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There is extensive literature on the reconfiguration of manufacturing systems; however, there are only a few decision support approaches that allow full advantage to be taken of the flexibilities introduced by this paradigm. Existing approaches do not consider expert knowledge to deal with new occurrences of similar, previously encountered disturbances. Most approaches are preventive and off-line planning and scheduling approaches, thus missing updated accurate data about plant activities that may trigger reconfiguration decisions and make such decisions worth consideration. In this article, we design a decision support system to suggest candidate configurations and select a suitable configuration considering a knowledge-based multi-criteria decision making approach. Expert knowledge is captured using an ontology, which is used both to monitor the manufacturing system and to make configuration recommendations. A multi-criteria decision-making approach based on TOPSIS relies on the recommended configurations to select a suitable configuration. An industrial case study shows how the suggested approach can be used to reconfigure the system at the execution stage to cope with disturbances in a reactive manner. [ABSTRACT FROM AUTHOR]