Description
Maintenance of electrical buses (EBs) is based on corrective and preventive actions. Corrective actions are performed in response to a failure on the road, which leads to inconvenience, loss in passengers' confidence, and higher cost of repairs. The latter are scheduled in advance independently of the bus' condition. This leads to actions that are taken prematurely, or after failure.
We propose condition-based maintenance that is based on Maintenance 4.0. This is an intelligent machine-assisted digital version of traditional condition-based maintenance. It includes connectivity technologies to sources of data, and methods to collect, analyze, and recommend actions based on the latest information gathered from sensors installed on each EB. We propose installing a connected system on each bus to warn the driver and the decision makers when actions must be taken. A self-healing system will be installed on each EB to allow the bus to reach the closest service center before failure. We will conduct analytical and experimental proof-of-concepts for these systems at three laboratories located at École Polytechnique, École de technologie Supérieure (ETS), and Solutions Serafin.
The impacts of this project include the creation of an intelligent testbed and system that allows the physical simulation of failure and offers autonomous and adaptive maintenance support to the EBs on the road, the quick transfer of technologies, leveraging the efforts of the industrial partner, Solutions Serafin, to be the first maintenance center that offers maintenance 4.0 capabilities for the EBs in America. Québec will be the first province in Canada to adopt maintenance 4.0 concepts and apply them successfully to the maintenance of EBs. Eight highly qualified personnel will be trained.
Institutions
Polytechnique Montréal
