Case Management supports knowledge workers in defining, executing, and monitoring the handling of their cases, e.g. in healthcare or logistics. Fragment-based case management (fCM) allows to define a case model with the help of several process fragments, which can be flexible combined at run-time based on case characteristics and the case worker's intuition. Cases are often influenced by unknown exception, e.g., the sudden change of patient condition's or a storm delaying transports. So far, fCM only reacts to known circumstances. In this paper, we want to extend fCM by an exception handling approach. Thereby, existing exception patterns for workflow systems are used and extended by the fragment-level for handling unknown events. In order to enable direct integration and avoid a duplication of semantics, precise rules are specified in order to clarify how to extend which pattern in detail. The applicability of the developed exception handling technique is exemplified on a last mile delivery for parcels.

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In order to achieve their business goals, organizations heavily rely on the operational excellence of their business processes. In traditional scenarios, business processes are usually well-structured, clearly specifying when and how certain tasks have to be executed. Flexible and knowledge-intensive processes are gathering momentum, where a knowledge worker drives the execution of a process case and determines the exact process path at runtime. In the case of an exception, the knowledge worker decides on an appropriate handling. While there is initial work on exception handling in well-structured business processes, exceptions in case management have not been sufficiently researched. This paper proposes an exception handling framework for stage-oriented case management languages, namely Guard Stage Milestone Model, Case Management Model and Notation, and Fragment-based Case Management. The effectiveness of the framework is evaluated with two real-world use cases showing that it covers all relevant exceptions and proposed handling strategies.