The Intelligent Maintenance Conference is an international event on new diagnostic and intelligent monitoring methods for industrial systems! Our objective is to be a place to share fruitful discussions on predictive maintenance between experts from the industry and the academic world. Renowned speakers from varied backgrounds, including railway, healthcare, energy, and chemical industries, academics, and others, will be present.

We are excited to announce that, for the first time, the 8th Intelligent Maintenance Conference will include a dedicated 1-day workshop on the latest advancements and practical applications of artificial intelligence in maintenance technology.

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involves different data types. If not just the detection of a fault is required--> but also the ability to distinguish between different fault types, unsupervised--> methods are not sufficient and supervised methods not only suffer from imbalance--> but also specialize on faults that have been already observed before. Given the--> rarity of faults, it is unrealistic to assume that all fault types have been--> observed within a short period of time during training dataset observation--> period. However, we typically can assume that domain have knowledge on the--> expected fault types (e.g. through a failure mode and effect analysis).--> Recently, the introduction of Large Language Models (LLMs) has opened new--> possibilities across various domains, including industrial operation and--> maintenance. This progress enables integration of semantic domain expert--> knowledge to anticipate and describe possible anomalies and faults also for new--> fault types that have not been observed before. Leveraging the expertise--> knowledge, our recent work proposes a novel approach to transform expert--> descriptions of fault types into guidance for realistic anomaly generation. By--> combining LLMs and diffusion models, we are able to generate realistic, diverse--> and semantically meaningful anomaly samples. By doing so, we not only enhance--> the interpretability of generated anomalies but also improve the performance of--> downstream anomaly detection tasks. This talk will give insights in our proposed--> framework, showcasing its advantages over traditional unsupervised anomaly--> detection and generation techniques. Furthermore, it will discuss the potential--> of LLMs for enhancing industrial fault detection, highlighting their promising--> performance in generic anomaly generation and understanding.-->

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IMC Hands-on Workshop

Join us at the 8th Intelligent Maintenance Conference for the interactive IMC Hands-on Workshop (IMC HOW?). We are excited to announce that, for the first time, the 8th Intelligent Maintenance Conference will include a dedicated 1-day workshop on the latest advancements and practical applications of artificial intelligence in maintenance technology. The workshop will cover the following topics:

The Power of Graph Neural Networks: A Comprehensive Introduction and Industrial Applications

Given by Mengjie Zhao and Raffael Theiler

IMOS, EPFL

Description

Graph Neural Networks (GNNs) offer a powerful way to analyze complex assets and systems. They have been applied to a wide range of industrial applications, from the analysis of individual components such as bearings or turbofan engines to condition monitoring of large-scale interconnected systems such as power plants, distributed heating networks or energy distribution networks. In this workshop, we start by exploring the theoretical basics of how Graph Neural Networks (GNNs) facilitate learning in data that is structured as entities and their relationships. Then we'll apply GNNs to industrial applications that benefit from this relational interpretation of the data and learn how GNNs enable model generalization to unseen environments. The workshop includes a comprehensive introduction to GNNs followed by a hands-on tutorial using an industrial dataset, giving you direct guidance in applying these techniques to solve practical problems.

Mastering Domain Adaptation in Deep Learning: A Practical Workshop

Given by Han Sun

IMOS, EPFL

Description

In the dynamic field of Deep Learning (DL), the ability to adapt models to new, unseen domains is crucial for achieving robust and generalizable performance across a wide range of applications. Designed for practitioners and researchers with a basic understanding of deep learning, this hands-on workshop is designed to introduce participants to the concept and techniques of domain adaptation in DL, providing them with the practical skills and knowledge needed to navigate and implement these strategies effectively.

Understanding your Deep Learning Models with Explainable AI

Given by Dr. Florent Forest

IMOS, EPFL

Description

This workshop offers a practical introduction to various eXplainable artificial intelligence (XAI) tools that can be leveraged, on the one hand, to explain the decisions of already trained deep neural networks, or on the other hand, to make their architecture inherently more interpretable, with the ultimate goal of increasing trust and acceptance of AI-based systems. During this workshop, you will have the occasion to open the black-box of several models in industry-relevant applications.

Prerequisites:

Beginner to intermediate experience in Python.
A basic understanding of deep learning, basic knowledge of data science, and time series analysis will be helpful for understanding the theoretical background.
A laptop with a stable internet connection and a Gmail account to be able to follow along during the hands-on sessions in Google Colab.

Registration

It is possible to book tickets for a single conference day.

STANDARD

CHF 500 / 2 days

Standard Ticket

Access to all sessions

Free Apéro

Register Now

STUDENT

CHF 50 / 2 days

Basic Ticket

Access to all sessions

Free Coffee

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WORKSHOP^*

CHF 200

Basic Ticket

Access to all sessions

Register Now

WORKSHOP^* STUDENT

CHF 100

Basic Ticket

Access to all sessions

Register Now

^*Students will be asked to show their student card at the conference and the workshop check-in. Workshop will take place only with enough attendees and is limited to maximum 30 attendees. You will be informed beginning of August if the event will take place. In case of cancellation, you will get reimbursed. Participants are asked to bring their own laptop to the workshop. Participants will receive an IMOS certificate of attendance on successful completion.

8th Intelligent Maintenance Conference