It is widely accepted that future generation warehouses require a real-time visibility and accuracy of inventory data in order to maintain efficient and effective warehousing operations, optimal SKU levels, and up-to-date inventory management and control of incoming and outgoing goods that often occur today at increasingly centralised distribution centres. This phenomenon is partially due to a sharp rise of online shopping activities in many countries where customers now prefer to purchase goods online and demand a fast delivery of ordered products to be dispatched directly at their door steps. Thus, there is a strong desire from supply chain and logistics sectors to seek even more efficient and cost-effective methods for sorting, storing, picking and dispatching goods at increasingly centralised distribution centres in which automation and integration of warehousing systems is inevitable. As part of a research programme for future generation warehouses, this thesis presents an investigation into some design theories and an integrated optimisation methodology for a future generation warehousing system in which an RFID-based inventory management system has the capability of interacting with a proposed RFID-enabled automated storage and retrieval mechanism without any human intervention. An efficient item selection algorithm based on pre-defined rules was developed and implemented within an RFID-based inventory management system, which also allows a manipulation of RFID-tracked items to seek an optimal solution by assigning a priority to one of selected items to travel in an order (if applicable) with both minimal travel time and waiting time to a specified collection point; this maximises efficiency in material-handling and minimises operational costs. A pilot test was established and carried out based on the proposed RFID-enabled inventory management system for examining the feasibility and applicability of its embedded RFID-enabled item-selection optimisation algorithm. Experimental results demonstrate that the developed methodology can be useful for determining an optimal solution (or route) for the RFID-enabled pusher to push a selected RFID-tagged item located randomly from a storage rack to an output conveyor system in a sequence that allows all the selected items traveling to a specified collection point with a minimal waiting time for packing. In theory, such a system can also be expanded by incorporating other pre-defined selection parameters as requested by users. Moreover, a multi-objective model using the multi-criterion fuzzy programming approach was developed and used for obtaining a trade-off decision based on conflicting objectives: minimisation of the total cost, maximisation of capacity utilisation, maximisation of service level and minimisation of travel distance within the proposed warehousing system. The developed model also supports design decisions in determining an optimum number of storage racks and collection points that need be established for the proposed warehouse. To reveal the alternative Pareto-optimal solutions, a decision-making algorithm namely TOPSIS was also employed to select the best Pareto-optimal solution obtained using the multi-criterion fuzzy programming approach. Case-studies were also conducted to demonstrate the feasibility and applicability of the developed multi-objective model and optimisation methods. The study concluded that the research work provided a useful basis by developing a framework as part of contributions in design theories and optimisation approaches for integration of future generation RFID-based warehousing systems and a practical means of exploring the further work in this field.
|Date of Award||Sep 2017|
|Supervisor||Qian Wang (Supervisor) & Nick Bennett (Supervisor)|