Agent-based technologies can be applied to many aspects of manufacturing. The need for responsive, flexible agents is pervasive in manufacturing environments due to the complex, dynamic nature of manufacturing problems. Two critical aspects of agent capabilities are the ability to: (1) classify agent behaviors according to autonomy level, and (2) adapt problem-solving roles to various problem-solving situations during system operation. This issue is addressed by research on Sensible Agents, capable of Dynamic Adaptive Autonomy. In Sensible Agent-based systems, levels of autonomy constitute descriptions of agent problem-solving roles. These roles are defined along a spectrum ranging from command-driven, to consensus, to locally autonomous, to master. Dynamic Adaptive Autonomy allows Sensible Agents to change autonomy levels during system operation to meet the needs of a particular problem-solving situation. This paper provides an overview of the Sensible Agent testbed, and provides examples showing how this testbed can be used to simulate agent-based problem solving in manufacturing environments.