How can big data assist in predictive maintenance for rollercoasters – Vekoma Rides

 Overview

Company Description

Ingenuity that moves you.
Vekoma Rides, designs, manufactures and builds new and innovative rides world wide. Every single day our 300+ specialists work with unprecedented energy to move the boundaries of ride experiences to new heights. Vekoma Rides contributes to the success of Amusement and Theme Parks around the world delivering a real experience. Every year millions of people across the globe are delighted, thrilled and profoundly move by coasters and attractions that bear the exceptional Vekoma brand, the world’s leading roller coaster enterprise. We have the world’s largest in-house expertise centrum, so no challenge is too big or too difficult for us to handle.

Vekoma Rides Parts & Services BV main objective is to support the park’s maintenance staff and operators, in such a way to ensure that the Vekoma attractions will operate in a reliable and above all safe manner. Assistance in maintenance, training, advisory, troubleshooting or relocations we are at your service.

Project Description

Vekoma Rides Parts & Services is currently integrating a support platform for our clients to assist them with their maintenance tasks. This platform allows us to store several parameters for general trend information. Additionally the connection allows us to gather more data for future purposes.

One of them is to be able to store and use data to do predictive maintenance to increase the uptime and prevent issues which could have been detected on forehand.

The data which is necessary for this purpose and how it can be used/integrated still has to be investigated.

Main question: “How can big data assist Vekoma Rides Parts & Services in predictive maintenance”.

Sub question: check the theory of design and maintenance, investigate which and how data can be gathered and how it can be used/analysed to assist in future maintenance.

Goals of the Project

The goal of the internship is to define a clear path towards predictive maintenance for our amusement rides, taking into consideration the use of our maintenance platform and the idea of big data.

Deliverables

Final deliverables will be determined in consultation with the student. Our thoughts:

• Start with a detailed roadmap towards predictive maintenance.
• Analysis of data that is to be gathered and analyzed to realize predictive maintenance.
• Advise on how to implement this data in the design process of the attraction.

Essential Student Knowledge

Our maintenance is currently mainly focused on mechanical parts, but over the last couple of years the designs shifted more and more to a complete mechatronic systems (e.g. with integrated drives and sensors).

So knowhow about mechanical design as well as the mechatronic aspect (measuring systems and datalogging) would be required.

More information: escf@tue.nl