Reliability Seminar 2021
We are proud to announce our LIVE Reliability Seminar on Data Science for Reliability & Root Cause Analysis:
Thursday 14 and Friday 15 October 2021
High Tech Campus Eindhoven
Join us!
Our intention is to make our seminar in 2021 an even bigger success ! In the months leading up to this event, we will be sharing insights and innovations on Reliability 2.0, Data Science, and Root Cause Analysis. And, together with you as speaker and together with our participants, we would like to give you more opportunities to share knowledge and experiences between data science and reliability experts. And thereby to be able to accelerate your projects, improve quality and reliability, start co-developments, discover growth opportunities, learn from each other and have fun!
We will keep in touch, and don’t forget to regularly check this page, where we will continue to share insights, knowledge, and experiences in the exciting fields of Reliability & Data Science.
Let’s aim for an excellent Reliability Seminar in 2021!
Stay healthy and stay safe!
Reliability Competence Team – Holland Innovative
October 14th & 15th, 2021
During the Reliability Seminar we will explore the importance of reliability in the high tech industry. Together with all the visitors we want to answer these questions:
- What can Data Science mean for Root Cause Analysis, Condition Monitoring and Reliability Prediction?
- Will it lead to Reliability Engineering 2.0 – Life Time prediction per machine or per component based on machine data?
- How to collect the proper information and how to transform this into usable data?
- How to model the data to get accurate predictions?
- What is the role of the Reliability Engineer in connection with Data Science?
Conference Center, High Tech Campus Eindhoven
Keynotes, lectures and presentations, closing panel discussion. Including lunch, dinner and evening program.
Share knowledge and experiences between data science and reliability experts to be able to accelerate projects, improve quality and reliability, start co-developments, discover growth opportunities, learn from each other and have fun!
Reliability-, root cause analysis-, system- and lead engineers, data scientists, system- and software architects, program managers in hightech, mobility, energy, medtech and agrotech.
The Programme:
We are excited to offer you an impression what to expect on October 14 & 15, 2021. The seminar will be a mixed bag of presentations, panel discussions, executive round tables and matching events, all centred around our main theme: Data Science for Reliability and Root Cause Analysis. And yes, there will also be plenty of time to get together, to meet each other over drinks and to enjoy some of the engineering highlights the Eindhoven region has to offer.
We are proud to announce our keynote speakers:
Prof. Michael Pecht, CALCE, University of Maryland
Prof. Tiedo Tinga, University of Twente
Dr.-Ing. Martin Dazer, University of Stuttgart
Prof. Michael Pecht, founder of CALCE at University of Maryland, will present his keynote on Using Artificial Intelligence Methods for Data Insight Analysis, Health Monitoring and Prognostics.
Prof. Tiedo Tinga, professor at NLDA and University of Twente, will present his keynote on Predictive Maintenance – Combining Data and Physics.
Dr.-Ing. Martin Dazer will present his vision for future trends in reliability assurance using big data and machine learning based on their projects
But there’s more. Here’s a selection:
- We’re planning parallel tracks on the topics of Data Science (Big Data), Reliability 2.0 (e.g. Prediction, Reliability Centered Maintenance) and Root Cause Analysis.
- There will be an Executive Round Table, directly after the Keynote speakers on day one.
- We offer all participants the opportunity to talk to the experts in “Meet & Match” sessions during and after the breaks.
- Joint Panel discussions will focus on all the relevant themes of our seminar.
- An optional evening programme not only is the best occasion to get together in more relaxed circumstances but with specific site visits, it will also show some of the best practices from the Eindhoven based engineering tradition.
We hope you can understand – and maybe already feel – our enthusiasm for the upcoming Reliability seminar. Looking forward to seeing you there!
