Digital Energy Journal- AspenTech – integration, AI and full lifecycle optimisation

Join | Existing Member Login

You are Home » News » View Article

AspenTech – integration, AI and full lifecycle optimisation

Wednesday, February 28, 2024

Process software company AspenTech is improving data integration, developing AI for industry, and moving towards 'full lifecycle optimisation.' CEO Antonio Pietri explained

AspenTech, a company which provides software for the upstream and process industries, is working to improve its data integration capability, and developing industrial AI.

It sees both as a pathway to 'full lifecycle optimisation,' being able to optimise operation of an asset much more broadly, improving its environmental performance, and reporting emissions.

Antonio Pietri, president and CEO of AspenTech, explained, with a talk at the 'Emerson Exchange Virtual Edition 2023' broadcast on March 9.

Emerson, an automation and technology company, became a 55 per cent owner of AspenTech in a complex transaction in May 2022. Oil and gas subsurface readers may be interested to know that Paradigm Geophysical, acquired by Emerson in 2017, is now part of AspenTech's Subsurface Science and Engineering division.

Commenting on the Emerson transaction, Mr Pietri said, 'we wanted someone with a scale and capabilities of Emerson. Certainly the balance sheet, we wanted Emerson to help us make acquisitions. We wanted to diversify AspenTech into new industries. We wanted to reposition AspenTech around sustainability.'

Data integration

AspenTech recently announced the acquisition of Inmation, a data management and integration company from Germany, with about 50 employees.

Inmation has tools to integrate all kinds of data, including plant data in historians and enterprise software systems. It developed its capabilities with a goal of 'bringing order to data,' working together with two global chemical and pharmaceutical companies.

'This is the most forward thinking data management, data integration company in the industry,' he said. 'It will help you collect data, organise data, contextualise massive amounts of data,' and ultimately get a better understanding of your operation.

Mr Pietro warned that putting all of your data in a cloud based 'data lake' does not provide integrated data. A number of companies have been promoting the data lake idea. 'They're doing a wonderful job convincing all of you that its the way to go.'

'I've met with customers over the last year or two, what I'm hearing, now you have all this massive amounts of data in your data lakes, you don't know what to do with the data, you don't understand the data, you don't know how its related, the data is not of great quality, there's no context for that data,' he said. 'You're scratching your head about what to do.'

AI for industry

Already in 2015-2016, AspenTech could see that AI was a 'potentially disruptive technology,' Mr Pietro says.

AspenTech's background is on modelling industrial processes using first principles of engineering and science. 'AspenTech is rooted in first principles of engineering, the physics, the chemistry that rules the world,' he said.

But AI means modelling in a different way, using data itself.

The first thing to learn about industrial AI is that it can be very dangerous, if it is not done together with first principles of engineering, he said. 'AI doesn't understand physical constraints. You cannot train AI in your very complex industrial operations.'

So AspenTech has been developing ways to combine AI with domain expertise and first principles, 'to create a new generation of products that we call industrial AI.'

'This is a new generation of capabilities that AspenTech is introducing to the market, that leverage all the data that is now available with first principles, to create hybrid models which are most accurate and can drive greater value in your operations.'

Full lifecycle optimisation

The broader goal is to be able to optimise an asset over its 'full lifecycle', rather than just optimising specific processes or systems.

The work to optimise individual systems began in the late 1980s and 1990s, when AspenTech developed tools which could use data from process control systems to change operations. The systems could operate and optimise themselves, and the operators became supervisors of the technology.

'We believe we can go further than that, we are now working on the self optimising asset,' he said. This means 'closing the loop' on a wider process in a plant, including multiple units at once. We can 'create a plant that is self learning, self adapting, and self sustaining,' he said.

'We believe technology will be able to learn on a real time basis. It will be able to adapt and send signals to the plant or the engineer or operator, to take decisions, and be able to self-sustain,' he said.

This will be particularly helpful in improving reliability, identifying potential equipment failures, or process degeneration. The technologies can work together to predict future state, and future performance.

'This will not happen overnight, it's going to be 10, 15 years. [But] we believe that we need to get ourselves on a path to greater operational autonomy. The technologies exist today now to achieve that.'

Improving reliability 'is probably the biggest untapped value opportunity in your industrial assets,' he said.

Companies can use the capability to develop new business models which can drive profitability and sustainability, as a 'smart enterprise,' he said.

'Our strategy is about optimising across the full asset lifecycle to make operations safer, to make your assets more sustainable, more efficient, more optimum.'

'We help you push the boundaries of what's possible in the operation of your assets. We have customers pushing their facilities to 110 - 115 per cent of design capacity, through the use of our technology, our latest capabilities on asset performance management.'

Better outcomes

Digital technologies can help you achieve better operational and financial results, as well as better environmental performance, he said.

'You can drive greater efficiencies, consume less energy, reduce the waste of resources as you recycle more,' he said.

Meeting this challenge 'starts with the insight,' he said. 'If you have the insights you can make the right decisions. You have flexibility in your operations, the agility.'

As an example of how software can help, when the pandemic was declared and demand for some products dropped, one chemical operator's demand dropped to 60 per cent of their operating capacity. The chemical process was 'highly unstable', which meant it was very difficult to keep the facility running at this low capacity.

AspenTech's software, used to help operate the facility, was able to switch from 'economic optimisation' to 'stable optimisation', and keep the plant in operation, Mr Pietri said.

Another example is improving the efficiency of plastic recycling. AspenTech is developing new digital modelling tools which can be used in the processing of recycled plastic to make new products. It is also developing models for recycling electrical batteries, so more chemicals can be re-used.

The global chemicals demand is expected to grow 300 per cent by 2050, and better chemical recycling will be important in meeting this demand. It also needs to be done with a low environmental impact. 'We're working to remake the global economy in 30 years, it's a huge challenge,' he said.

In refining, AspenTech estimates that its customers gain $22bn in value a year from using the software, including from getting more throughput, better quality products, less energy consumption. They also reduce CO2 emissions by 16m metric tones.

Refining is a very complex and dangerous process with much technology involved. Its refinery customers are 'perhaps the biggest users of digital capability,' he said.

Some customers are purchasing software more for emissions management purposes than optimisation, he said. Emissions can be measured, tracked and reported using the software, and an audit trail developed.

'We need to work on those technologies we need to scale for the 2030s, 2040s, to make net zero emissions. That's hydrogen, carbon capture and storage, and biofuels, and eventually circularity around plastic waste.'

'The next 10 years is about efficiencies. The next 20-30 years is about a scaling of technologies, and eventually new business models that your companies have to put in place to retain the license to operate from society.'

'This is why AspenTech exists today and why Emerson took interest and invested.'

Background

AspenTech was founded in 1981 as a project in Massachusetts Institute of Technology (MIT) to design more energy efficient chemical plants, following the energy crisis of the 1970s.

It was a period where many facilities were been upgraded from pneumatic and analogue operations to digital systems, so there was an explosion of data.

'A new generation of entrepreneurs saw an opportunity to build on that data to create specific applications to take advantage of the value in that data,' he said. This included tools for advanced control, multi-variable control, planning and scheduling.

As a result, AspenTech was founded. 'We were a modelling and simulation company for 15 years.'

In the mid 1990s, AspenTech switched to being a process optimisation technology, and acquired 23 companies with the best technologies over the next 7 years.

In 2015, it switched to being an 'asset optimisation' company. 'We felt there was a bigger opportunity to move the company to the reliability and maintenance space,' he said.

Associated Companies
» AspenTech

CREATE A FREE MEMBERSHIP

To attend our free events, receive our newsletter, and receive the free colour Digital Energy Journal.