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It has long been recognised that, in the military sector, the Integrated Logistics Support ILS can significantly enhance system effectiveness and add value to their competitiveness. Hence, it is not surprising that many organisations outside to the military support the ILS adoption to increase their competence level. Even though the ILS underlying theory is general, there is a lack of suitable methodology that facilitates ILS implementation in other industries such as Oil & Gas industry. In particular when considering complex systems with long life-span, the optimisation of maintenance-related activities is important to fulfil system readiness, safety and whole life cost requirements. Modern petroleum equipment like gas turbines and drilling rigs are dependent on readily available maintenance supports in order to maximise their operational ability. Therefore, it has been identified that the study should be conducted to an effective use of ILS with the petroleum industry. In doing so, the usage of the ILS framework as a decision tool for maintenance optimisation is outlined. This framework embraces ILS concepts to support asset managers in developing their maintenance strategies. Level of repair analysis and spare parts management have been identified as potential areas for enhancing the use of ILS. In particular, maintenance optimisation is approached as a trade-off between investment in spare parts level and repair capacity. The developed framework delivers cost-effective support strategies obtained with iterative optimisation algorithm built on heuristics and genetic algorithm techniques. Finally, this algorithm has been implemented into computational algorithms. The framework can be employed to identify the optimum level of spare parts and the optimum amount of repair capacity for multi echelon repair network and multi-indenture systems. The framework has been used to carry out optimisations intended to maximise the availability of gas turbines by varying logistics support parameters. Typical results have shown that a joint optimisation of spare parts and level of repair analysis leads to better results than optimising them separately and emphasises the need for the developed framework. As part of this research, an expert panel validation method has been used to both refine the design of the developed framework and also evaluate its functionality from experienced practitioners within the Algerian petroleum industry. The results of this validation have demonstrated the advantages of integrating spare part management and level of repair analysis LORA to the problem of maintenance optimisation and shown that the framework is able to deliver optimal maintenance supportability decisions. The generic framework developed in this thesis can be seen a novel and comprehensive model for integrating two ILS elements into the operating tool in a manner that improves maintenance support provision, while remaining both flexible and usable; and therefore as a contribution to a better adoption of ILS technique within Algerian Petroleum Industry.