didn’t have whenever they ran their own processes, that provides us a competitive edge over other toll processors.

When we are able to add the IoT component to toll processing, when we are able to provide them data that they didn’t have whenever they ran their own processes, that provides us a competitive edge over other toll processors.

Gardner: And, of course, your optimization benefits can go right to the bottom line, so a very big business benefit when you learn quickly as you go.

Stan, tell us about the cultural collaboration element, both from the ecosystem provider team support side as well as getting people inside of a customer like Texmark to perhaps think differently and behave differently than they had in the past.

Galanski: It’s all about human behavior. If you are going to make progress in anything of this nature, you are going to have to understand the guy sitting across the table from you, or the person out in the plant who is working in some fairly challenging environments. Also, the folks sitting at the control room table with a lot of responsibility for managing the processes with lots of chemicals for many hours at a time. 

So we sat down with them. We got introduced to them. We explained to them our credentials. We asked them to tell us about their job. We got to know them as people; they got to know us as people.

We established trust, and then we started saying, “We are here to help.” They started telling us their problems, asking, “Can you help me do this?” And we took some time, came up with some ideas, and came back and socialized those ideas with them. Then we started attacking the problem in little chunks of accomplishments.

We would say, “Well, what if we do this in the next two weeks and show you how this can be an asset for you?” And they said, “Great.” They liked the fact that there was quick turnaround time, that they could see responsivity. We got some feedback from them. We developed a little more confidence and trust between each other, and then more things started out-pouring a little at a time. We went from one department to another and pretty soon we began understanding and learning about all aspects of this chemical plant.

It didn’t happen overnight. It meant we had to be patient, because it’s an ongoing operation. We couldn’t inject ourselves unnaturally. We had to be patient and take it in increments so we could actually demonstrate success.

And over time you sometimes can’t tell the difference between us and some of their workers because we all come to meetings together. We talk, we collaborate, and we are one team — and that’s how it worked.

Gardner: On the level of digital transformation — when you look at the bigger picture, the strategic picture — how far along are they at Texmark? What would be some of the next steps? 

All systems go digital 

Galanski: They are now very far along in digital transformation. As I outlined earlier, they are utilizing quite a few technologies that are available — and not leaving too many on the table. 

So we have edge computing. We have very strong ubiquitous communication networks. We have software analytics able to analyze the data. They are using very advanced asset integrity applications to be able to determine where every piece, part, and element of the plant is located and how it’s functioning.

I have seen other companies where they have tried to take this only one chapter at a time, and they sometimes have multiple departments working on these independently. They are not necessarily ready to integrate or to scale it across the company.

But Texmark has taken a corporate approach, looking at holistic operations. All of their departments understand what’s going on in a systematic way. I believe they are ready to scale more easily than other companies once we get past this first phase.

Gardner: Linda, any thoughts about where you are and what that has set you up to go to next in terms of that holistic approach?

Salinas: I agree with Stan. From an operational standpoint, now that we have some sensored pumps for predictive analytics, we might sensor all of the pumps associated with any process, rather than just a single pump within that process.

That would mean in our next phase that we sensor another six or seven pumps, either for toll processing or our production processes. We won’t just do analytics on the single pump and its health, lifecycle, and when it needs to be repaired. Instead we look at the entire process and think, “Okay, not only will I need to take this one pump down for repair, but instead there are two or three that might need some service or maintenance in the next nine months. But the fuller analytics can tell me that if I can wait 12 months, then I can do them all at the same time and bring down the process and have a more efficient use of our downtime.”

I could see something like that happening.

Galanski: We have already seen growth in this area where the workers have seen us provide real-time data to them on hands-free mobile and wearable devices. They say, “Well, could you give me historical data over the past hour, week, or month? That would help me determine whether I have an immediate problem, not just one spike piece of information?”

So they have given us immediate feedback on that and that’s progressing.

Gardner: Peter, we are hearing about a more granular approach to sensors at Texmark, with the IoT edge getting richer. That means more data being created, and more historical analysis of that data.

Are you therefore setting yourself up to be able to take advantage of things such as AI, ML, and the advanced automation and analytics that go hand in hand? Where can it go next in terms of applying intelligence in new ways?

Deep learning from abundant data 

Moser: That’s a great question because the data growth is exponential. As more sensors are added, videos incorporated into their workflows, and they connect more of the workers and employees at Texmark their data and data traffic needs are going to grow exponentially.

But with that comes an opportunity. One is to better manage the data so they get value from it, because the data is not all the same or it’s not all created equal. So the opportunity there is around better data management, to get value from the data at its peak, and then manage that data cost effectively.

That massive amount of data is also going to allow us to better train the current models and create new ones. The more data you have, the better you can do ML and potentially deep learning.

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Lastly, we need to think about new insights that we can’t create today. That’s going to give us the greatest opportunity, when we take the data we have today and use it in new and creative ways to give us better insights, to make better decisions, and to increase health and safety. Now we can take all of the data from the sensors and videos and cross-correlate that with weather data, for example, and other types of data, such as supply chain data, and incorporate that into enabling and empowering the salespeople, to negotiate better contracts, et cetera.

So, again, the art of the possible starts to manifest itself as we get more and more data from more and more sources. I’m very excited about it.

Gardner: What advice do you have for those just beginning similar IoT projects? 

Galanski: I recommend that they have somebody lead the group. You can try and flip through the catalogs and find the best vendors who have the best widgets and start talking to them and bring them on board. But that’s not necessarily going to get you to an end game. You are going to have to step back, understand your customer, and come up with a holistic approach of how to assign responsibilities and specific tasks, and get that organized and scheduled. 

There are a lot of parties and a lot of pieces on this chess table. Keeping them all moving in the right direction and at a cadence that people can handle is important. And I think having one contractor, or a department head in charge, is quite valuable.

Salinas: You should rent a party bus. And what I mean by that is when we first began our journey, actually our first lecture, our first step onto the learning curve about IoT, was when Texmark rented a party bus and put about 13 employees on it and we took a field trip to the HPE Innovation Lab.

When Doug Smith, our CEO, and I were invited to visit that lab we decided to bring a handful of employees to go see what this IoT thing was all about. That was the best thing we ever could have done, because the excitement was built from the beginning.

They saw, as we saw, the art of the possible at the HPE IoT Lab, and the ride home on that bus was exciting. They had ideas. They didn’t even know where to begin. The buy-in was there from the beginning. 

They saw, as we say, the art of the possible at the HPE IoT Lab, and the ride home on that bus was exciting. They had ideas. They didn’t even know where to begin, but they had ideas just from what they had seen and learned in a two-hour tour about what we could do at Texmark right away. So the engagement, the buy-in was there from the beginning, and I have to say that was probably one of the best moves we have made to ensure the success of this project.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: Hewlett Packard Enterprise. 

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About Dana Gardner

Dana Gardner is president and principal analyst at Interarbor Solutions, an enterprise IT analysis, market research, and consulting firm. Gardner, a leading identifier of software and cloud productivity trends and new IT business growth opportunities, honed his skills and refined his insights as an industry analyst, pundit, and news editor covering the emerging software development and enterprise infrastructure arenas for the last 18 years. Gardner tracks and analyzes a critical set of enterprise software technologies and business development issues: Cloud computing, hybrid IT, software-defined data center, IT productivity, multicloud, AI, ML, and intelligent enterprise. His specific interests include social media, cloud standards and security, as well as integrated marketing technologies and techniques. Gardner is a former senior analyst at Yankee Group and Aberdeen Group, and a former editor-at-large and founding online news editor at InfoWorld. He is a former news editor at IDG News Service, Digital News & Review, and Design News.
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