Computer-Assisted Troubleshooting for Efficient Off-board Diagnosis

This licentiate thesis considers computer-assisted troubleshooting of complex products such asheavy trucks. The troubleshooting task is to find and repair all faulty components in a malfunc-tioning system. This is done by performing actions to gather more information regarding whichfaults there can be or to repair components that are suspected to be faulty. The expected cost of theperformed actions should be as low as possible. The work described in this thesis contributes to solving the troubleshooting task in such a waythat a good trade-off between computation time and solution quality can be made. A frameworkfor troubleshooting is developed where the system is diagnosed using non-stationary dynamicBayesian networks and the decisions of which actions to perform are made using a new planningalgorithm for Stochastic Shortest Path Problems called Iterative Bounding LAO*. It is shown how the troubleshooting problem can be converted into a Stochastic Shortest Pathproblem so that it can be efficiently solved using general algorithms such as Iterative BoundingLAO*. New and improved search heuristics for solving the troubleshooting problem by searchingare also presented in this thesis. The methods presented in this thesis are evaluated in a case study of an auxiliary hydraulic brakingsystem of a modern truck. The evaluation shows that the new algorithm Iterative BoundingLAO* creates troubleshooting plans with a lower expected cost faster than existing state-of-the-art algorithms in the literature. The case study shows that the troubleshooting framework can beapplied to systems from the heavy vehicles domain. This work is supported in part by Scania CV AB, the Vinnova program Vehicle Information and Communi-cation Technology VICT, the Center for Industrial Information Technology CENIIT, the Swedish ResearchCouncil Linnaeus Center CADICS, and the Swedish Foundation for Strategic Research (SSF) StrategicResearch Center MOVIII. Department of Computer and Information ScienceLinköping universitetSE-581 83 Linköping, Sweden