Redesigned FMEA diagnosis software for world’s first civilian operated lunar mission

Designed and tested FLEUR(Fault List Evaluator), an FMEA system used in real-time IRIS Lunar Rover mission, achieving a 28% reduction of operator response time.

ROBOTICS | SPACETECH | USABILITY TESTING
Problem

Operators face low rates of accuracy in failure mode diagnoses.

Operators faced a systems knowledge gap, needing to memorize numerous FMEA documents and manually verify analyses. This hindered their ability to swiftly analyze faults, identify failure modes, and propose solutions during real-time missions.

Bottom Line Up Front

30% reduction in response time with the use of FLEUR.

Fault List Evaluator for Ultimate Response (FLEUR) is a software that lets users track indicators, explore possible failure modes and input solution suggestions. To streamline usability, I designed wireframes and prototypes, tested during mission simulations with scalability and interoperability perspectives.

IRIS Lunar Team with the nano - robot rover

Shot of IRIS Rover in space on the lander

Mission Control Room - Set up to operate the rover in mission

IRIS Lunar Team with the nano - robot rover

Mission

What is the IRIS Lunar Rover?

Iris is a 2kg rover exploring the Gruithuisen Domes, a part of the moon left untouched & never explored by both man or machine. It flew to space in January 2024 setting the tone for many firsts: world's first private rover, world's first nano robot, & most importantly, world's first student-operated rover mission.

Our team is an internationally diverse group of students, from all different majors across the university, who worked tirelessly over the last few years to create this miracle of micro miniaturization. Along with testing small, lightweight rover mobility on the Moon, Iris was designed to collect scientific images for geological sciences.

Articles
  • NASA.GOV ↗

    Former Intern Uses NASA to Lead Robotic Moon Rover

    As the first CubeRover to secure a flight to the Moon, Iris is an example of how NASA investments stimulate technology innovation.

  • IEE Spectrum↗

    New Moon Rover Gives It the Old College Try

    The United States’ first robotic lunar rover was built by Carnegie Mellon students.

  • SPACENEWS ↗

    Vulcan Centaur launches Peregrine lunar lander on inaugural mission

    United Launch Alliance’s Vulcan Centaur soared into night skies on its long-awaited first launch Jan. 8, carrying a commercial lunar lander.

My Role

Lead Product
Designer

Tools

Interactive prototyping,
UX Research, Product design,
Usability Testing

Team

2 Product Designers
4 Frontend Engineers
4 Backend Engineers

Background
Problem
Operators face low rates of accuracy in failure mode diagnoses.

Operators faced a systems knowledge gap, needing to memorize numerous FMEA documents and manually verify analyses. This hindered their ability to swiftly analyze faults, identify failure modes, and propose solutions during real-time missions. Our challenge is to create an easy-to-use interface that allows operators to easily administer the rover and identify correct failure modes throughout the mission within the limited time frame and reduce chances of errors.

SCOPE

How might we enable mission operators to efficiently diagnose and self-validate their actions intuitively ?

Challenge faced

Diagnosing failure modes currently requires using both an Excel spreadsheet (FMEA) and a Ground Software applet (Fault Tree), and these tools lack integration. FMEA provides criticality and risk scores, while the Fault Tree illustrates the relationship between indicators and failure modes.

Research
Investigating needs and priorities

I first analyzed the different tasks operators need to complete during the mission. We conducted contextual inquiry to understand what steps occur need to be taken with the rover, and what operators need to see and do to accomplish those tasks. We could immediately tell that he interface was not user-friendly for operators dealing with a large amount of data with a short time to make a decision.

We supplemented the interviews with an in-depth stakeholder study, as we knew that there is a system of operators who need to perform a collective effort to execute a final command for the rover. Conducting a journey mapping session with the different operator brought out the differences in the decision structure 3 primary stakeholders: Systems, navigation and Telemetry operators.

Research
Diving deeper into the context

While we continued interviewing operators, we also conducted secondary research to help further synthesize our findings. To understand the needs of operators:

  • We conducted interviews with the IRIS engineering team, that was developing the Telemetry software to learn about how this data was collected, and what edge cases were important to keep in mind while designing.
  • We carried out fly-on-the wall protocols for 10+ mission simulations, what the underlying issues with the current software are.
  • We researched design principles and usability practices for data-driven designs. Aiming to understand the methods visually designing the data to be communicated instantly.
Research
Key insights

Our synthesis of our research led is to the following insights:

  1. Recall rather than recognition with the FMEA data allowed for faster decisions made by operators.
  2. Delays occur due to a linear format for diagnoses vs an iterative approach for each use case.
  3. Navigation operators are interested in the details of each failure mode.
Research to Design
Opportunities

Using our insights we reframed our problem space to accurately address the needs of the operators, and leveraging the design opportunities.

Rescoping Design Oppurtunity

How might we reduce cognitive load on operators to reduce errors in failure mode diagnoses?

Design Opportunities:

  1. Communicate the criticality of the indicator through integration of the FMEA document and Fault Tree interactive data.
  2. Adding a friction point to cross-compare failure modes, allowing for a  non-linear decision process.
  3. Allow for state scanning within the indicators and failure modes to reduce cognitive load.
CHALLENGE

The impending launch date posed a challenge, necessitating an increased demand for the optimization of FLEUR within a limited timeframe.

As the launch date was approaching, we did not have the opportunity to create wireframes first and then move on to high-fidelity prototypes. Since there was a base to create a style guide, we simultaneously updated the style guide and jumped into the process of creating high-fidelity screens.

Design Process
Features Designed & Developed
Play with the prototype here ↗
Comprehensive Dashboard

Presenting the steps of the diagnoses and key pieces of information in a strict hierarchy that was intuitive for the operator to follow.

Comparison of failure modes

We optimized the friction point for operators by facilitating cross-comparison of failure modes. This allows users to recognize rather than recall, providing validation for their thinking and reducing errors.

Quick Scan - Connection between steps

To ease cognitive load, we enabled operators to quickly check the connection between failure modes, indicators, and their marked solutions.

Rover Machine Visualization

Supplementing the data with a visual representation of the rover, highlighting faulty parts, facilitates tracking new fault indicators and reduces response time to address faults.

Results
Impact on the rover mission
  • Qualitatively, operators expressed increased confidence in identifying the rover's state and a reduced sense of panic during the transition from diagnosis to resolution.
  • Quantitatively, the Quality Assurance engineer noted a 28% reduction in the operator response time during mission simulations.
Reflection
What I learned through this experience

Designing for a high stake situation, crafting experiences that are small in scale but monumental in impact. Working in Space technology, at the intersection of Human Computer interaction and Human Machine Interaction, was one area that I always want to practice my product design skills in, and IRIS gave me a first hand opportunity. I was able to develop my skills in evaluative user research, data-driven design, data visualization and getting stakeholders on board.

IRIS Lunar Team with the nano - robot rover

Shot of IRIS Rover in space on the lander

Mission Control Room - Set up to operate the rover in mission

IRIS Lunar Team with the nano - robot rover

I am grateful for the opportunity to be a part of the launch of the rover on the Peregrine Lander on January 8th 2024. IRIS’s legacy of ingenuity and unity lives on, inspiring future generations to reach for the moon and beyond!