Bühler: Qlaire

Enhance Quality Management with generative AI

Started
January 1, 2024
Status
Completed
Share this project

Abstract

Bühler is a leading global provider of industrial processing technologies for food, grains, and advanced materials. The Bühler brand stands for high quality. Quality issues have the potential to rapidly erode trust with significant financial and reputational losses. Hence, quality has always been a top priority for Bühler. Bühler has recorded quality issues in the form of structured (tabular) and unstructured (textual) data over the years, creating a valuable source of knowledge and a potential goldmine of valuable feedback.

Accessing textual information is particularly challenging due to the high volume of records and the variety of languages, among other factors. Through the in-house tool called Qlaire, Bühler aims to enable its global quality teams to leverage recent generative AI technologies and access valuable insights at unprecedented speed and quality.

People

Collaborators

SDSC Team:
Ivan-Daniel Sievering
Roberto Castello

PI | Partners:

Buehler Group: 

Dr. Matthias Graeber, Head of Data Science

Dr. Juergen Auge, Head of Quality & Compliance

description

Objectives

Qlaire is an AI-powered insights engine for quality issues in manufacturing. Working together with the Swiss Data Science Center (SDSC), Bühler’s Quality & Compliance team wanted to implement advanced linguistic tools to help internal experts to rapidly and more effectively analyze issues contained in textual reports. To this end, Natural Language Processing (NLP) and Large Language Models (LLMs) were utilized.

Within Qlaire, a data pipeline processes the issue dataset by cleaning and enhancing it. It extracts key information from texts (e.g., machine names), automatically translates texts to English, and summarizes each issue into a concise text. Four tools were made available via an intuitive WebApp:

·  Overview tool: to offer a quick glance at relevant information about an issue (summary, answers to predefined questions, etc.), speeding up expert decision-making.

·  Insights tool: to compile common concerns (like the machine's frequent issues), helping experts identify problems for further investigation.

·  Q&A tool: to answer experts' questions (citing relevant issues for explainability), aiding experts in their analyses.

·  Similarity tool: to identify similar issues, which may unveil existing solutions.

‍

Figure: The issues are stored in an enhanced database, which Qlaire uses to assist experts in analysis, saving time and money.

Benefits

Qlaire enables Bühler's quality experts to rapidly access knowledge from issues texts. This leads to faster resolution of issues, easier retrieval of existing solutions, more efficient identification of quality hotspots, and a deeper understanding of quality concerns. The result is dramatically improved quality management processes with real-time analysis, saving time and money and supporting Bühler's reputation in quality excellence.

Collaboration

This project highlights the continued fruitful partnership between Bühler and the Swiss Data Science Center since 2018. In a previous collaboration a widely adopted solution, MontBlanc, was developed together to reduce carbon emissions associated with the high energy demand of malting processes. This product is currently available to Bühler’s customers. As a follow-up to this impactful project, now Qlaire enables the quality teams at Bühler to incorporate text analytics into their quality management processes.

Notes

Special thanks go to Matthias GRAEBER, Head of Data Science, and Juergen AUGE, Head of Quality & Compliance at Bühler, for their trust, support, and guidance throughout the project. The front-end Web application was built with the support of Arcanite.

‍

Gallery

Image Reference:

Cover image: Many digital journeys start with an analog mapping exercise (image source: Daria Nepriakhina, Unsplash).

Annexe

Additional resources

Bibliography

Publications

Related Pages

More projects

IICU National Data Stream

In Progress
Personalized, data-driven prediction and assessment of infection-related outcomes in Swiss intensive care units (ICUs)
Academia
Public sector

SMARTT

In Progress
Smart sampling for small-angle x-ray scattering Tensor Tomography
Academia

TGSF-DA

In Progress
Data Analysis of the Turbulence and Gravity roles in Stellar Formation
Academia

MOBIKO

In Progress
Mountain Biodiversity Knowledge Graph
Academia

More projects

No results found.
There are no results with this criteria. Try changing your search.
No result

News

Latest news

Elevating International Geneva's Impact with AI
October 21, 2026

Elevating International Geneva's Impact with AI

Elevating International Geneva's Impact with AI

Two AI projects have been selected for funding through the 2026 Geneva AI Initiative, run by the EPFL AI Center with the SDSC.
12 Zurich SMEs join next AI Innovation Program
October 15, 2026

12 Zurich SMEs join next AI Innovation Program

12 Zurich SMEs join next AI Innovation Program

Strong results encourage further AI exploration to simplify operations and boost the competitiveness of SMEs in the Canton of Zurich.
La science des données au service de la neutralité carbone du canton : ENERBAT ouvre la voie
September 17, 2026

La science des données au service de la neutralité carbone du canton : ENERBAT ouvre la voie

La science des données au service de la neutralité carbone du canton : ENERBAT ouvre la voie

News release : ENERBAT, un outil fondé sur les données soutient la politique de rénovation des bâtiments du Canton de Vaud.

Contact us

Would you like to explore how we can work together?

Our team of data scientists and professionals looks forward to engaging in impactful, results-driven collaborations with you.