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Schlagwort: Smart Maintenance

Smart Maintenance Insights – Online Session

Am 27. April 2023 laden wir Sie sehr herzlich zu unseren Smart Maintenance Insights ein.

In Zusammenarbeit mit der data innovation alliance veranstaltet Easyfairs zum dritten Mal einen Online-Event kostenfrei.

Rund um das Fokusthema „Was bleibt nach dem Hype: Reale Smart Maintenance cases in der Umsetzung“, erwarten Sie zwei hochwertige Referate, welche Wissenschaft und Praxis zusammenbringen.

Bringen Sie sich auf das smarte Level und reservieren Sie sich einen kostenlosen Platz an unserer Online-Session vom 27. April 2023 von 10:00 – 11:00 Uhr.

Expert Day

We invite you to the second iteration of the Expert Day. Join us in an exchange of expertise and find inspiration. These following groups will participate:

  • Natural Language Processing & Big Data Technologies
  • Smart Maintenance
  • Smart Services
  • Spatial Data Analytics

Detailed Program:

15:00 – Welcome
15:30 – Keynote by Prof. Pierre Dersin
16:10 – Expert Group Meetings in breakout rooms (see below)
17:40 – Apéro

Data-driven Value Added for Words, Images and Things

Digital transformation is a defining feature of our epoch.

Abundance of data, immense increase in hardware processing capabilities and breakthroughs in analytics algorithms have made practical some of the visions put forward about three quarters of a century ago. The branch of Artificial Intelligence called Machine Learning, and in particular Deep Learning, permeates image processing, natural language processing ( “ words”) and smart maintenance (‚things‘), and furthermore enables rich synergies between those three fields, which span a great deal of human activity, with profound potential impacts—some already visible, on industry, science, the arts and social life.

Natural Language Processing & Big Data Technologies

Everyone is talking about ChatGPT these days and some of its output is truly impressive! We will discuss how the most recent wave of text generation algorithms can transform business, science and teaching. The meeting will feature the following expert talks:

Grounded Copywriting with ChatGPT & Co
by Michael Wechner (Wyona AG) + Colin Carter (Coop Rechtsschutz)
Everyone talks about the pros and cons of ChatGPT, its competitors and how to combine the generated text with grounded knowledge. We will demonstrate how ChatGPT & Co can be applied in insurance and discuss the future of retrieval augmented language models.

Can we Identify Machine-Generated Text? An Overview of Current Approaches
by Anastassia Shaitarova (UZH Institute for Computational Linguistics)

The detection of machine-generated text has become increasingly important due to the prevalence of automated content generation and its potential for misuse. In this talk, we will discuss the motivation for automatic detection of generated text. We will present the currently available methods, including feature-based classification as a „first line-of-defense.“ We will provide an overview of the detection tools that have been made available so far and discuss their limitations. Finally, we will reflect on some open problems associated with the automatic discrimination of generated texts.

Using AI to Query the Football World Cup Database in Natural Language
by Kurt Stockinger (ZHAW Institute for Applied Information Technology)

Football is one of the most popular sports on earth with millions of people watching the FIFA world cup. In this talk, we describe how we built a system to query the world cup database in natural language. We explain how we translate natural language into the database query language SQL using modern transformer architecture. We also demonstrate how we have used large language models such as Open AI’s GPT-3 and Google’s T5 to explain how the system interprets users’ questions.

We are looking forward to exchanging opinions, experiences and questions, and to exploring this exciting field together!

Smart Maintenance

The value of condition monitoring data: 5 use cases. 

In this meeting of the Smart Maintenance Expert Group we will hear about successful student projects conducted together with industry partners from various fields. The focus points of the projects are very diverse, ranging from prediction of energy losses, through anomaly detection, fault diagnostics, prediction of the remaining useful life and optimal maintenance scheduling.  We will have 5 short pitch presentations, followed by an interactive discussion of future interest topics of our expert group, including active feedback of all participants.

  • Anomaly Detection in Marine Engines with Convolutional Neural Networks (Company: WinGD)
  • Aircraft Scheduling Optimization based on Prognostics Degradation Models (Company: Swiss International Airlines)
  • Modeling Wake Energy Losses in Wind Farms using Graph Neural Networks (Company: Fluence Energy)
  • Using Error Code Patterns to Predict Service Requests on Production Machines with Machine Learning (Company: Zünd Systemtechnik).
  • Fault Detection in Solar Power Plants using Physics Informed Deep Learning (Company: Fluence Energy)

Smart services for sustainability – circular servitization

With data-driven services, industrial companies can create quantifiable value for their customers, partners and themselves. At the same time, these services also have the potential for ecological benefits, e.g., through optimized processes in operations or logistics. To make this possible, economic and ecological goals must be captured in a targeted and combined manner when designing the services.

The 1.5-hour workshop will discuss how specific problems from everyday business can be systematically addressed to create relevant added value for business and ecology. Participants will bring their own business issue and leave the workshop with a first approach on how to create economic and environmental value through smart services. The workshop will run through typical phases of a project in a compressed time format to give an impression of what such a project might look like on a larger scale.

Spatial Data Analytics

High-quality spatial data is increasingly available for free use. However, with the large amount of data and the sometimes very specific data types and formats, it is challenging to find the appropriate data sources. In addition, some of the data access platforms are only partially intuitive and can be used without expert knowledge. Accordingly, the question arises whether the full potential of the available data base could not be better exploited if data access and data sharing were simplified. In this co-creation workshop, concepts and approaches will be reflected and discussed with representatives from research and industry as well as from cantonal and federal agencies, with the aim of developing possible approaches for joint implementation.

