When we are asked to recall a memory, usually most, if not all of us, will not go through the events describing it step-by-step. If it is a good memory, we will usually associate it with feelings of happiness and for example, mental images of smile, laughter, or maybe bright colors to name a few. …
Context The CIMPLO-project aims at developing a cross-industry predictive maintenance optimization platform, which addresses the real-world requirements for dynamic, scalable multiple-criteria maintenance scheduling. The platform consists of three components: Data Infrastructure, Modeling Engine, and Optimization Engine. The Modeling Engine uses techniques from Predictive Maintenance to predict Remaining Useful Life (RUL) of vehicle components (brakes, engine, …
Remaining useful lifetime (RUL) is the time remaining until an asset no longer meets operational requirements. An accurate estimation of the RUL is central to the prognosis and health management (PHM) systems and to manufacturing engineering. Knowing the RUL helps to minimize catastrophic failure events, to dynamically optimize maintenance schedules as well as to select …
This video presents a concise overview of the CIMPLO research project funded by the Dutch funding agency NWO TTW and industry partners.
The CIMPLO Team attended the annual NWO-TTW program meeting Smart Industry 2016 (SI2016) held on the 8th October 2019. The meeting took place in the new NWO office in Utrecht. This year all PhDs involved in SI2016 projects were encouraged to present their project and research in a short video. The videos were presented throughout the day and could be judged by all attendees via an online app. Furthermore for each project one industry partner and one PhD had to present a short pitch about their collaborative work within the ongoing research. The attendees were also able to vote on the best pitch via the online app. Afterwards, over drinks, prizes were presented to the winning videos and pitches. The SI2016 program meeting was again an excellent event to network with the other project partners (academic and industrial).
Novel Algorithms for Multiobjective Optimization of Maintenance Scheduling To find optimal schedules for maintenance is a difficult combinatorial puzzle that belongs to the class of so-called NP-hard problems, for which only algorithms with an exponentially growing running time are known. Researchers in the CIMPLO project managed to model maintenance scheduling as a multiobjective problems and …
On May 8th the fourth CIMPLO user committee meeting will be held at LIACS, to inform and discuss with all partners, users as well as NWO the progress and future plans of the project.
The CIMPLO team visited KLM Engine Services on the 17th October 2018 at Schiphol Airport. KLM is one of the industrial partners within the CIMPLO project. The very productive and fruitful meeting was intended to discuss data availability for the optimization platform. The meeting ended with a tour of the KLM engine services workshop providing team members an in depth view of the practical side of engine maintenance.
The CIMPLO Team attended the annual NWO-TTW program meeting Smart Industry 2016 (SI2016) held in Utrecht on the 9th October 2018. The meeting was organized for all recipients of the SI2016 grand, and allowed not only to present the current status of the projects but also to network and share experiences. This included members of the academic research groups as well as the collaborating industrial partners. An external moderator facilitated in-depth discussion and exchange of ideas and possible future-collaborations.
As systems and equipment become more complex and expensive, the competition drives industries to become increasingly concerned about system reliability and availability. The need to reduce maintenance and logistics costs while at the same time minimizing the risk of catastrophic failures, and maximizing system availability is leading a drive towards predictive maintenance. In predictive maintenance, …
