Decision-making of reconfiguration timing for reconfigurable manufacturing systems considering functionality and capacity

For the problem that reconfiguration timing decision-making of Reconfigurable Manufacturing System (RMS), a decision-making method considering machining functionality and capacity was proposed. The influencing factors of RMS dynamic complexity were identified from the machine level and cell level, and a RMS dynamic complexity quantitative model was built based on information entropy, which could be solved through the state probability of machining functionality and capacity calculation. A RMS reconfiguration timing decision model was constructed with cusp catastrophe, whose control variables were positive complexity and passive complexity. According to the cusp catastrophe mutation determination condition, RMS state mutation could be recognized, which was RMS' reconfiguration timing. A case study from a RMS shop floor of an institute was presented to validate the effectiveness and practicability of proposed method.