A broad range of real-world systems can be defined using discrete-time hybrid systems, e.g., chemical process plants and manufacturing systems. We characterize this application domain using a class of discrete-event systems, max-plus linear discrete-event systems, which captures synchronization without concurrency or selection. The model framework of these hybrid systems is non-linear in a conventional algebra, but linear in the max-plus algebra, thereby enabling linear-time inference. We use an observer-based framework for monitoring and diagnosing max-plus diagnostics models, and further improve computational efficiency by searching over only the most-likely space of behaviours. We illustrate our approach using a chemical process-control example.