8:30 | Registration | |
9:00 | Plenary – Opening and Welcome | |
9:15 | Keynote prof. Michael Pecht | |
10:15 | Keynote prof. Tiedo Tinga | |
11:15 | Network Break | |
11:45 | Track A: Reliability 2.0 | Track B: Data Science, Root Cause Analysis |
Speaker Presentation | Speaker Presentation | |
12:30 | Lunch | |
13:30 | Track A: Reliability 2.0 | Track B: Data Science, Root Cause Analysis |
Speaker Presentation | Speaker Presentation | |
Speaker Presentation | Speaker Presentation | |
15:00 | Network Break | |
15:30 | Track A: Reliability 2.0 | Track B: Data Science, Root Cause Analysis |
Speaker Presentation | Speaker Presentation | |
16:15 | Pitches by Sponsors | |
16:30 | Plenary Panel discussion | |
17:00 | Meet & Match – Expert Sessions: illustrative summary | |
17:15 | Network Drink | |
18:15 | End of Day 1 | |
19:00 | Social Evening Program | |
Technical Inspired Innovative Dinner Centre of Eindhoven | ||
22:00 | End of Evening Program |
8:30 | Re-welcome | |
9:00 | Opening and Re-cap day 1 | |
9:15 | Keynote Dr.-Ing.M. Dazer | |
10:15 | Track A: Reliability 2.0 | Track B: Data Science, Root Cause Analysis |
Speaker Presentation | Speaker Presentation | |
11:00 | Network Break | |
11:30 | Track A: Reliability 2.0 | Track B: Data Science, Root Cause Analysis |
Speaker Presentation | Speaker Presentation | |
12:15 | Lunch | |
13:00 | Track A: Reliability 2.0 | Track B: Data Science, Root Cause Analysis |
Speaker Presentation | Speaker Presentation | |
13:45 | Meet & Match Summary | |
14:00 | Panel Discussion | |
14:45 | Closure and Wrap-Up | |
15:00 | End of Seminar |
Get to Know Our Keynote Speakers!
Abstract
For critical systems, it is very important that maintenance is performed at the right moment. Too early maintenance leads to high costs and spoiling of system lifetime, while being too late causes failures, leading to reduced reliability and availability. Predictive maintenance can assist in achieving just-in-time maintenance, and nowadays data analytics and artificial intelligence are believed to fully enable this. This presentation will show that a purely data-driven approach is not always feasible, especially in the military domain. It will be demonstrated that combining data with (physical) degradation models and knowledge on system failure behavior can lead to a much stronger approach. Moreover, this also helps to develop effective health and condition monitoring systems. Finally, some case studies from various application fields will be used to demonstrate the proposed approach.
Biography
Prof.dr.ir. Tiedo Tinga is full professor Life Cycle Management at the Netherlands Defence Academy (NLDA) in Den Helder and professor in Dynamics based Maintenance at the University of Twente. He holds a MSc and PDEng in Material Science and a PhD in computational mechanics. He has been working at the National Aerospace Laboratory NLR for 10 years as a senior scientist. In 2007 he joined the Netherlands Defence Academy, and since 2012, he combines this position with the part-time full professorship at the University of Twente.
His research focuses on improving the predictability of failures, aiming to improve preventive maintenance processes and to develop advanced predictive maintenance concepts. The research is based on understanding and modelling the physics of failure, and combined with advanced health and condition monitoring and data analysis. The research is applied to assets in various sectors of industry. Tiedo now leads research programs on maintenance at both institutes and has been (co-)supervising 15 PhD and PDEng students in the past 5 years. Tiedo has published around 60 papers in international ISI journals and conferences.
Abstract
The use of artificial intelligence (AI) methods, including machine learning, has been providing new insights in product reliability and new ways to assess and predict product reliability. This presentation will overview how AI methods have been used by the Center for Advanced Life Cycle Engineering at the University of Maryland and its sponsoring companies: to assess failures in devices; to assess changes in failure mechanisms in devices as a results of changes in environmental regulations; to monitor the health of electronics systems; to predict individual product reliability and forecast maintenance actions; and to reduce qualification time. Examples of each of these AI-based methods will discussed.
