Towards the development of a predictive maintenance concept: A dynamic concept beyond fixed schedules – Lely
|Company Name / Department||
Oscar Moers, Ipek Kivanc, and, Claudia Fecarotti
|Optional remote work|
|Travel expenses (own account or reimbursed by the company)|
|Housing arranged by company||No|
|Housing expenses (how much per month, own account or subsidized by the company)||Own account|
|Study program||OML, MSE|
Working at Lely
It is an amazing opportunity at an international innovative company, leader in the agricultural industry. In other words, enough to learn for an intern!
- Working in an international environment where you can really make an impact with your contribution;
- You will work at one of the most innovative organizations in the Netherlands;
- Freedom in organizing your own work;
- Lots of responsibility;
And the best cappuccinos made by our own barista and fresh milk directly from our farm from one of our colleagues.
Below are some useful links: https://www.lely.com/about-lely/our-company/ https://www.lely.com/about-lely/our-company/vision-and-mission/ https://www.lely.com/maintenance/technical-service-support/ https://www.lely.com/maintenance/
Lely is traditionally an Original Equipment Manufacturer (OEM) which supplies innovative products along with some technical service including necessary repairs and warranty. Nowadays Lely is undertaking a “servitization journey” aimed at upgrading the company from an OEM, to a service provider. This means that Lely will not only supply products, but the technical services provided to the client as per contract will be a tailored preventive maintenance service optionally bundled with a lump sum for break-down services. The offered maintenance services develop from corrective maintenance, via preventive and predictive maintenance to pro-active maintenance. One of the goals of the servitization journey is to offer customers 100% uptime for Lely products, with no unscheduled breakdowns and limited number of scheduled service visits, along with a minimization of the maintenance costs and a maximization of the product output performance. The offered maintenance services develop from corrective maintenance, via preventive and predictive maintenance to pro-active maintenance. This research plan is meant to contribute to Lely’s servitization journey by ultimately developing a decision support system for initiating maintenance actions and their clustering for a machine as a whole during the entire life of the machine. The decision support system will develop “optimal” maintenance concepts for the machine during the (1) design phase, (2) early exploitation phase and (3) full exploitation phase, respectively. Each phase has different requirements and challenges related to the uncertainty of the failure and degradation processes, which are strictly dependent on the availability of engineering and field data. The decision support system should work as one system, but embed models tailored for each phase.
The ultimate vision is to have a machine with maintenance concept that is customer specific optimized on cost, downtime and performance, by fully implementing predictive and pro-active maintenance. The relevant components are continuously monitored by means of sensors. The IoT (Internet of Things) technology combined with AI (Artificial Intelligence) techniques will enable the timely prediction of failures and times to degrade to relevant degradation thresholds, as well as the selection of the appropriate maintenance action. Accurate predictions of the remaining useful life of components will enable to minimize the loss of life while also minimizing the risk of unexpected failures. The decision support system will enable “individualization” of the maintenance concepts based on customer preference, external circumstances, service conditions and machine usage.
If the OEM wants to achieve 100% uptime, the OEM can choose either to further develop components or to maintain them. The predictive maintenance project was initiated in 2020 in collaboration with Lely and TU/e, is currently in the stage of moving to a dynamic maintenance concept. This prompts the question:
‘How can we develop a dynamic maintenance concept optimized against multiple conflicting objectives over a finite life span?
This research question delves into the development of an advanced maintenance concept for multi-component heterogeneous systems, surpassing traditional fixed schedules. With the benefits of technological advancements and sensor utilization, we can monitor component conditions in real time, allowing us to focus on timely, efficient maintenance and preventing unexpected breakdowns.
Our research aims to establish a dynamic maintenance concept that adapts to the current state of components, contrasting it with static maintenance concepts reliant on fixed schedules. The optimization of this maintenance approach recognizes the presence of multiple, often conflicting objectives, such as minimizing downtime, reducing costs, and maximizing component lifespan. We concentrate on maintenance within a finite operational lifespan, acknowledging the limited durability of components and systems. Therefore, the maintenance strategy must account for this temporal limitation.
To address this research question, we will explore deviations from fixed maintenance schedules, the clustering of maintenance activities, considerations of economic and structural dependencies, and the integration of continuous monitoring for informed maintenance decisions. The ultimate objective is to develop a comprehensive and adaptable maintenance strategy that optimizes system performance while effectively managing constraints and objectives.
More information: firstname.lastname@example.org