Schlagwort: Smart Maintenance

Intelligent Maintenance symposium on “Asset Performance Services in Smart Buildings”

We are looking forward to hosting our third Intelligent Maintenance online symposium on 3 December at 2 pm CET with an exciting keynote presentation and lots of opportunities for discussions and exchange.

Please register for the symposium by sending a mail to Angela Meyer by November 27. You will receive a Zoom link one day before the event. We look forward to welcoming you at the symposium!

Speaker: Antoine Vandyck from Siemens Smart Infrastructure is discussing “Asset Performance Services in Smart Buildings”. Antoine is a product portfolio manager at Siemens in Zug where he is developing and delivering energy and asset performance services. He studied energy and process engineering and worked in facility management and building energy consulting for 8 years before joining Siemens in 2018.

Outline “Asset Performance Services in Smart Buildings”

Every asset in a building is transmitting its exact status. Analysis with the right tools by building performance experts allows to predict issues and resolve them before they turn into problems or fix existing ones faster. The starting point for smart building performance management is comprehensive expertise that allows to bring three distinct types of operational data from buildings together:

Maintenance data, typically sourced from computerized maintenance management systems
Asset data, including the make and model of installed equipment, required parts and service schedules
Performance data, such as comfort readings, energy consumption and CO2 emissions

Once these data sets are brought together, they are evaluated with rules and algorithms. A crucial collaboration between customers, facility manager and building experts is the last and the more important piece of the process to achieve our three key goals: Energy efficiency, maintenance efficiency, and operational performance. All of this results in increasing comfort, reducing risks and reduced costs.

Expert Group Event – Smart Maintenance Webinar

Webinar 28.08.2020

Program:

14.00 Welcome

14.10 Florian Pitschi, Swisscom: Condition Monitoring at Meier Tobler – An IoT journey of a Swiss company

Meier Tobler is a Swiss company selling heating and cooling systems. Together with Swisscom, they started their IoT journey more than three years ago. Florian Pitschi will explain why they started the journey, where Meier Tobler are now, showing different components of the employed solution in the different IoT layers  from PLC data extraction, device management up to condition monitoring, and some possible next steps.

Florian Pitschi holds a Master’s degree in information technology from the University of Ulm and accomplished a doctorate in computational biology in Shanghai on a Max Planck scholarship. Florian has been working as a data solution architect at Swisscom since 2015.

Florian Pitschi holds a Master’s degree in information technology from the University of Ulm and accomplished a doctorate in computational biology in Shanghai on a Max Planck scholarship. Florian has been working as a data solution architect at Swisscom since 2015.

14.35 Jianwen Meng, Université Paris-Sud: Lithium-ion battery monitoring and fault diagnosis for embedded application

Thanks to their high energy/power density and extended life cycle, lithium-ion batteries (LIBs) are currently the state-of-the-art power sources for electrified powertrain systems. Safety operation of LIBs is of vital importance for the development of electric vehicles (EVs). However, reliability and safety of electrified vehicle can be compromised due to overcharge (OC), overdischarge (OD),  internal short circuit (ISC) or external short circuit (ESC) of the battery. They can cause irreversible battery damages, or even lead to battery thermal runaway (TR), which is a catastrophic failure of on-board batteries. Therefore, fault diagnosis and mitigation strategies for EVs’ battery are critical functions to prevent TR.To this end, this presentation will focus on battery incipient short-circuit (SC) diagnosis. Because SC is an important stage before TR regardless of different kinds of battery abuse conditions. Furthermore, during the incubation period of SC, no electrical or thermal thresholds are exceeded for a long time before TR. Therefore, detection of incipient SC at its earliest stage is meaningful as it can prevent battery failure. However, incipient SC fault signature is weak as it may look like healthy operating conditions and fault features may be concealed in environmental nuisances. Hence its detection is challenging.

Jianwen Meng received the Master’s degree in Electrical engineering from University of Nantes, Nantes, France, in 2017. He is currently working toward the Ph.D. degree with the ESTACA Engineering School, Saint-Quentin-en-Yvelines, France; and also with GeePs | Group of Electrical Engineering – Paris, CNRS, CentraleSupélec, Université Paris-Saclay, Sorbonne Université, France with Prof. Demba Diallo and Prof. Moussa Boukhnifer. Jianwen’s research interests include fault diagnosis, fault-tolerant control and energy management with the background of electric vehicle.

Expert Group Meeting – Smart Maintenance

The meeting planned on April 2 was cancelled due to the Covid-19 outbreak and we have now arranged an “online” meeting as a substitute until we can arrange meetings as usual. We hope that time will come soon.

And, our sincere apologies for the short notice term for this meeting, it was a result of availability of presenters and time zone alignment between Switzerland and Singapore.

Program:

10.00-10.45 “Vibration-based fault detection in CNC machines” presented by Dr. Farzam Farbiz

10.45-11.30 “Digital services in the mobility market: how to optimize value with co-creation” presented by Ruben Lorenzo

For registration, please send a message to Thomas.palme@ge.com or to merg@zhaw.ch and we will send you the MS TEAMS link to join the meeting.

Dr. Farzam Farbiz is currently a senior scientist with the Department of Computing & Intelligence, Institute of High Performance Computing (IHPC), Agency for Science, Technology, and Research (A*STAR), Singapore (https://www.a-star.edu.sg/ihpc). His current research interest is on using physics-based AI to improve the performance of data-driven based machine learning models, and how these new models can be applied for and be benefited by manufacturing applications.

Ruben André Lorenzo is Head of Sales at Siemens Mobility Services. He has been with Siemens since 2009 and is responsible for developing innovative services with a focus on the digital service business.

These two presentations touch base on both “Analytics” and “Business case” areas of Smart Maintenance, hence this will be a very interesting meeting!

Expert Group – Smart Maintenance Event

Date: 21.01.2020 3:30pm

Our keynote presentation focusses on “Condition-based Maintenance and Resistance to Change” at the German engineering company Heidelberger Druckmaschinen. Hanna Sotnikova of USU project partners will present the solutions and experiences made as part of this comprehensive digitalization and smart maintenance project. We also look forward to Work in Progress discussed by Lee Sacco of Oracle, followed by an Apero afterwards.

Program:

3:30 pm Welcome & Introduction

3:45 pm “Heidelberger Druckmaschinen: Condition-based Maintenance and Resistance to Change”, presented by Hanna Sotnikova (USU)

4:30 pm Work-in-Progress, presented by Lee Sacco (Oracle)

4:50 pm News & Outlook

Followed by Snacks and Drinks at around 5 pm

Location: ZHAW Zurich, Lagerstrasse 45, Conference room E0.11 on ground floor

Registration: Please register by 13 Jan by email to Angela Meyer

Meet-an-Expert: As usual we are offering “Meet-an-Expert” one-on-one sessions starting 2:30pm as a service and an opportunity to discuss your Smart Maintenance topics and get feedback from technical experts. To book please email Angela Meyer.

Expert Group Meeting – Predictive Maintenance

On behalf of the industrial and academic leaders of our group, I am pleased to invite you to our first meeting of this year. The topic is deep learning for predictive maintenance. We will have Distran presenting their handheld sensor that overlays video and acoustic information, and ZHAW Prof. Dr. Thilo Stadelmann who will talk about deep learning use cases in the industry.

The date is May 10th, starting at 14hrs. The location of the meeting is TL 202 at ZHAW School of Engineering, Technikumstrasse 9, Winterthur.

Find the invitation attached as a pdf, and please let us know that you are coming to estimate the amount of food and drinks.