Abstract

Preventive maintenance for an automobile, significantly reduces the time of a vehicle to be out of service; nonetheless, knowing when any kind of maintenance or repairs should be done to the automobile it is not an exact science. Mechanical and repair shops usually provide service as a reactive measure, and up to this date, there are not automated tools to let know the user when should the next visit or repair must be done.

Utilizing case based reasoning, an informatics automated system was build, so that it takes and processes data including manufacturer’s standards and the vehicle’s environment, converting it into information, generating a more precise data about the automobile so that it can predict when should the next repair occur.

Once the project concluded, it allowed to observe how the technic chosen with a growing database with relevant information about the automobile and it’s similar, all the repair shops who will use this tool, will be capable to give a better service for their customers, and also automobile owners will get benefits, since they can now plan ahead checkups and repairs which in the end will transform in a better vehicle overall health and time saving for its owners.

Keywords: Maintenance prediction; lifespan prediction; repair parts use; prediction system; CBR; RBC