- Tiddens, W.W., Braaksma, A.J.J., Tinga T., 2015. The adoption of prognostic technologies in maintenance decision making: a multiple case study.
- Tiddens, W.W., Braaksma, A.J.J., Tinga T., 2015. Supporting the route to implementation of prognostic technologies for maintenance decision making.
Wieger Tiddens is a PhD-candidate working on maintenance prediction and decision making for life cycle management of complex moving assets. This research is part of the Tools4LCM project, funded by the Netherlands Ministry of Defence and the National Aerospace Laboratory NLR.
The research project aims to develop specific methods and tools to enable structured maintenance decision making, supported by advanced maintenance analyses, or: diagnostics and prognostics.
A lot of research is conducted in developing specific models and algorithms, many academic researchers have discussed or commented on the technical features of these technologies and many techniques are described in the literature. However, research suggests that a lot of companies applying these advanced maintenance techniques experience a gap between potential and realized benefits.With this study we envision to use advanced maintenance analysis effectively to support decision making for life cycle management and aid business purposes rather than only using these analyses for technical evaluations.One of the goals of this study is therefore to enable more widespread adoption of these techniques, we study the current usage of these techniques within companies and try to identify the issues and challenges companies experience. In the remainder of this research, we will propose and develop specific methods to overcome these issues to enable the adoption and effective usage of these advanced maintenance analyses to aid decision making for maintenance and life cycle management.
This project aims to develop quantitative tools to improve the Life Cycle Management process (both in general and specifically within the Ministry of Defence). Using data from different sources, i.e. failure, logistic, maintenance, usage, condition and financial data, methods are developed to quantify the maintenance performance. Both the costs and the resulting performance (i.e. realized availability) are addressed. A team of representatives from Airforce, Army and Navy has been formed to work on relevant case studies, like the CV-90, Cougar, F-16 and LCF, and provide useful input data. In addition the NLDA / UT researchers analyze the data and develop the new methods.
Next to my current position as a PhD-candidate, I’m active as a reservist in the Royal Netherlands Army. We protect and defend (temporary) military objects on Dutch territory and provide military assistance and support.
MaxGrip is a consultancy firm specialised in Asset Performance Management. MaxGrip provides integrated solutions (Consultancy, Software, and Staffing). Its strength lies in translating maintenance methodology, theory and business goals into practical solutions.
The main projects I was involved in:
- Maintenance concept development and improvement at Tata Steel.
- Project Maintenance Engineer (PME) at BOF plant Tata Steel.