Multilocation Inventory Systems With Centralized Information.

The management of multi-echelon inventory systems has been both an important and challenging research area for many years. The rapid advance in information technology and the emphasis on integrated supply chain management have new implications for the successful operation of distribution systems. This research focuses on the study of some fundamental issues related to the operation of a multilocation inventory system with centralized information. First, we do a comparative analysis to evaluate the overall performance of individual versus centralized ordering policies for a multi-store distribution system where centralized information is available. This study integrates the existing research and clarifies one of the fundamental questions facing inventory managers today: whether or not ordering decisions should be centralized. Next, we consider a multi-store distribution system where emergency transshipments are permitted among these stores. Based on some simplifying assumptions, we develop an integrated model with a joint consideration of inventory and transshipment components. An approximately optimal (s, S) policy is obtained through a dynamic programming technique. This ordering policy is then compared with a simplified policy that assumes free and instantaneous transshipments. We also examine the relative performance of base stock policies for a centralized-ordering distribution system. Numerical studies are provided to give general guidelines for use of the policies

Reducing costs of repairable spare parts supply systems via dynamic scheduling

We study a system consisting of one repair shop and one stockpoint, where spare parts of repairables are kept on stock to serve an installed base of systems. Part requests are met from stock if possible, and backordered otherwise. Our objective is to determine initial stock levels and a policy for scheduling repair jobs such that holding and backorder cost are minimized. We propose two dynamic scheduling rules, compare their performance with the static priority rule, and show that even when stock levels and static priorities have been optimized simultaneously, dynamic scheduling rules often reduce total cost by more than 10%

Whole life costing optimisation with integrated logistics support considerations.

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