Intelligent manufacturing systems are often designed with decision-making ability and higher capabilities than required, referred to as capability redundancy. Considering the effects of degradation and wear, during operation system capability redundancy decreases gradually under uncertainty. This uncertainty needs to be considered to decide if the requirements are still satisfied after some years of operation. The proposed approach includes this uncertainty in the system model using SysML as modeling language and is represented through a metamodel. The metamodel encapsulates capability redundancy and multi-requirement satisfaction oriented decision-making under uncertainty. The metamodel can be used as knowledge base supporting intelligent decision-making during runtime as demonstrated in earlier work and thereby increasing the overall equipment effectiveness. A conveyor system is introduced as case study.     «

Intelligent manufacturing systems are often designed with decision-making ability and higher capabilities than required, referred to as capability redundancy. Considering the effects of degradation and wear, during operation system capability redundancy decreases gradually under uncertainty. This uncertainty needs to be considered to decide if the requirements are still satisfied after some years of operation. The proposed approach includes this uncertainty in the system model using SysML as mo...     »