Biography
Prof Michael Pecht (25,000+ citations, 70+ H-Index) has a BS in Physics, an MS in Electrical Engineering and an MS and PhD in Engineering Mechanics from the University of Wisconsin. He is a Professional Engineer, an IEEE Fellow, a PHM Society Life Fellow, an ASME Fellow, an SAE Fellow and an IMAPS Fellow. He served as editor-in-chief of IEEE Access for six years, as editor-in-chief of IEEE Transactions on Reliability for nine years, editor-in-chief of Microelectronics Reliability for sixteen years, and editor of Circuit World. He has also served on three U.S. National Academy of Science studies, two US Congressional investigations in automotive safety, and as an expert to the U.S. FDA. He is the Director of CALCE (Center for Advanced Life Cycle Engineering) at the University of Maryland (UMd), which is funded by over 150 of the world’s leading electronics companies at more than US$6M/year. He is also a Professor in Applied Mathematics at UMd. He has written more than twenty books on product reliability, development, use and supply chain management. He has also written a series of books of the electronics industry in China, Korea, Japan and India. He has written over 700 technical articles and has 10 patents. In 2015 he was awarded the IEEE Components, Packaging, and Manufacturing Award for visionary leadership in the development of physics-of-failure-based and prognostics-based approaches to electronics reliability. He was also awarded the Chinese Academy of Sciences President’s International Fellowship. In 2010, he received the IEEE Exceptional Technical Achievement Award for his innovations in the area of prognostics and systems health management. In 2008, he was awarded the highest reliability honor, the IEEE Reliability Society’s Lifetime Achievement Award.
Biography
Dr. Martin Dazer completed his master’s degree in mechanical engineering at the University of Stuttgart in 2014. In 2015 Dr. Dazer began his doctorate as a research assistant in the field of reliability engineering at the Institute for Machine Components (IMA). Supported by the Knorr-Bremse AG, Dr. Dazer conducted research until the end of 2017 on simulative reliability predictions for casted components and on efficient testing methods. Since 2018, Dr. Dazer is working as the head of reliability engineering department at IMA and is also a lecturer for reliability engineering and Design of Experiments seminars as well as a consultant in the field of reliability technology, life testing and general testing methodology. In June 2019 he was awarded his PhD with his research on the topic of reliability test planning with consideration of prior knowledge from stochastic lifetime calculations.
Sign Up!
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- If you want to join our Seminar and benefit from meeting other experts, learn from presentations and Meet&Match expert groups, discover new opportunities, then please sign-up below !
- Attendance of 2-day Seminar including catered lunches and breaks: 495 Euro (ex VAT)
- Social Evening Program including Dinner on Thursday 14 October: 75 Euro (ex VAT)
Call for Speakers
We are looking for presenters who can share their experiences and ideas on this year’s topic: “Data Science for Root Cause Analysis and Reliability”. Studies and cases from companies, institutes and universities are welcome. We are looking for real-life examples, projects and cases related to the topic. We are especially looking for visionary ideas and strategies on this new field of expertise within Reliability and RCA using Data Science.
- Submit abstract – proposal: 31 May 2021
- Notification of acceptance: 21 June 2021
- Submit presentation: 1 September 2021
Our story:
How Holland Innovative helps the high tech industry to monitor and improve their processes
The importance of reliability in solving and preventing problems in high tech
When even optimal quality is not enough: Reliability makes the difference
“It takes a disaster to realize how important reliability is” – Professor Michael Pecht
Why do things break down – and when? Material science and data science offer the answer
Sponsors

HBM Prenscia – Reliasoft
ARDC Europe – Applied Reliability and Durability Conference
HBM Prenscia is a global leader in providing technology and engineering software products and services for reliability, durability, and performance. ReliaSoft software provides a powerful range of solutions to facilitate a comprehensive set of reliability engineering modeling and analysis techniques.

Partners
Contact:
High Tech Campus 29
5656 AE Eindhoven (NL)
T: +31 (0)40 851 4610
E: reliability@holland-innovative.nl