M. Tech. (Department of Mechanical Engineering, Faculty of Engineering and Technology), Vaal University of Technology. / The subject of maintenance optimisation is not new, and many researchers have explored it. However, it is seen that one optimisation solution cannot be used in all industries. Each industry and equipment thereof are unique as the product streams differ, layouts and operation variables, to name a few. Though Turn-around management is the most used strategy in petrochemical industries. Equipment downtime remains the biggest challenge thus, the purpose of the study was to optimise the maintenance practices used on the critical electromechanical equipment in Sasol Synfuels Catalyst Preparation using both the Analytical Network and Analytical Hierarchy multi-decision approach. Data was collected from the SAP system database, of which the breakdown work orders was obtained from the period of January 2016 to June 2021. The data was collected for each 13 electromechanical equipment identified in the catalyst preparation unit. The applied maintenance strategies employed on the electromechanical equipment in the catalyst preparation unit was also analysed using the Meridium maintenance strategy software tool utilised in Sasol Synfuels. An analysis and identification of the critical equipment within the unit were obtained with the use of two different methods, namely the JADERI, (2019) and AFEFY, (2010) approaches. A theoretical distribution was drawn after that in order to assess the effectiveness of the current maintenance strategy compared to the identified key performance indicators. The theoretical distribution analysis was used to determine the plant utilisation, availability, and maintenance cost. The analytical network and hierarchy process application, and the super decision network model framework, were analysed to obtain the maintenance optimisation solution. Though the ANP and AHP approaches have different problem identification frameworks and cluster dependencies, it is seen that both methods portray more or less similar results. Both methods indicate that in order to achieve an optimised maintenance strategy within the catalyst preparation unit, condition-based maintenance strategy is the most weighed alternative node with 50% for optimal maintenance solution. The least most weighed alternative node is corrective maintenance, weighed at 7%. This is true as corrective maintenance is applied once a breakdown has occurred, of which the aim is to avoid unforeseen breakdowns. Fixed time maintenance is the second most weighed maintenance strategy with 30%, followed then by the operate to failure strategy at 13%. Considering that the operation to failure maintenance strategy is applied based on the consequence of failure and maintenance cost as well as mean time to repair, this is then concluded as practical as RCM priorities predictive and preventative strategies to be employed. It was drawn, for criteria nodes, that the ANP approach resulted in the environmental safety impact as the most important criteria to consider when applying the optimal maintenance strategy in the Sasol Synfuels Catalyst preparation unit. The environmental safety impact was rated at 0.33, followed by availability with a factor of 0.32. The least weighed criteria nodes are then the maintenance cost and MTTR, both with a factor of 0.17. This proves to true considering that the petrochemical industry is considered a high-risk industry as it processes and produces hazardous chemicals The AHP approach structure however, does not consider interdependencies through the criteria and alternative clusters thus the alternative weight could not be defined. The results obtained prove that the ANP approach is the most practical mutli criteria decision making method for maintenance optimisation compared to the AHP approach.