Tag: Smart Maintenance

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:

  • Big Data & AI Technologies
  • Data Sharing & Visualisation
  • Digital Health
  • Natural Language Processing
  • Smart Maintenance

Detailed Program:

Big Data & AI Technologies
More information will follow soon!

Data Sharing & Visualisation
More information will follow soon!

Digital Health
More information will follow soon!

Natural Language Processing
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.
What new opportunities are there? What limitations and pitfalls should we be aware of?
We are looking forward to exchanging opinions, experiences and questions, and to exploring this exciting field together!

Smart Maintenance
More information will follow soon

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.

Operational ML for Service Engineers: Successes and Pitfalls

By Lilach Goren Huber, Thomas Palmé, Manuel Arias Chao (all ZHAW), Maik Hadorn, Roche

Smart Maintenance Expert Group Meeting 20.01.2022

Once more, we met online for an interesting presentation followed by vivid discussions and networking. Yes, online networking!

We started by proudly introducing our new industrial Lead: Dr. Maik Hadorn, International Product Manager, from Roche Diagnostics. Welcome Maik, we are honored to profit from your expertise!

Next, Niels Uitterdijk, the CTO and founder of Amplo exposed us not only to success stories but also to challenges and pitfalls on the way to successful machine-learning-based predictive maintenance. As usual in our EG, this included concrete use case examples, this time from several different application fields.

After an intense Q&A session (we were 29 attendees!) we switched from Zoom to Wonder, where we had the chance to meet and network with group members. Similarly to previous meetings of our EG, this worked out really well!

We look forward to the next meeting – this time, finally, face to face.

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

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