AspenTech

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Streamlining Plant Operations with Self Optimizing Dashboard

Combining predictive analytics and collaborative workflows for faster and more efficient plant management

Sector

Power & Engineering

Industrial

Service

Research & Sythesis

UX/UI

Design System

Plant Status

AspenTech and Narrative enable plant managers and operators to focus on the work that matters most

In 2021, AspenTech introduced a new approach to managing industrial facilities called the “Self Optimizing Plant.” This approach leverages vast amounts of data and utilizes advanced technology to gain production insights and make accurate predictions. This shift started because older plant managers—who have a deep understanding of how the machinery works—are retiring and the new managers replacing them are more familiar with technology and expect simpler tools. A symptom of this shift is the loss of valuable knowledge about how to predict and deal with unexpected problems.

To address this issue, Narrative helped AspenTech created a new system that helps plant managers and operators quickly identify and solve issues. This system combines data analysis and a user-friendly interface, enabling less experienced managers to easily understand what's going on and take action. The north star goal was to help plant management become faster and more efficient.

Dashboard

Challenge

Filling the gap of knowledge created by a retiring generation

Many experienced workers who have a deep understanding of how different machines work together and their unique characteristics are retiring, causing a shortage of knowledge in complicated manufacturing processes.

Business Value

A streamlined workflow reduces overhead and improves operations

AspenTech can provide an AI-based solution to help plant managers and operators quickly identify potential issues and take action. This will reduce the time and effort needed from front-line workers.

User Value

More time for the important work

Plant managers and operators save time and can focus on other important tasks, instead of spending time diagnosing and fixing problems.

Dashboard
Quote Mark

This is going to help the collaboration part of what we need to do. I can make decisions and do the work to move forward. That is the huge value of this. It’s all right here. Depending on what it is, this can take me a day or so to chase all this down depending on systems.”

Avatar

Plant Manager

Worker
Dashboard

AI-powered asset monitoring for plant operations and management

AspenTech envisioned a new offering: an asset management and alert system that decreased the time for front line plant managers and operators to identify a a risk and take the appropriate action. This solution would combine the power of predictive-analytics with a collaborative space that enables AspenTech’s AI to make recommendations based on historical data—ensuring plant managers and operators who lack this historical knowledge have the ability to see potentially catastrophic problems through the noise of daily operations.

With this revolutionary dashboard, AspenTech can provide valuable insights to plant managers and operators through a single source of truth and prioritize alerts (and groups of alerts) that require immediate adjustment in operations or planning for downtime and repair. This feature will help plant administrators more proactively adjust for disruptions in the production schedule, with the added benefit of reducing the time specialized engineers and maintenance personnel spend on diagnosing and making recommendations.

Dashboard

Ethnographic research paired with design improved collaboration

Our approach was rooted in the principles of qualitative ethnography and participatory design, engaging the individuals who directly use and maintain the application. This user-centered design process ensured that the end result was both effective and practical.

The rapid iteration of low-fidelity prototypes enhanced user testing at each stage, allowing the team to quickly identify and address breakdowns in the collaborative workflows across various manufacturing facilities. This iterative approach encouraged constant feedback and refinement, leading to a well-designed application that improved collaboration and streamlined processes.

We conducted interviews and user testing with alert responders, their managers, and their extended team members.

Faces

16

Participants

10

Hour-long discussions

4

Prototype iterations

20

Hour-long user testing sessions

Quote

The workflow has to be flexible enough to represent the true operations of that particular facility.

Exploration
Prototype

Front-end components for streamlined UI development

We designed a series of components and controls optimized for ease of use, visibility, and information hierarchy display. This UI elements became the base of a comprehensive design language system, one that can easily extend beyond this alerting tool into the rest of the AspenTech product portfolio.

Aspen Mtell© Recognized as

Best Digital Technology of the Year

Aspen Mtell© has received the “Best Digital Technology of the Year” award from the Latin American Refining Technology Conference.

AspenTech was recognized during the 2nd annual “Awards of Excellence” ceremony which celebrates notable achievements throughout the Latin American downstream industry.