PUBLIC EVENT: Expert Group Meeting – Smart Maintenance Webinar

Dear Colleagues

We would like to invite you to a special “End of the Year” webinar on Friday 16.12.2022 at 14:30. We are delighted to have Dr. Gabriel Michau as our speaker, telling about his research work titled:

Whispering machines: Deep Learning for viable Condition Based Maintenance

Which was recently published in the highly prestigious journal PNAS. The talk description can be found here: Link.

The Speaker: Dr. Gabriel Michau is leading the development of Data-Driven maintenance solutions at Stadler Service AG, piloting end-to-end data-driven projects, from identifying the sensing technology to the optimisation of the existing maintenance strategies. He specialised in the development of innovative deep learning algorithms for the processing of industrial data as Senior Scientist at the ETH Zürich, in the Chair of Intelligent Maintenance Systems. At the ZHAW, he worked on several innovation projects with industrial partners to develop machine learning solutions to specific problems met by the industries. Gabriel holds a joint PhD between the Ecole Normale Supérieure de Lyon, in Physics, specialised in convex optimisation and the Queensland University of Technology in Brisbane, in Traffic Engineering.

You can use the following link to join the webinar: Microsoft Teams Meeting

We hope to see you all there!

Best Regards

Maik, Manuel, Thomas and Lilach,

The Smart Maintenance Expert Group.

Smart Maintenance Insights

Am 02. Juni 2022 laden wir Sie sehr herzlich zu unserer Online-Session „smart maintenance insights“ ein.

In Zusammenarbeit mit data innovation alliance veranstaltet Easyfairs zum ersten Mal die smart maintenance insights kostenfrei per MS Teams.

Rund um die Fokusthemen Predictive Maintenance und Predictive Quality erwarten Sie am Donnerstag, den 02. Juni 2022, zwei hochwertige Referate, welche die Wissenschaft und die Praxis zusammenbringen.

Melden Sie sich an unter maintenance-schweiz.ch mit dem Registrierungscode 250.
Wir freuen uns auf Ihre Anmeldung!

Service Event: “Lernen, Netzwerken”

Organized by the Smart Services and Smart Maintenance Expert Groups

Showcase Kistler & Digitalization

In this afternoon event, we will introduce the digitalization initiatives of Kistler and then focus on the digital service initiatives with a focus on pilot projects in various fields of advanced services. The event will be rounded off with a presentation of a turn-key solution by Kistler innovation lab and digital hub, followed by a tour around the company and apéro.

Please register at: https://ch.xing-events.com/digitalization_and_service
Number of places limited
You can also find all relevant information in the flyer!

ONLINE – Expert Group Meeting – Smart Maintenance

We are pleased to invite you to our next meeting of the Smart Maintenance Expert Group. The meeting will take place online.

Thomas Wuhrmann from Kistler Instrumente AG will talk about

Machine Learning based Cause of Failure Analysis in Injection Molding & Metal Machining

In industrial manufacturing processes, the most important tasks are usually concerned with an improvement of the quality outcome, a reduction of waste and an improvement of the process stability. This applies specifically to injection molding and metal machining with a turning lathe. Injection molding is the state-of-the-art process to produce plastic parts in different shapes and sizes. Machining on the turning lathe allows to perform highest precision process steps on expensive raw materials using specialized cutting tools. In both applications, machine learning allows to harness the process information more effectively to improve the yield of in-specification parts and understanding the quality-determining process mechanisms. In this talk Kistler approaches to implement solutions to realize this in both applications will be presented. In both applications, the insights obtained by machine learning, though different in nature, allow a reduction of waste. In both fields, further investigations are aimed to generalize these models and fully integrate them into the corresponding process automation and control.

Program

14:30-14:45 An Introduction Round.
14:45-15:30 ML based Cause of Failure Analysis in Injection Molding & Metal Machining (Thomas Wuhrmann, Kistler Instrumente AG).
15:30-16:30 Networking on “Wonder”.

Registration

Please register to the meeting using the form below. For questions you are welcome to contact us directly through lilach.gorenhuber@zhaw.ch or palm@zhaw.ch

Looking forward to meeting you,
Maik, Thomas, Manuel and Lilach.

ONLINE – Expert Group Meeting – Smart Maintenance

We are pleased to invite you to open 2022 with a meeting of the “Smart Maintenance Expert Group”. The meeting will take place online on 20 January 2022 at 14:30.

Niels Uitterdijk from Amplo GmbH will talk about
Successes and pitfalls on the road to a generic, operational machine learning platform for service engineers

Industrial machine manufacturers have heavily invested in IoT infrastructures in the last decade, yet tools that extract actionable insights remain illusive. To drastically reduce the maintenance costs and data analysis efforts, Amplo developed a smart maintenance platform which gives service engineers themselves access to state of the art operational machine learning systems that are deployable without any code or machine learning expertise. Currently, the platform provides models that diagnose failures, analyse production quality and monitor machine performance. 

The benefits are clear. Tritium avoids hours of data analysis and enjoys automated root cause analysis, allowing them to instantly send out repair orders. Solarmanager is able to notify thousands of homeowners when their PV panels are underperforming. TB Safety now services their filters only when necessary, instead of inspecting them every year.

Program

14:30 – 14:45 An introduction round
14:45 – 15:30 Successes and pitfalls on the road to a generic, operational machine learning platform for service engineers
15:30 – 16:30 Networking on “Wonder”

Registration

Please register to the meeting using the form below. For questions you are welcome to contact us directly through lilach.gorenhuber@zhaw.ch or palm@zhaw.ch

Looking forward to meeting you,
Maik, Thomas, Manuel and Lilach