Automatic Engine Component Detection with MTU

Automatic identification of engine components to save maintenance time and reduce costs for spare parts by enabling the reuse of components.

Client
MTU Aero Engines
Expertise
AI & Data

"I truly value the professional and interdisciplinary collaboration with Motius, especially their flat hierarchies. Over the years we have developed a very amicable work mode."

Steffen Claus
Process Engineer @MTU
The Outcome

Our Final Result

Overview

Team Size
Maturity Level

Challenge

Solution

Technologies

Impact

The Outcome

Our Final Result

Result

On average, the identification time of machine parts was reduced by 30%. Furthermore, the reliable classification of expensive precision machine parts allows their reuse, reducing the costs for spare parts.

95%
Top-1 Accuracy

Proven 30% Faster Identification of Engine Components

  • Targeted process duration reduction of 50% can be achieved with further code and interface development
  • We improved the algorithm, partially achieving 95% top-1 accuracy, and scaled the software.
  • Less new spare parts are needed, due to reliable component classification
  • MTU patent application (WO2022/237930A1)

A solid business case and the successful implementation in production has led to a long-term collaboration between MTU and Motius. Currently we are exploring the adaptation of the use case in other MTU business units and developing further features.

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Challenge

During maintenance, the entire aircraft engine is disassembled, and all essential components are recorded. To shorten this time-consuming process and free up valuable time for skilled workers, MTU aimed to (partially) automate the process.

Tedious and Time-Consuming Engine Components Classification

Aircraft engines on average are composed of more than 300 parts. These high-precision machine parts are costly, often very small and many of them look almost identical. Thus, their classification requires a lot of time and needs to be done by skilled experts.

Solution

Motius developed a computer vision solution combined with a box containing multiple cameras to ensure optimal lighting conditions. A dashboard presents the user with a sample image of the recognized machine part.

Overview

All About MTU Aero Engines

Germany’s Leading Engine Manufacturer

MTU Aero Engines is an expert in the development, manufacturing, and maintenance of civil and military engines across all thrust and performance categories, as well as stationary industrial gas turbines. Their innovative propulsion systems, high-tech solutions, and comprehensive services enhance aviation efficiency, safety, and sustainability. In the field of civil maintenance, MTU Maintenance ranks among the top 3 global providers for civil aviation propulsion systems and industrial gas turbines.

The Process

Tackling the Challenge in a Four-Step Process

POC & Prototype

To see if the concept is feasible, we started with a simple, wooden PoC, with only 50 components, 4 cameras, and a scale. The performance was around 70%, which showed that the concept works, but needed more improvement. We came up with a more elaborate prototype that had better hardware and implemented faster software for quicker detection results.

MVP

For the MVP we increased the size of the detection box, so it can be used with bigger components as well. The design stayed similar, so it is compatible with the older, smaller prototype.

Iteration

To ensure user acceptance of the released MVP, we conducted UX interviews and integrated the feedback. This resulted in faster software, better cameras, and a new distance sensor that can differentiate in the nanometer range. For better usability we centralized the data storage and minimized the cold-start issue by using the same ML model on each device.

Rollout and Optimization

As the MVP has been improved and significantly shortened maintenance time, the product was rolled out to all MTU locations. For better scalability, we further optimized up-time and reliability.