The opportunistic maintenance (OM) approach allows exploiting the stoppage for performing additional maintenance actions alongside those planned, to save cost and time. This study aims to propose a graphical approach to identify the optimal maintenance grouping strategies in an operating process. The failure of a specific component is predicted by using the statistically-derived probability distribution function that reflects its time-variant failure behaviours. The periodic maintenance schedule is first derived, and the system failure likelihood is predicted within each time interval. The failure of one of the component creates an opportunity to reschedule maintenance activities, which can be carried out while replacing the failed components. The expected cost to mitigate the failures (‘Sinks’) can be reduced by the expected maintenance reschedule cost savings (‘Sources’) based on the derived schedule previously. In this work, Pinch Analysis is used as a targeting tool to determine the maximum cost savings and expected cost required to handle unexpected plant shutdown. The methodology is presented and demonstrated with a case study, featuring the component replacement for a hydrogen compressor in an oil refinery. The results show that about 35 % of the expected failure cost would need to be invested for opportunistic maintenance at the earlier time, minimising the risk of failure, while the remaining 65 % can be saved. The extra savings at the end of the period also suggest the maintenance grouping can be further reduced. The limitations and potential future development of the framework are discussed as well.