The average capital project today is delivered 80pc over budget and 20 months late, according to US research consortium the Construction Industry Institute (CII). These overages can dramatically impact the financial viability of a project and put investments such as ExxonMobil’s proposed carbon capture hub—with an estimated price tag of $100bn—under immense pressure to minimise project risk by maximising predictability.

CII research also says that, within a typical capex project, procurement and construction make up 80pc of the costs, while engineering represents only 10pc. Considering this, is it logical to focus on your engineering technologies and workflows to address budget overages?

The answer is unexpectedly, yes. Why? Because the engineering and design phase is where design errors take place, and their impact can be catastrophic to the entire project.

Problem: Engineers waste up to 50pc of their time looking for and validating engineering information. This slows capital project progress and drives up the risk of errors, rework and further cost and schedule escalations that result in late and over-budget projects.

The industry has made headwinds in addressing common project inefficiencies through increased adoption of collaborative practices such as advanced work packaging, collaborative contracting and scheduling, and integrated project delivery. However, without addressing the challenge of siloed teams and disconnected technologies and workflows, these practices can leave teams swimming in a pool of unstructured, messy data that may cause more problems than it solves.

50pc of engineers’ time is wasted validating information

Solution: Create a single source of truth that all project teams can access and trust to make decisions and act upon them.

To keep a competitive edge, owner-operators and engineering, procurement and construction companies must drop their manual tracking processes and adopt one unified, integrated, data-centric system that can autonomously flag updated information and store it in one place for consistency. A data-centric approach allows for everyone working on the project to see what is going on. Everyone sees the same real-time information so they can easily locate the right data to make confident decisions and take action.

The more integrated your data is, the better

Future-focused companies are adopting new ways to leverage their data by unifying the entire simulation process and engineering and design workflow within one single, cloud-based environment.

When all engineering disciplines can compile, view, share and manage all their data within one central location, the value is tenfold. Process simulation can be used to test a variety of design iterations for optimal sustainability and operational efficiency, downstream effects of design changes can be considered across all engineering disciplines in a matter of minutes, and design clashes are easily identified and mitigated far before they are noticed onsite.

A critical step in any digital twin journey

A data-centric engineering approach empowers the complete project execution process—from concept to completion—and creates high-quality, trusted engineering information management, the primary building block to any effective digital twin strategy.

A clear, validated view of your engineering information tells you everything you need to know about your plant’s physical make up—from how it was designed to how it stands today (which may or may not be the same). It can then be layered with machine-learning and AI mechanisms to contextualise, and even visualise, the model with behaviour over time, effectively becoming a living, breathing digital twin of your plant.

Digital twins are critical for building the plant of the future, which is designed and executed predictably, operating efficiently and sustainably thanks to the insights provided at all stages of the asset lifecycle.

Do not forget about the Cloud

To maximise the value of your integrated, data-centric engineering efforts, consider deploying on the Cloud. Cloud deployment further democratises your data and turns it into intelligent, actionable information available at the fingertips of those who need it.

And storing and maintaining engineering data in the Cloud allows engineers to work on their projects both in the office or from remote locations for business continuity reassurance across a global workforce. It also reduces reliance on internal IT teams and infrastructure by allowing you to match deployment and licensing to your needs as the project progresses or your business needs change.

The bottom line

By delivering your project using data-centric engineering in a single environment, ideally on the Cloud, you can reduce rework and time wasted verifying information in engineering and design, while also unlocking the ability to leverage that information to make decisions you can trust at later stages of the project.

These insights not only drive up engineering efficiency and generously augment the productivity gains from collaborative best practices in project execution, they also power a digital twin strategy to enhance connectivity, reporting and asset visualisation for rapid, confident decision-making far beyond the project phase of the asset lifecycle.

How can you get started? Read our whitepaper, Breaking Down the Silos between FEED and Detailed Design, to learn more.

Vanessa Erickson is a capital project portfolio expert at AVEVA



{{ error }}
{{ comment.comment.Name }} • {{ comment.timeAgo }}
{{ comment.comment.Text }}