Careful assets maintenance planning is crucial in ensuring minimal process interruptions in a chemical plant while fulfilling production demand. This paper aims to propose a systematic framework with easily comprehensible tools for effective and efficient maintenance optimisation. The first step is to identify the optimal maintenance time for the equipment depending on their failure time distributions, minimising the expected maintenance cost. A maintenance tasks clustering model is then formulated for grouping individual preventive maintenance actions, to save the production downtime and cost. The solutions from long-term planning are transferred to the short-term planning model for detailed manpower scheduling. In this work, Pinch Analysis is selected as the targeting tool to maximise the available manpower utilisation and target the extra working hours needed. The daily maintenance tasks are formulated as the ‘Demand/Sink’, while the workers’ shifts are the ‘Supply/Source’. This method not only provides excellent visualisation of the problem/results, it also enables tuneable workers’ daily schedules, tasks delay and the required earliest finished date of a task. A case study of a chemical plant, namely the Tennessee Eastman problem is used to elucidate the proposed approach. The results show that extra 22 h are needed for 8 h shift (5 d/week) for a single worker, but extra 13 h for 12 h shift (4 d/week).