On-board Diagnostics Framework

For as long as complex machines have been around there has also been a need for accurate diagnostic and prognostic capabilities. Over the last decades there have been many attempts to develop and implement systems with various degrees of diagnostic and prognostic abilities, some successful some not. This master thesis presents a software architecture that is used to implement an on-board diagnostic framework capable of advanced diagnostics and prognostics in industrial vehicles. The presented architecture consists of a set of modules that focuses on performance, scalability and simplicity that fulfills the demands of current and upcoming diagnostic and prognostic techniques