Digital transformation will enable new sustainability pathways

Our chemical and fuels sector recently set out three pathways that will enable the chemical sector to reduce its emissions and contribute to a more sustainable world: establishing alternative feedstocks, decarbonizing chemical processes, and developing new approaches to resource stewardship.

But these pathways are only made possible through the digital transformation of the chemical industry.

Getting the most out of digital takes more than retrofitting different technologies into the existing approach and data streams. We need to consider how and when the right digital technology is introduced to maximize value across all phases of an asset’s life. Not just achieving a small gain within a single phase. And we need to change the way we capture, store, and use data, and put it in the hands of the right people at the right time to get the most out of it.

A good example of a lifecycle approach is how a chemical’s carbon footprint, or its greenhouse gas (GHG) emissions are measured. We calculate this in a life cycle assessment, which accounts for all the emissions produced starting from resource extraction and feedstock use through manufacturing to transportation, disposal and reuse or recycle alternatives. Once we calculate those emissions and establish a baseline, we must think about how to bring those emissions down.

So how does this relate to the implementation of digital technology across the life of the asset?

Translating a lifecycle approach to capture value of digital

Digital enablement is already streamlining the engineering process of how we design and deliver large infrastructure. Artificial intelligence and machine learning has an important role in improving the quality of decision making and is enabling more autonomous ways of working. And other technologies like blockchain are also having a disruptive impact to contracts and supply chain management.

When we apply it correctly, through a value-based approach, digital technology can bring enormous value across the asset’s life. Take the example of digital twin technology.

A digital twin is an accurate digital representation of physical object or process. We use them every day with things like Google maps, interactive parcel tracking and online shopping. In recent times, you may have attended a virtual conference as a replacement for a physical event.

There are just as many potential applications of digital twins for the chemical industry. For example, predictive diagnostics of asset health helps to minimize downtime, accurate assessments of production forecasts enable better planning. And more effective plant navigation and remote working practices are enabled by technologies like 3D modelling and industrial internet of things (IIOT) devices.

But the full potential of a digital twin is only realized when we consider how data will travel across the life of the asset.

Reaping the rewards of a digital twin takes value-based thinking

The design and build phase of industrial facilities is often regarded separately from the operational phase. Here, the key motivation is to build a quality facility as quickly and cost effectively as possible. The purpose of twins for design and build is often limited to navigation of the asset, simulation of long-term production forecast and performance, or support for construction teams.

However, the greatest benefit of a digital twin is often realized in the operations phase. To improve maintenance strategy and execution, reduce costs, improve production, and reduce emissions.

These motivations are very different to those in the design and build phases. Yet, realizing these benefits in operations are highly dependent on the level of consideration and implementation of the digital twin in those earlier phases. But because the return on the investment needed to support effective operations is not realized during the design and build phase, this is often overlooked.

By the time the operations’ digital twin is implemented, much of the essential data that should be accumulated through design, build and the transition to operation phase, is lost. At best, this extends the time to realize a return on investment. At worst, it makes it impossible to use digital twins effectively in operations at all.

Perhaps it’s not surprising, given the traditional phased approach to asset development and operation. If digital twins are implemented in this way, it can create a narrow business case, restrictive commercial models and financial structures, and a risk of ineffective connectivity and integration across the asset’s value chain.

Shift a digital ambition into reality

While I use the digital twin as an example, I believe this is reflective of the challenges for digital transformation more generally. So how do we capture the maximum value for the asset, and deliver the most sustainable ways of working?

To address booming demand for chemicals and fuels, we have an opportunity to change the way we think about the integration of digital technology as new projects come online. From the earliest phase of a project, we must consider how data will travel across the life of the asset. That means widening our perspective and challenging working practices, commercial models, and interconnectivity and integrations across the value chain.

This shift in thinking could pave the way to capturing the true value of asset data, enable more efficient operations and help to accelerate emission reductions in the chemical sector. Only then will we maximize the potential of digital as the enabler.